diff --git a/CHANGES.md b/CHANGES.md index a6e0ebd..10adb9e 100644 --- a/CHANGES.md +++ b/CHANGES.md @@ -1,4 +1,4 @@ -## Changes in 0.3.0 (in development) +## Changes in 0.3.0 (from 2026-07-22) - Sentinel-1 GRD analysis mode is now fully lazy, enabling seamless execution on local and distributed Dask clusters. diff --git a/docs/examples/sentinel_1_native.ipynb b/docs/examples/sentinel_1_native.ipynb index 23ef624..49ddfe6 100644 --- a/docs/examples/sentinel_1_native.ipynb +++ b/docs/examples/sentinel_1_native.ipynb @@ -100,8 +100,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 22.5 ms, sys: 3.07 ms, total: 25.6 ms\n", - "Wall time: 4.1 s\n" + "CPU times: user 24.7 ms, sys: 1.97 ms, total: 26.6 ms\n", + "Wall time: 280 ms\n" ] }, { @@ -611,7 +611,7 @@ " \n", "
<xarray.DatasetView> Size: 0B\n", - "Dimensions: ()\n", - "Data variables:\n", - " *empty*\n", - "Attributes: (2)
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- azimuth_time: 16689
- ground_range: 26642
azimuth_time(azimuth_time)datetime64[ns]2026-03-16T16:47:54.761834 ... 2...array(['2026-03-16T16:47:54.761834000', '2026-03-16T16:47:54.763331000',\n", + " '2026-03-16T16:47:54.764829000', ..., '2026-03-16T16:48:19.757385000',\n", + " '2026-03-16T16:48:19.758883000', '2026-03-16T16:48:19.760381000'],\n", + " shape=(16689,), dtype='datetime64[ns]') line(azimuth_time)int64dask.array<chunksize=(2048,), meta=np.ndarray>\n", + "
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grd(azimuth_time, ground_range)uint16dask.array<chunksize=(2048, 2048), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'line', 'pixel', 'ground_range'], 'dimensions': ['azimuth_time', 'ground_range'], 'dtype': '<u2', 'long_name': 'measurement data set for GRD IW'}
- dtype :
- <u2
- long_name :
- measurement data set for GRD IW
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<xarray.DatasetView> Size: 0B\n", - "Dimensions: ()\n", + "<xarray.Dataset> Size: 890MB\n", + "Dimensions: (azimuth_time: 16689, ground_range: 26642)\n", + "Coordinates:\n", + " * azimuth_time (azimuth_time) datetime64[ns] 134kB 2026-03-16T16:47:54.761...\n", + " line (azimuth_time) int64 134kB dask.array<chunksize=(2048,), meta=np.ndarray>\n", + " * ground_range (ground_range) float64 213kB 0.0 10.0 ... 2.664e+05 2.664e+05\n", + " pixel (ground_range) int64 213kB dask.array<chunksize=(2048,), meta=np.ndarray>\n", + "Data variables:\n", + " grd (azimuth_time, ground_range) uint16 889MB dask.array<chunksize=(2048, 2048), meta=np.ndarray>xarray.Dataset
- azimuth_time: 16689
- ground_range: 26642
azimuth_time(azimuth_time)datetime64[ns]2026-03-16T16:47:54.761834 ... 2...array(['2026-03-16T16:47:54.761834000', '2026-03-16T16:47:54.763331000',\n", + " '2026-03-16T16:47:54.764829000', ..., '2026-03-16T16:48:19.757385000',\n", + " '2026-03-16T16:48:19.758883000', '2026-03-16T16:48:19.760381000'],\n", + " shape=(16689,), dtype='datetime64[ns]') line(azimuth_time)int64dask.array<chunksize=(2048,), meta=np.ndarray>\n", + "
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grd(azimuth_time, ground_range)uint16dask.array<chunksize=(2048, 2048), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'line', 'pixel', 'ground_range'], 'dimensions': ['azimuth_time', 'ground_range'], 'dtype': '<u2', 'long_name': 'measurement data set for GRD IW'}
- dtype :
- <u2
- long_name :
- measurement data set for GRD IW
\n", + "
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<xarray.DatasetView> Size: 322kB\n", - "Dimensions: (azimuth_time: 27, count: 730)\n", - "Coordinates:\n", - " * azimuth_time (azimuth_time) datetime64[ns] 216B 2026-03-16T16:47:...\n", - " * count (count) int64 6kB 0 1 2 3 4 5 ... 725 726 727 728 729\n", - "Data variables:\n", - " elevation_angle (azimuth_time, count) float32 79kB dask.array<chunksize=(27, 730), meta=np.ndarray>\n", - " incidence_angle (azimuth_time, count) float32 79kB dask.array<chunksize=(27, 730), meta=np.ndarray>\n", - " roll (azimuth_time) float64 216B dask.array<chunksize=(27,), meta=np.ndarray>\n", - " slant_range_time_ap (azimuth_time, count) float64 158kB dask.array<chunksize=(27, 730), meta=np.ndarray>\n", - " swath (azimuth_time) <U3 324B dask.array<chunksize=(27,), meta=np.ndarray>\n", - " terrain_height (azimuth_time) float64 216B dask.array<chunksize=(27,), meta=np.ndarray>
array(['2026-03-16T16:47:55.425896000', '2026-03-16T16:47:56.276897000',\n", + "<xarray.Dataset> Size: 2GB\n", + "Dimensions: (\n", + " VH_conditions_antenna_pattern_azimuth_time: 27,\n", + " VH_conditions_antenna_pattern_count: 730,\n", + " VH_conditions_attitude_azimuth_time: 25,\n", + " VH_conditions_doppler_centroid_azimuth_time: 27,\n", + " VH_conditions_doppler_centroid_degree: 3,\n", + " ...\n", + " VV_quality_calibration_azimuth_time: 27,\n", + " VV_quality_calibration_ground_range: 668,\n", + " VV_quality_azimuth_swath: 3,\n", + " VV_quality_azimuth_azimuth_time: 1688,\n", + " VV_quality_range_azimuth_time: 26,\n", + " VV_quality_range_ground_range: 671)\n", + "Coordinates: (12/58)\n", + " * VH_conditions_antenna_pattern_azimuth_time (VH_conditions_antenna_pattern_azimuth_time) datetime64[ns] 216B ...\n", + " * VH_conditions_antenna_pattern_count (VH_conditions_antenna_pattern_count) int64 6kB ...\n", + " * VH_conditions_attitude_azimuth_time (VH_conditions_attitude_azimuth_time) datetime64[ns] 200B ...\n", + " * VH_conditions_doppler_centroid_azimuth_time (VH_conditions_doppler_centroid_azimuth_time) datetime64[ns] 216B ...\n", + " * VH_conditions_doppler_centroid_degree (VH_conditions_doppler_centroid_degree) int64 24B ...\n", + " * VH_conditions_gcp_azimuth_time (VH_conditions_gcp_azimuth_time) datetime64[ns] 80B ...\n", + " ... ...\n", + " VV_quality_azimuth_last_range_sample (VV_quality_azimuth_swath) int32 12B dask.array<chunksize=(3,), meta=np.ndarray>\n", + " VV_quality_azimuth_line (VV_quality_azimuth_swath, VV_quality_azimuth_azimuth_time) int32 20kB dask.array<chunksize=(3, 1688), meta=np.ndarray>\n", + " * VV_quality_range_azimuth_time (VV_quality_range_azimuth_time) datetime64[ns] 208B ...\n", + " VV_quality_range_line (VV_quality_range_azimuth_time) int32 104B dask.array<chunksize=(26,), meta=np.ndarray>\n", + " * VV_quality_range_ground_range (VV_quality_range_ground_range) float64 5kB ...\n", + " VV_quality_range_pixel (VV_quality_range_ground_range) int32 3kB dask.array<chunksize=(671,), meta=np.ndarray>\n", + "Dimensions without coordinates: VH_quality_azimuth_azimuth_time,\n", + " VV_quality_azimuth_azimuth_time\n", + "Data variables: (12/78)\n", + " VH_conditions_antenna_pattern_elevation_angle (VH_conditions_antenna_pattern_azimuth_time, VH_conditions_antenna_pattern_count) float32 79kB dask.array<chunksize=(27, 730), meta=np.ndarray>\n", + " VH_conditions_antenna_pattern_incidence_angle (VH_conditions_antenna_pattern_azimuth_time, VH_conditions_antenna_pattern_count) float32 79kB dask.array<chunksize=(27, 730), meta=np.ndarray>\n", + " VH_conditions_antenna_pattern_roll (VH_conditions_antenna_pattern_azimuth_time) float64 216B dask.array<chunksize=(27,), meta=np.ndarray>\n", + " VH_conditions_antenna_pattern_slant_range_time_ap (VH_conditions_antenna_pattern_azimuth_time, VH_conditions_antenna_pattern_count) float64 158kB dask.array<chunksize=(27, 730), meta=np.ndarray>\n", + " VH_conditions_antenna_pattern_swath (VH_conditions_antenna_pattern_azimuth_time) <U3 324B dask.array<chunksize=(27,), meta=np.ndarray>\n", + " VH_conditions_antenna_pattern_terrain_height (VH_conditions_antenna_pattern_azimuth_time) float64 216B dask.array<chunksize=(27,), meta=np.ndarray>\n", + " ... ...\n", + " VV_quality_calibration_beta_nought (VV_quality_calibration_azimuth_time, VV_quality_calibration_ground_range) float32 72kB dask.array<chunksize=(27, 668), meta=np.ndarray>\n", + " VV_quality_calibration_dn (VV_quality_calibration_azimuth_time, VV_quality_calibration_ground_range) float32 72kB dask.array<chunksize=(27, 668), meta=np.ndarray>\n", + " VV_quality_calibration_gamma (VV_quality_calibration_azimuth_time, VV_quality_calibration_ground_range) float32 72kB dask.array<chunksize=(27, 668), meta=np.ndarray>\n", + " VV_quality_calibration_sigma_nought (VV_quality_calibration_azimuth_time, VV_quality_calibration_ground_range) float32 72kB dask.array<chunksize=(27, 668), meta=np.ndarray>\n", + " VV_quality_azimuth_noise_azimuth_lut (VV_quality_azimuth_swath, VV_quality_azimuth_azimuth_time) float32 20kB dask.array<chunksize=(3, 1688), meta=np.ndarray>\n", + " VV_quality_range_noise_range_lut (VV_quality_range_azimuth_time, VV_quality_range_ground_range) float32 70kB dask.array<chunksize=(26, 671), meta=np.ndarray>\n", + "Attributes: (2)xarray.Dataset
- VH_conditions_antenna_pattern_azimuth_time: 27
- VH_conditions_antenna_pattern_count: 730
- VH_conditions_attitude_azimuth_time: 25
- VH_conditions_doppler_centroid_azimuth_time: 27
- VH_conditions_doppler_centroid_degree: 3
- VH_conditions_gcp_azimuth_time: 10
- VH_conditions_gcp_ground_range: 21
- VH_conditions_orbit_azimuth_time: 17
- VH_conditions_orbit_axis: 3
- VH_measurements_azimuth_time: 16689
- VH_measurements_ground_range: 26642
- VH_quality_calibration_azimuth_time: 27
- VH_quality_calibration_ground_range: 668
- VH_quality_azimuth_swath: 3
- VH_quality_azimuth_azimuth_time: 1688
- VH_quality_range_azimuth_time: 26
- VH_quality_range_ground_range: 671
- VV_conditions_antenna_pattern_azimuth_time: 27
- VV_conditions_antenna_pattern_count: 730
- VV_conditions_attitude_azimuth_time: 25
- VV_conditions_doppler_centroid_azimuth_time: 27
- VV_conditions_doppler_centroid_degree: 3
- VV_conditions_gcp_azimuth_time: 10
- VV_conditions_gcp_ground_range: 21
- VV_conditions_orbit_azimuth_time: 17
- VV_conditions_orbit_axis: 3
- VV_measurements_azimuth_time: 16689
- VV_measurements_ground_range: 26642
- VV_quality_calibration_azimuth_time: 27
- VV_quality_calibration_ground_range: 668
- VV_quality_azimuth_swath: 3
- VV_quality_azimuth_azimuth_time: 1688
- VV_quality_range_azimuth_time: 26
- VV_quality_range_ground_range: 671
VH_conditions_antenna_pattern_azimuth_time(VH_conditions_antenna_pattern_azimuth_time)datetime64[ns]2026-03-16T16:47:55.425896 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- zero doppler azimuth time of antenna pattern measurement
array(['2026-03-16T16:47:55.425896000', '2026-03-16T16:47:56.276897000',\n", " '2026-03-16T16:47:57.222452000', '2026-03-16T16:47:58.182397000',\n", " '2026-03-16T16:47:59.031342000', '2026-03-16T16:47:59.983064000',\n", " '2026-03-16T16:48:00.938898000', '2026-03-16T16:48:01.791954000',\n", @@ -4228,7 +5690,37 @@ " '2026-03-16T16:48:13.765569000', '2026-03-16T16:48:14.725514000',\n", " '2026-03-16T16:48:15.578570000', '2026-03-16T16:48:16.526181000',\n", " '2026-03-16T16:48:17.488182000', '2026-03-16T16:48:18.337127000',\n", - " '2026-03-16T16:48:19.280627000'], dtype='datetime64[ns]') count(count)int640 1 2 3 4 5 ... 725 726 727 728 729array([ 0, 1, 2, ..., 727, 728, 729], shape=(730,))
elevation_angle(azimuth_time, count)float32dask.array<chunksize=(27, 730), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'count'], 'dimensions': ['azimuth_time', 'count'], 'dtype': '<f4', 'long_name': 'elevation angle to grid point', 'units': 'degrees'}
- dtype :
- <f4
- long_name :
- elevation angle to grid point
- units :
- degrees
\n", + " '2026-03-16T16:48:19.280627000'], dtype='datetime64[ns]')
VH_conditions_antenna_pattern_count(VH_conditions_antenna_pattern_count)int640 1 2 3 4 5 ... 725 726 727 728 729array([ 0, 1, 2, ..., 727, 728, 729], shape=(730,)) VH_conditions_attitude_azimuth_time(VH_conditions_attitude_azimuth_time)datetime64[ns]2026-03-16T16:47:55.000002 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- time stamp at which orbit state vectors apply
array(['2026-03-16T16:47:55.000002000', '2026-03-16T16:47:55.999998000',\n", + " '2026-03-16T16:47:57.000002000', '2026-03-16T16:47:57.999996000',\n", + " '2026-03-16T16:47:59.000000000', '2026-03-16T16:47:59.999995000',\n", + " '2026-03-16T16:48:01.000000000', '2026-03-16T16:48:01.999995000',\n", + " '2026-03-16T16:48:03.000000000', '2026-03-16T16:48:04.000003000',\n", + " '2026-03-16T16:48:04.999998000', '2026-03-16T16:48:06.000003000',\n", + " '2026-03-16T16:48:06.999997000', '2026-03-16T16:48:08.000002000',\n", + " '2026-03-16T16:48:08.999996000', '2026-03-16T16:48:10.000001000',\n", + " '2026-03-16T16:48:10.999996000', '2026-03-16T16:48:12.000000000',\n", + " '2026-03-16T16:48:12.999995000', '2026-03-16T16:48:14.000000000',\n", + " '2026-03-16T16:48:14.999994000', '2026-03-16T16:48:16.000000000',\n", + " '2026-03-16T16:48:17.000004000', '2026-03-16T16:48:17.999998000',\n", + " '2026-03-16T16:48:19.000004000'], dtype='datetime64[ns]') VH_conditions_doppler_centroid_azimuth_time(VH_conditions_doppler_centroid_azimuth_time)datetime64[ns]2026-03-16T16:47:56.021426 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- zero doppler azimuth time of terrain height measurement
array(['2026-03-16T16:47:56.021426000', '2026-03-16T16:47:56.022979000',\n", + " '2026-03-16T16:47:56.035054000', '2026-03-16T16:47:58.779703000',\n", + " '2026-03-16T16:47:58.781256000', '2026-03-16T16:47:58.793331000',\n", + " '2026-03-16T16:48:01.537980000', '2026-03-16T16:48:01.539533000',\n", + " '2026-03-16T16:48:01.551608000', '2026-03-16T16:48:04.296257000',\n", + " '2026-03-16T16:48:04.297810000', '2026-03-16T16:48:04.309885000',\n", + " '2026-03-16T16:48:07.054533000', '2026-03-16T16:48:07.056086000',\n", + " '2026-03-16T16:48:07.068161000', '2026-03-16T16:48:09.812810000',\n", + " '2026-03-16T16:48:09.814363000', '2026-03-16T16:48:09.826438000',\n", + " '2026-03-16T16:48:12.571087000', '2026-03-16T16:48:12.572640000',\n", + " '2026-03-16T16:48:12.584715000', '2026-03-16T16:48:15.329364000',\n", + " '2026-03-16T16:48:15.330917000', '2026-03-16T16:48:15.342992000',\n", + " '2026-03-16T16:48:18.087641000', '2026-03-16T16:48:18.089194000',\n", + " '2026-03-16T16:48:18.101269000'], dtype='datetime64[ns]') VH_conditions_doppler_centroid_degree(VH_conditions_doppler_centroid_degree)int642 1 0array([2, 1, 0]) VH_conditions_gcp_azimuth_time(VH_conditions_gcp_azimuth_time)datetime64[ns]2026-03-16T16:47:54.761834 ... 2...array(['2026-03-16T16:47:54.761834000', '2026-03-16T16:47:57.762318000',\n", + " '2026-03-16T16:48:00.762803000', '2026-03-16T16:48:03.763288000',\n", + " '2026-03-16T16:48:06.763773000', '2026-03-16T16:48:09.764257000',\n", + " '2026-03-16T16:48:12.764742000', '2026-03-16T16:48:15.765227000',\n", + " '2026-03-16T16:48:18.765712000', '2026-03-16T16:48:19.760381000'],\n", + " dtype='datetime64[ns]') VH_conditions_gcp_line(VH_conditions_gcp_azimuth_time)int32dask.array<chunksize=(10,), meta=np.ndarray>\n", "
\n", " \n", - "\n", " \n", "\n", @@ -4243,14 +5735,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "76.99 kiB \n", - "76.99 kiB \n", + "40 B \n", + "40 B \n", "\n", " \n", "Shape \n", - "(27, 730) \n", - "(27, 730) \n", + "(10,) \n", + "(10,) \n", "\n", " \n", "Dask graph \n", @@ -4258,32 +5750,34 @@ "\n", " \n", " \n", "Data type \n", - "float32 numpy.ndarray \n", + "int32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 730 \n", - "27 \n", + "10 \n", + "1 \n", " incidence_angle(azimuth_time, count)float32dask.array<chunksize=(27, 730), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'count'], 'dimensions': ['azimuth_time', 'count'], 'dtype': '<f4', 'long_name': 'incidence angle to grid point', 'units': 'degrees'}
- dtype :
- <f4
- long_name :
- incidence angle to grid point
- units :
- degrees
\n", + "
VH_conditions_gcp_ground_range(VH_conditions_gcp_ground_range)float640.0 1.333e+04 ... 2.664e+05array([ 0., 13330., 26660., 39990., 53320., 66650., 79980., 93310.,\n", + " 106640., 119970., 133300., 146630., 159960., 173290., 186620., 199950.,\n", + " 213280., 226610., 239940., 253270., 266410.]) VH_conditions_gcp_pixel(VH_conditions_gcp_ground_range)int32dask.array<chunksize=(21,), meta=np.ndarray>\n", "
\n", " \n", - "\n", " \n", "\n", @@ -4298,14 +5792,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "76.99 kiB \n", - "76.99 kiB \n", + "84 B \n", + "84 B \n", "\n", " \n", "Shape \n", - "(27, 730) \n", - "(27, 730) \n", + "(21,) \n", + "(21,) \n", "\n", " \n", "Dask graph \n", @@ -4313,32 +5807,43 @@ "\n", " \n", " \n", "Data type \n", - "float32 numpy.ndarray \n", + "int32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 730 \n", - "27 \n", + "21 \n", + "1 \n", " roll(azimuth_time)float64dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'estimated roll angle for this antenna pattern', 'units': 'degrees'}
- dtype :
- <f8
- long_name :
- estimated roll angle for this antenna pattern
- units :
- degrees
\n", + "
VH_conditions_orbit_azimuth_time(VH_conditions_orbit_azimuth_time)datetime64[ns]2026-03-16T16:46:46.681692 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- time stamp at which orbit state vectors apply
array(['2026-03-16T16:46:46.681692000', '2026-03-16T16:46:56.681692000',\n", + " '2026-03-16T16:47:06.681692000', '2026-03-16T16:47:16.681692000',\n", + " '2026-03-16T16:47:26.681692000', '2026-03-16T16:47:36.681693000',\n", + " '2026-03-16T16:47:46.681693000', '2026-03-16T16:47:56.681692000',\n", + " '2026-03-16T16:48:06.681692000', '2026-03-16T16:48:16.681692000',\n", + " '2026-03-16T16:48:26.681692000', '2026-03-16T16:48:36.681692000',\n", + " '2026-03-16T16:48:46.681692000', '2026-03-16T16:48:56.681693000',\n", + " '2026-03-16T16:49:06.681693000', '2026-03-16T16:49:16.681692000',\n", + " '2026-03-16T16:49:26.681692000'], dtype='datetime64[ns]') VH_conditions_orbit_axis(VH_conditions_orbit_axis)<U1'x' 'y' 'z'array(['x', 'y', 'z'], dtype='<U1') VH_measurements_azimuth_time(VH_measurements_azimuth_time)datetime64[ns]2026-03-16T16:47:54.761834 ... 2...array(['2026-03-16T16:47:54.761834000', '2026-03-16T16:47:54.763331000',\n", + " '2026-03-16T16:47:54.764829000', ..., '2026-03-16T16:48:19.757385000',\n", + " '2026-03-16T16:48:19.758883000', '2026-03-16T16:48:19.760381000'],\n", + " shape=(16689,), dtype='datetime64[ns]') VH_measurements_line(VH_measurements_azimuth_time)int64dask.array<chunksize=(2048,), meta=np.ndarray>\n", "
\n", " \n", - "\n", " \n", "\n", @@ -4353,47 +5858,56 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "216 B \n", - "216 B \n", + "130.38 kiB \n", + "16.00 kiB \n", "\n", " \n", "Shape \n", - "(27,) \n", - "(27,) \n", + "(16689,) \n", + "(2048,) \n", "\n", " \n", "Dask graph \n", - "1 chunks in 2 graph layers \n", + "9 chunks in 2 graph layers \n", "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "int64 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 27 \n", - "1 \n", + "16689 \n", + "1 \n", " slant_range_time_ap(azimuth_time, count)float64dask.array<chunksize=(27, 730), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'count'], 'dimensions': ['azimuth_time', 'count'], 'dtype': '<f8', 'long_name': 'two-way slant range time to sample', 'units': 's'}
- dtype :
- <f8
- long_name :
- two-way slant range time to sample
- units :
- s
\n", + "
VH_measurements_ground_range(VH_measurements_ground_range)float640.0 10.0 ... 2.664e+05 2.664e+05array([0.0000e+00, 1.0000e+01, 2.0000e+01, ..., 2.6639e+05, 2.6640e+05,\n", + " 2.6641e+05], shape=(26642,)) VH_measurements_pixel(VH_measurements_ground_range)int64dask.array<chunksize=(2048,), meta=np.ndarray>\n", "
\n", " \n", - "\n", " \n", "\n", @@ -4408,47 +5922,73 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "153.98 kiB \n", - "153.98 kiB \n", + "208.14 kiB \n", + "16.00 kiB \n", "\n", " \n", "Shape \n", - "(27, 730) \n", - "(27, 730) \n", + "(26642,) \n", + "(2048,) \n", "\n", " \n", "Dask graph \n", - "1 chunks in 2 graph layers \n", + "14 chunks in 2 graph layers \n", "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "int64 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 730 \n", - "27 \n", + "26642 \n", + "1 \n", " swath(azimuth_time)<U3dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': 'U3', 'long_name': 'Swath'}
- dtype :
- U3
- long_name :
- Swath
\n", + "
VH_quality_calibration_azimuth_time(VH_quality_calibration_azimuth_time)datetime64[ns]2026-03-16T16:47:54.761834 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- zero doppler azimuth time at which calibration vector applies
array(['2026-03-16T16:47:54.761834000', '2026-03-16T16:47:55.761834000',\n", + " '2026-03-16T16:47:56.761834000', '2026-03-16T16:47:57.761834000',\n", + " '2026-03-16T16:47:58.761834000', '2026-03-16T16:47:59.761834000',\n", + " '2026-03-16T16:48:00.761834000', '2026-03-16T16:48:01.761834000',\n", + " '2026-03-16T16:48:02.761834000', '2026-03-16T16:48:03.761834000',\n", + " '2026-03-16T16:48:04.761834000', '2026-03-16T16:48:05.761834000',\n", + " '2026-03-16T16:48:06.761834000', '2026-03-16T16:48:07.761834000',\n", + " '2026-03-16T16:48:08.761834000', '2026-03-16T16:48:09.761834000',\n", + " '2026-03-16T16:48:10.761834000', '2026-03-16T16:48:11.761834000',\n", + " '2026-03-16T16:48:12.761834000', '2026-03-16T16:48:13.761834000',\n", + " '2026-03-16T16:48:14.761834000', '2026-03-16T16:48:15.761834000',\n", + " '2026-03-16T16:48:16.761834000', '2026-03-16T16:48:17.761834000',\n", + " '2026-03-16T16:48:18.761834000', '2026-03-16T16:48:19.761834000',\n", + " '2026-03-16T16:48:20.761834000'], dtype='datetime64[ns]') VH_quality_calibration_line(VH_quality_calibration_azimuth_time)int32dask.array<chunksize=(27,), meta=np.ndarray>
- dimensions :
- ['azimuth_time']
- dtype :
- <i4
- long_name :
- image line at which the calibration vector applies
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -4463,8 +6003,8 @@ " \n", "
\n", @@ -4498,12 +6038,12 @@ "\n", " \n", " \n", "Bytes \n", - "324 B \n", - "324 B \n", + "108 B \n", + "108 B \n", "\n", @@ -4478,7 +6018,7 @@ " \n", "\n", " \n", " \n", "Data type \n", - "\n", + " int32 numpy.ndarray \n", "\n", "\n", " \n", - " 27 \n", - "1 \n", + "27 \n", + "1 \n", "\n", " terrain_height(azimuth_time)float64dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'mean terrain height in range for this antenna pattern (in metres above the ellipsoid) for the given zero-doppler azimuth time', 'units': 'm'}
- dtype :
- <f8
- long_name :
- mean terrain height in range for this antenna pattern (in metres above the ellipsoid) for the given zero-doppler azimuth time
- units :
- m
\n", + "
VH_quality_calibration_ground_range(VH_quality_calibration_ground_range)float640.0 400.0 ... 2.664e+05 2.664e+05array([ 0., 400., 800., ..., 266000., 266400., 266410.], shape=(668,)) VH_quality_calibration_pixel(VH_quality_calibration_ground_range)int32dask.array<chunksize=(668,), meta=np.ndarray>\n", "
\n", " \n", - "\n", " \n", "\n", @@ -4518,14 +6058,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "216 B \n", - "216 B \n", + "2.61 kiB \n", + "2.61 kiB \n", "\n", " \n", "Shape \n", - "(27,) \n", - "(27,) \n", + "(668,) \n", + "(668,) \n", "\n", " \n", "Dask graph \n", @@ -4533,501 +6073,32 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "int32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 27 \n", - "1 \n", + "668 \n", + "1 \n", "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - " \n", - " \n", - " \n", - "\n", - " \n", - " \n", - " \n", - " <xarray.DatasetView> Size: 2kB\n", - "Dimensions: (azimuth_time: 25)\n", - "Coordinates:\n", - " * azimuth_time (azimuth_time) datetime64[ns] 200B 2026-03-16T16:47:55.0000...\n", - "Data variables:\n", - " pitch (azimuth_time) float64 200B dask.array<chunksize=(25,), meta=np.ndarray>\n", - " q0 (azimuth_time) float32 100B dask.array<chunksize=(25,), meta=np.ndarray>\n", - " q1 (azimuth_time) float32 100B dask.array<chunksize=(25,), meta=np.ndarray>\n", - " q2 (azimuth_time) float32 100B dask.array<chunksize=(25,), meta=np.ndarray>\n", - " q3 (azimuth_time) float32 100B dask.array<chunksize=(25,), meta=np.ndarray>\n", - " roll (azimuth_time) float64 200B dask.array<chunksize=(25,), meta=np.ndarray>\n", - " wx (azimuth_time) float64 200B dask.array<chunksize=(25,), meta=np.ndarray>\n", - " wy (azimuth_time) float64 200B dask.array<chunksize=(25,), meta=np.ndarray>\n", - " wz (azimuth_time) float64 200B dask.array<chunksize=(25,), meta=np.ndarray>\n", - " yaw (azimuth_time) float64 200B dask.array<chunksize=(25,), meta=np.ndarray>attitude
- azimuth_time: 25
azimuth_time(azimuth_time)datetime64[ns]2026-03-16T16:47:55.000002 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- time stamp at which orbit state vectors apply
array(['2026-03-16T16:47:55.000002000', '2026-03-16T16:47:55.999998000',\n", - " '2026-03-16T16:47:57.000002000', '2026-03-16T16:47:57.999996000',\n", - " '2026-03-16T16:47:59.000000000', '2026-03-16T16:47:59.999995000',\n", - " '2026-03-16T16:48:01.000000000', '2026-03-16T16:48:01.999995000',\n", - " '2026-03-16T16:48:03.000000000', '2026-03-16T16:48:04.000003000',\n", - " '2026-03-16T16:48:04.999998000', '2026-03-16T16:48:06.000003000',\n", - " '2026-03-16T16:48:06.999997000', '2026-03-16T16:48:08.000002000',\n", - " '2026-03-16T16:48:08.999996000', '2026-03-16T16:48:10.000001000',\n", - " '2026-03-16T16:48:10.999996000', '2026-03-16T16:48:12.000000000',\n", - " '2026-03-16T16:48:12.999995000', '2026-03-16T16:48:14.000000000',\n", - " '2026-03-16T16:48:14.999994000', '2026-03-16T16:48:16.000000000',\n", - " '2026-03-16T16:48:17.000004000', '2026-03-16T16:48:17.999998000',\n", - " '2026-03-16T16:48:19.000004000'], dtype='datetime64[ns]')
pitch(azimuth_time)float64dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'platform pitch angle calculated from ancillary attitude data', 'units': 'degrees'}
- dtype :
- <f8
- long_name :
- platform pitch angle calculated from ancillary attitude data
- units :
- degrees
\n", + "
VH_quality_azimuth_swath(VH_quality_azimuth_swath)<U3'IW1' 'IW2' 'IW3'
- dimensions :
- ['swath']
- dtype :
- U3
- long_name :
- Swath
array(['IW1', 'IW2', 'IW3'], dtype='<U3') VH_quality_azimuth_first_azimuth_time(VH_quality_azimuth_swath)int32dask.array<chunksize=(3,), meta=np.ndarray>
- dtype :
- <i4
- long_name :
- first azimuth line azimuth thermal noise correction
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -5042,14 +6113,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "200 B \n", - "200 B \n", + "12 B \n", + "12 B \n", "\n", " \n", "Shape \n", - "(25,) \n", - "(25,) \n", + "(3,) \n", + "(3,) \n", "\n", " \n", "Dask graph \n", @@ -5057,32 +6128,32 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "int32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 25 \n", - "1 \n", + "3 \n", + "1 \n", " q0(azimuth_time)float32dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f4', 'long_name': 'q0 attitude quaternion as extracted from ancillary attitude data'}
- dtype :
- <f4
- long_name :
- q0 attitude quaternion as extracted from ancillary attitude data
\n", + "
VH_quality_azimuth_first_range_sample(VH_quality_azimuth_swath)int32dask.array<chunksize=(3,), meta=np.ndarray>
- dtype :
- <i4
- long_name :
- first range sample azimuth thermal noise correction
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -5097,14 +6168,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "100 B \n", - "100 B \n", + "12 B \n", + "12 B \n", "\n", " \n", "Shape \n", - "(25,) \n", - "(25,) \n", + "(3,) \n", + "(3,) \n", "\n", " \n", "Dask graph \n", @@ -5112,32 +6183,32 @@ "\n", " \n", " \n", "Data type \n", - "float32 numpy.ndarray \n", + "int32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 25 \n", - "1 \n", + "3 \n", + "1 \n", " q1(azimuth_time)float32dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f4', 'long_name': 'q1 attitude quaternion as extracted from ancillary attitude data'}
- dtype :
- <f4
- long_name :
- q1 attitude quaternion as extracted from ancillary attitude data
\n", + "
VH_quality_azimuth_last_azimuth_time(VH_quality_azimuth_swath)int32dask.array<chunksize=(3,), meta=np.ndarray>
- dtype :
- <i4
- long_name :
- last azimuth line azimuth thermal noise correction
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -5152,14 +6223,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "100 B \n", - "100 B \n", + "12 B \n", + "12 B \n", "\n", " \n", "Shape \n", - "(25,) \n", - "(25,) \n", + "(3,) \n", + "(3,) \n", "\n", " \n", "Dask graph \n", @@ -5167,32 +6238,32 @@ "\n", " \n", " \n", "Data type \n", - "float32 numpy.ndarray \n", + "int32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 25 \n", - "1 \n", + "3 \n", + "1 \n", " q2(azimuth_time)float32dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f4', 'long_name': 'q2 attitude quaternion as extracted from ancillary attitude data'}
- dtype :
- <f4
- long_name :
- q2 attitude quaternion as extracted from ancillary attitude data
\n", + "
VH_quality_azimuth_last_range_sample(VH_quality_azimuth_swath)int32dask.array<chunksize=(3,), meta=np.ndarray>
- dtype :
- <i4
- long_name :
- last range sample azimuth thermal noise correction
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -5207,14 +6278,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "100 B \n", - "100 B \n", + "12 B \n", + "12 B \n", "\n", " \n", "Shape \n", - "(25,) \n", - "(25,) \n", + "(3,) \n", + "(3,) \n", "\n", " \n", "Dask graph \n", @@ -5222,32 +6293,32 @@ "\n", " \n", " \n", "Data type \n", - "float32 numpy.ndarray \n", + "int32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 25 \n", - "1 \n", + "3 \n", + "1 \n", " q3(azimuth_time)float32dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f4', 'long_name': 'q3 attitude quaternion as extracted from ancillary attitude data'}
- dtype :
- <f4
- long_name :
- q3 attitude quaternion as extracted from ancillary attitude data
\n", + "
VH_quality_azimuth_line(VH_quality_azimuth_swath, VH_quality_azimuth_azimuth_time)int32dask.array<chunksize=(3, 1688), meta=np.ndarray>
- dimensions :
- ['swath', 'azimuth_time']
- dtype :
- <i4
- long_name :
- line
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -5262,14 +6333,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "100 B \n", - "100 B \n", + "19.78 kiB \n", + "19.78 kiB \n", "\n", " \n", "Shape \n", - "(25,) \n", - "(25,) \n", + "(3, 1688) \n", + "(3, 1688) \n", "\n", " \n", "Dask graph \n", @@ -5277,32 +6348,45 @@ "\n", " \n", " \n", "Data type \n", - "float32 numpy.ndarray \n", + "int32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 25 \n", - "1 \n", + "1688 \n", + "3 \n", " roll(azimuth_time)float64dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'platform roll angle calculated from ancillary attitude data', 'units': 'degrees'}
- dtype :
- <f8
- long_name :
- platform roll angle calculated from ancillary attitude data
- units :
- degrees
\n", + "
VH_quality_range_azimuth_time(VH_quality_range_azimuth_time)datetime64[ns]2026-03-16T16:47:54.761834 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- zero doppler azimuth time at which noise vector applies
array(['2026-03-16T16:47:54.761834000', '2026-03-16T16:47:55.762495000',\n", + " '2026-03-16T16:47:56.763156000', '2026-03-16T16:47:57.763817000',\n", + " '2026-03-16T16:47:58.764478000', '2026-03-16T16:47:59.765139000',\n", + " '2026-03-16T16:48:00.765800000', '2026-03-16T16:48:01.766461000',\n", + " '2026-03-16T16:48:02.767122000', '2026-03-16T16:48:03.767783000',\n", + " '2026-03-16T16:48:04.768444000', '2026-03-16T16:48:05.769104000',\n", + " '2026-03-16T16:48:06.769765000', '2026-03-16T16:48:07.770426000',\n", + " '2026-03-16T16:48:08.771087000', '2026-03-16T16:48:09.771748000',\n", + " '2026-03-16T16:48:10.772409000', '2026-03-16T16:48:11.773070000',\n", + " '2026-03-16T16:48:12.773731000', '2026-03-16T16:48:13.774392000',\n", + " '2026-03-16T16:48:14.775053000', '2026-03-16T16:48:15.775714000',\n", + " '2026-03-16T16:48:16.776375000', '2026-03-16T16:48:17.777036000',\n", + " '2026-03-16T16:48:18.777697000', '2026-03-16T16:48:19.760382000'],\n", + " dtype='datetime64[ns]') VH_quality_range_line(VH_quality_range_azimuth_time)int32dask.array<chunksize=(26,), meta=np.ndarray>
- dimensions :
- ['azimuth_time']
- dtype :
- <i4
- long_name :
- line
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -5317,14 +6401,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "200 B \n", - "200 B \n", + "104 B \n", + "104 B \n", "\n", " \n", "Shape \n", - "(25,) \n", - "(25,) \n", + "(26,) \n", + "(26,) \n", "\n", " \n", "Dask graph \n", @@ -5332,32 +6416,32 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "int32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 25 \n", - "1 \n", + "26 \n", + "1 \n", " wx(azimuth_time)float64dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'x component of angular velocity vector as extracted from ancillary attitude data', 'units': 'degrees/s'}
- dtype :
- <f8
- long_name :
- x component of angular velocity vector as extracted from ancillary attitude data
- units :
- degrees/s
\n", + "
VH_quality_range_ground_range(VH_quality_range_ground_range)float640.0 400.0 ... 2.664e+05 2.664e+05array([ 0., 400., 800., ..., 265980., 266380., 266410.], shape=(671,)) VH_quality_range_pixel(VH_quality_range_ground_range)int32dask.array<chunksize=(671,), meta=np.ndarray>\n", "
\n", " \n", - "\n", " \n", "\n", @@ -5372,14 +6456,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "200 B \n", - "200 B \n", + "2.62 kiB \n", + "2.62 kiB \n", "\n", " \n", "Shape \n", - "(25,) \n", - "(25,) \n", + "(671,) \n", + "(671,) \n", "\n", " \n", "Dask graph \n", @@ -5387,32 +6471,75 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "int32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 25 \n", - "1 \n", + "671 \n", + "1 \n", " wy(azimuth_time)float64dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'y component of angular velocity vector as extracted from ancillary attitude data', 'units': 'degrees/s'}
- dtype :
- <f8
- long_name :
- y component of angular velocity vector as extracted from ancillary attitude data
- units :
- degrees/s
\n", + "
VV_conditions_antenna_pattern_azimuth_time(VV_conditions_antenna_pattern_azimuth_time)datetime64[ns]2026-03-16T16:47:55.425896 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- zero doppler azimuth time of antenna pattern measurement
array(['2026-03-16T16:47:55.425896000', '2026-03-16T16:47:56.276897000',\n", + " '2026-03-16T16:47:57.222452000', '2026-03-16T16:47:58.182397000',\n", + " '2026-03-16T16:47:59.031342000', '2026-03-16T16:47:59.983064000',\n", + " '2026-03-16T16:48:00.938898000', '2026-03-16T16:48:01.791954000',\n", + " '2026-03-16T16:48:02.741621000', '2026-03-16T16:48:03.695399000',\n", + " '2026-03-16T16:48:04.548455000', '2026-03-16T16:48:05.500177000',\n", + " '2026-03-16T16:48:06.453956000', '2026-03-16T16:48:07.307012000',\n", + " '2026-03-16T16:48:08.256678000', '2026-03-16T16:48:09.216623000',\n", + " '2026-03-16T16:48:10.063513000', '2026-03-16T16:48:11.011124000',\n", + " '2026-03-16T16:48:11.966958000', '2026-03-16T16:48:12.822069000',\n", + " '2026-03-16T16:48:13.765569000', '2026-03-16T16:48:14.725514000',\n", + " '2026-03-16T16:48:15.578570000', '2026-03-16T16:48:16.526181000',\n", + " '2026-03-16T16:48:17.488182000', '2026-03-16T16:48:18.337127000',\n", + " '2026-03-16T16:48:19.280627000'], dtype='datetime64[ns]') VV_conditions_antenna_pattern_count(VV_conditions_antenna_pattern_count)int640 1 2 3 4 5 ... 725 726 727 728 729array([ 0, 1, 2, ..., 727, 728, 729], shape=(730,)) VV_conditions_attitude_azimuth_time(VV_conditions_attitude_azimuth_time)datetime64[ns]2026-03-16T16:47:55.000002 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- time stamp at which orbit state vectors apply
array(['2026-03-16T16:47:55.000002000', '2026-03-16T16:47:55.999998000',\n", + " '2026-03-16T16:47:57.000002000', '2026-03-16T16:47:57.999996000',\n", + " '2026-03-16T16:47:59.000000000', '2026-03-16T16:47:59.999995000',\n", + " '2026-03-16T16:48:01.000000000', '2026-03-16T16:48:01.999995000',\n", + " '2026-03-16T16:48:03.000000000', '2026-03-16T16:48:04.000003000',\n", + " '2026-03-16T16:48:04.999998000', '2026-03-16T16:48:06.000003000',\n", + " '2026-03-16T16:48:06.999997000', '2026-03-16T16:48:08.000002000',\n", + " '2026-03-16T16:48:08.999996000', '2026-03-16T16:48:10.000001000',\n", + " '2026-03-16T16:48:10.999996000', '2026-03-16T16:48:12.000000000',\n", + " '2026-03-16T16:48:12.999995000', '2026-03-16T16:48:14.000000000',\n", + " '2026-03-16T16:48:14.999994000', '2026-03-16T16:48:16.000000000',\n", + " '2026-03-16T16:48:17.000004000', '2026-03-16T16:48:17.999998000',\n", + " '2026-03-16T16:48:19.000004000'], dtype='datetime64[ns]') VV_conditions_doppler_centroid_azimuth_time(VV_conditions_doppler_centroid_azimuth_time)datetime64[ns]2026-03-16T16:47:56.021426 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- zero doppler azimuth time of terrain height measurement
array(['2026-03-16T16:47:56.021426000', '2026-03-16T16:47:56.022979000',\n", + " '2026-03-16T16:47:56.035054000', '2026-03-16T16:47:58.779703000',\n", + " '2026-03-16T16:47:58.781256000', '2026-03-16T16:47:58.793331000',\n", + " '2026-03-16T16:48:01.537980000', '2026-03-16T16:48:01.539533000',\n", + " '2026-03-16T16:48:01.551608000', '2026-03-16T16:48:04.296257000',\n", + " '2026-03-16T16:48:04.297810000', '2026-03-16T16:48:04.309885000',\n", + " '2026-03-16T16:48:07.054533000', '2026-03-16T16:48:07.056086000',\n", + " '2026-03-16T16:48:07.068161000', '2026-03-16T16:48:09.812810000',\n", + " '2026-03-16T16:48:09.814363000', '2026-03-16T16:48:09.826438000',\n", + " '2026-03-16T16:48:12.571087000', '2026-03-16T16:48:12.572640000',\n", + " '2026-03-16T16:48:12.584715000', '2026-03-16T16:48:15.329364000',\n", + " '2026-03-16T16:48:15.330917000', '2026-03-16T16:48:15.342992000',\n", + " '2026-03-16T16:48:18.087641000', '2026-03-16T16:48:18.089194000',\n", + " '2026-03-16T16:48:18.101269000'], dtype='datetime64[ns]') VV_conditions_doppler_centroid_degree(VV_conditions_doppler_centroid_degree)int642 1 0array([2, 1, 0]) VV_conditions_gcp_azimuth_time(VV_conditions_gcp_azimuth_time)datetime64[ns]2026-03-16T16:47:54.761834 ... 2...array(['2026-03-16T16:47:54.761834000', '2026-03-16T16:47:57.762318000',\n", + " '2026-03-16T16:48:00.762803000', '2026-03-16T16:48:03.763288000',\n", + " '2026-03-16T16:48:06.763773000', '2026-03-16T16:48:09.764257000',\n", + " '2026-03-16T16:48:12.764742000', '2026-03-16T16:48:15.765227000',\n", + " '2026-03-16T16:48:18.765712000', '2026-03-16T16:48:19.760381000'],\n", + " dtype='datetime64[ns]') VV_conditions_gcp_line(VV_conditions_gcp_azimuth_time)int32dask.array<chunksize=(10,), meta=np.ndarray>\n", "
\n", " \n", - "\n", " \n", "\n", @@ -5427,14 +6554,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "200 B \n", - "200 B \n", + "40 B \n", + "40 B \n", "\n", " \n", "Shape \n", - "(25,) \n", - "(25,) \n", + "(10,) \n", + "(10,) \n", "\n", " \n", "Dask graph \n", @@ -5442,32 +6569,34 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "int32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 25 \n", - "1 \n", + "10 \n", + "1 \n", " wz(azimuth_time)float64dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'z component of angular velocity vector as extracted from ancillary attitude data', 'units': 'degrees/s'}
- dtype :
- <f8
- long_name :
- z component of angular velocity vector as extracted from ancillary attitude data
- units :
- degrees/s
\n", + "
VV_conditions_gcp_ground_range(VV_conditions_gcp_ground_range)float640.0 1.333e+04 ... 2.664e+05array([ 0., 13330., 26660., 39990., 53320., 66650., 79980., 93310.,\n", + " 106640., 119970., 133300., 146630., 159960., 173290., 186620., 199950.,\n", + " 213280., 226610., 239940., 253270., 266410.]) VV_conditions_gcp_pixel(VV_conditions_gcp_ground_range)int32dask.array<chunksize=(21,), meta=np.ndarray>\n", "
\n", " \n", - "\n", " \n", "\n", @@ -5482,14 +6611,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "200 B \n", - "200 B \n", + "84 B \n", + "84 B \n", "\n", " \n", "Shape \n", - "(25,) \n", - "(25,) \n", + "(21,) \n", + "(21,) \n", "\n", " \n", "Dask graph \n", @@ -5497,32 +6626,43 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "int32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 25 \n", - "1 \n", + "21 \n", + "1 \n", " yaw(azimuth_time)float64dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'platform yaw angle calculated from ancillary attitude data', 'units': 'degrees'}
- dtype :
- <f8
- long_name :
- platform yaw angle calculated from ancillary attitude data
- units :
- degrees
\n", + "
VV_conditions_orbit_azimuth_time(VV_conditions_orbit_azimuth_time)datetime64[ns]2026-03-16T16:46:46.681692 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- time stamp at which orbit state vectors apply
array(['2026-03-16T16:46:46.681692000', '2026-03-16T16:46:56.681692000',\n", + " '2026-03-16T16:47:06.681692000', '2026-03-16T16:47:16.681692000',\n", + " '2026-03-16T16:47:26.681692000', '2026-03-16T16:47:36.681693000',\n", + " '2026-03-16T16:47:46.681693000', '2026-03-16T16:47:56.681692000',\n", + " '2026-03-16T16:48:06.681692000', '2026-03-16T16:48:16.681692000',\n", + " '2026-03-16T16:48:26.681692000', '2026-03-16T16:48:36.681692000',\n", + " '2026-03-16T16:48:46.681692000', '2026-03-16T16:48:56.681693000',\n", + " '2026-03-16T16:49:06.681693000', '2026-03-16T16:49:16.681692000',\n", + " '2026-03-16T16:49:26.681692000'], dtype='datetime64[ns]') VV_conditions_orbit_axis(VV_conditions_orbit_axis)<U1'x' 'y' 'z'array(['x', 'y', 'z'], dtype='<U1') VV_measurements_azimuth_time(VV_measurements_azimuth_time)datetime64[ns]2026-03-16T16:47:54.761834 ... 2...array(['2026-03-16T16:47:54.761834000', '2026-03-16T16:47:54.763331000',\n", + " '2026-03-16T16:47:54.764829000', ..., '2026-03-16T16:48:19.757385000',\n", + " '2026-03-16T16:48:19.758883000', '2026-03-16T16:48:19.760381000'],\n", + " shape=(16689,), dtype='datetime64[ns]') VV_measurements_line(VV_measurements_azimuth_time)int64dask.array<chunksize=(2048,), meta=np.ndarray>\n", "
\n", " \n", - "\n", " \n", "\n", @@ -5537,515 +6677,357 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "200 B \n", - "200 B \n", + "130.38 kiB \n", + "16.00 kiB \n", "\n", " \n", "Shape \n", - "(25,) \n", - "(25,) \n", + "(16689,) \n", + "(2048,) \n", "\n", " \n", "Dask graph \n", - "1 chunks in 2 graph layers \n", + "9 chunks in 2 graph layers \n", "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "int64 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 25 \n", - "1 \n", + "16689 \n", + "1 \n", "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - " \n", - " \n", - " \n", - "\n", - " \n", - " \n", - " \n", - " <xarray.DatasetView> Size: 1kB\n", - "Dimensions: (azimuth_time: 27, degree: 3)\n", - "Coordinates:\n", - " * azimuth_time (azimuth_time) datetime64[ns] 216B 202...\n", - " * degree (degree) int64 24B 2 1 0\n", - "Data variables:\n", - " data_dc_polynomial (azimuth_time, degree) float32 324B dask.array<chunksize=(27, 3), meta=np.ndarray>\n", - " data_dc_rms_error (azimuth_time) float64 216B dask.array<chunksize=(27,), meta=np.ndarray>\n", - " data_dc_rms_error_above_threshold (azimuth_time) bool 27B dask.array<chunksize=(27,), meta=np.ndarray>\n", - " fine_dce_azimuth_start_time (azimuth_time) bool 27B dask.array<chunksize=(27,), meta=np.ndarray>\n", - " fine_dce_azimuth_stop_time (azimuth_time) bool 27B dask.array<chunksize=(27,), meta=np.ndarray>\n", - " geometry_dc_polynomial (azimuth_time, degree) float32 324B dask.array<chunksize=(27, 3), meta=np.ndarray>\n", - " t0 (azimuth_time) float64 216B dask.array<chunksize=(27,), meta=np.ndarray>doppler_centroid
- azimuth_time: 27
- degree: 3
azimuth_time(azimuth_time)datetime64[ns]2026-03-16T16:47:56.021426 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- zero doppler azimuth time of terrain height measurement
array(['2026-03-16T16:47:56.021426000', '2026-03-16T16:47:56.022979000',\n", - " '2026-03-16T16:47:56.035054000', '2026-03-16T16:47:58.779703000',\n", - " '2026-03-16T16:47:58.781256000', '2026-03-16T16:47:58.793331000',\n", - " '2026-03-16T16:48:01.537980000', '2026-03-16T16:48:01.539533000',\n", - " '2026-03-16T16:48:01.551608000', '2026-03-16T16:48:04.296257000',\n", - " '2026-03-16T16:48:04.297810000', '2026-03-16T16:48:04.309885000',\n", - " '2026-03-16T16:48:07.054533000', '2026-03-16T16:48:07.056086000',\n", - " '2026-03-16T16:48:07.068161000', '2026-03-16T16:48:09.812810000',\n", - " '2026-03-16T16:48:09.814363000', '2026-03-16T16:48:09.826438000',\n", - " '2026-03-16T16:48:12.571087000', '2026-03-16T16:48:12.572640000',\n", - " '2026-03-16T16:48:12.584715000', '2026-03-16T16:48:15.329364000',\n", - " '2026-03-16T16:48:15.330917000', '2026-03-16T16:48:15.342992000',\n", - " '2026-03-16T16:48:18.087641000', '2026-03-16T16:48:18.089194000',\n", - " '2026-03-16T16:48:18.101269000'], dtype='datetime64[ns]') degree(degree)int642 1 0array([2, 1, 0])
data_dc_polynomial(azimuth_time, degree)float32dask.array<chunksize=(27, 3), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'degree'], 'dimensions': ['azimuth_time', 'degree'], 'dtype': '<f4', 'long_name': 'doppler centroid estimated from data, expressed as polynomial with 5 coefficients: doppler centroid = d0 + d1(tsr-t0) + d2(tsr-t0)^2 + d3(tsr-t0)^3 + d4(tsr-t0)^4, where tsr = 2-way slant range time'}
- dtype :
- <f4
- long_name :
- doppler centroid estimated from data, expressed as polynomial with 5 coefficients: doppler centroid = d0 + d1(tsr-t0) + d2(tsr-t0)^2 + d3(tsr-t0)^3 + d4(tsr-t0)^4, where tsr = 2-way slant range time
\n", + " \n", + "
3 \n", + "1 \n", + "\n", + " \n", + " \n", + " VV_quality_azimuth_last_azimuth_time(VV_quality_azimuth_swath)int32dask.array<chunksize=(3,), meta=np.ndarray>
- dtype :
- <i4
- long_name :
- last azimuth line azimuth thermal noise correction
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -6060,14 +7042,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "324 B \n", - "324 B \n", + "12 B \n", + "12 B \n", "\n", " \n", "Shape \n", - "(27, 3) \n", - "(27, 3) \n", + "(3,) \n", + "(3,) \n", "\n", " \n", "Dask graph \n", @@ -6075,32 +7057,32 @@ "\n", " \n", " \n", "Data type \n", - "float32 numpy.ndarray \n", + "int32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", - " \n", "\n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 3 \n", - "27 \n", + "3 \n", + "1 \n", " data_dc_rms_error(azimuth_time)float64dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'RMS error of the doppler centroid estimate (calculated as the average of the individual RMS residual errors between input fine doppler centroid estimates and the fitted polynomial; if the doppler centroid was not estimated from data, this is set to 0)'}
- dtype :
- <f8
- long_name :
- RMS error of the doppler centroid estimate (calculated as the average of the individual RMS residual errors between input fine doppler centroid estimates and the fitted polynomial; if the doppler centroid was not estimated from data, this is set to 0)
\n", + "
VV_quality_azimuth_last_range_sample(VV_quality_azimuth_swath)int32dask.array<chunksize=(3,), meta=np.ndarray>
- dtype :
- <i4
- long_name :
- last range sample azimuth thermal noise correction
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -6115,14 +7097,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "216 B \n", - "216 B \n", + "12 B \n", + "12 B \n", "\n", " \n", "Shape \n", - "(27,) \n", - "(27,) \n", + "(3,) \n", + "(3,) \n", "\n", " \n", "Dask graph \n", @@ -6130,32 +7112,32 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "int32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 27 \n", - "1 \n", + "3 \n", + "1 \n", " data_dc_rms_error_above_threshold(azimuth_time)booldask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<b1', 'long_name': 'false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold'}
- dtype :
- <b1
- long_name :
- false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold
\n", + "
VV_quality_azimuth_line(VV_quality_azimuth_swath, VV_quality_azimuth_azimuth_time)int32dask.array<chunksize=(3, 1688), meta=np.ndarray>
- dimensions :
- ['swath', 'azimuth_time']
- dtype :
- <i4
- long_name :
- line
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -6170,14 +7152,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "27 B \n", - "27 B \n", + "19.78 kiB \n", + "19.78 kiB \n", "\n", " \n", "Shape \n", - "(27,) \n", - "(27,) \n", + "(3, 1688) \n", + "(3, 1688) \n", "\n", " \n", "Dask graph \n", @@ -6185,32 +7167,45 @@ "\n", " \n", " \n", "Data type \n", - "bool numpy.ndarray \n", + "int32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 27 \n", - "1 \n", + "1688 \n", + "3 \n", " fine_dce_azimuth_start_time(azimuth_time)booldask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<b1', 'long_name': 'false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold'}
- dtype :
- <b1
- long_name :
- false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold
\n", + "
VV_quality_range_azimuth_time(VV_quality_range_azimuth_time)datetime64[ns]2026-03-16T16:47:54.761834 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- zero doppler azimuth time at which noise vector applies
array(['2026-03-16T16:47:54.761834000', '2026-03-16T16:47:55.762495000',\n", + " '2026-03-16T16:47:56.763156000', '2026-03-16T16:47:57.763817000',\n", + " '2026-03-16T16:47:58.764478000', '2026-03-16T16:47:59.765139000',\n", + " '2026-03-16T16:48:00.765800000', '2026-03-16T16:48:01.766461000',\n", + " '2026-03-16T16:48:02.767122000', '2026-03-16T16:48:03.767783000',\n", + " '2026-03-16T16:48:04.768444000', '2026-03-16T16:48:05.769104000',\n", + " '2026-03-16T16:48:06.769765000', '2026-03-16T16:48:07.770426000',\n", + " '2026-03-16T16:48:08.771087000', '2026-03-16T16:48:09.771748000',\n", + " '2026-03-16T16:48:10.772409000', '2026-03-16T16:48:11.773070000',\n", + " '2026-03-16T16:48:12.773731000', '2026-03-16T16:48:13.774392000',\n", + " '2026-03-16T16:48:14.775053000', '2026-03-16T16:48:15.775714000',\n", + " '2026-03-16T16:48:16.776375000', '2026-03-16T16:48:17.777036000',\n", + " '2026-03-16T16:48:18.777697000', '2026-03-16T16:48:19.760382000'],\n", + " dtype='datetime64[ns]') VV_quality_range_line(VV_quality_range_azimuth_time)int32dask.array<chunksize=(26,), meta=np.ndarray>
- dimensions :
- ['azimuth_time']
- dtype :
- <i4
- long_name :
- line
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -6225,14 +7220,14 @@ " \n", "
\n", @@ -6257,15 +7252,15 @@ "\n", " \n", " \n", "Bytes \n", - "27 B \n", - "27 B \n", + "104 B \n", + "104 B \n", "\n", " \n", "Shape \n", - "(27,) \n", - "(27,) \n", + "(26,) \n", + "(26,) \n", "\n", " \n", "Dask graph \n", @@ -6240,7 +7235,7 @@ "\n", " \n", " \n", "Data type \n", - "bool numpy.ndarray \n", + "int32 numpy.ndarray \n", "\n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 27 \n", - "1 \n", + "26 \n", + "1 \n", "\n", " fine_dce_azimuth_stop_time(azimuth_time)booldask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<b1', 'long_name': 'false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold'}
- dtype :
- <b1
- long_name :
- false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold
\n", + "
VV_quality_range_ground_range(VV_quality_range_ground_range)float640.0 400.0 ... 2.664e+05 2.664e+05array([ 0., 400., 800., ..., 265980., 266380., 266410.], shape=(671,)) VV_quality_range_pixel(VV_quality_range_ground_range)int32dask.array<chunksize=(671,), meta=np.ndarray>\n", "
\n", " \n", - "\n", " \n", "\n", @@ -6280,14 +7275,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "27 B \n", - "27 B \n", + "2.62 kiB \n", + "2.62 kiB \n", "\n", " \n", "Shape \n", - "(27,) \n", - "(27,) \n", + "(671,) \n", + "(671,) \n", "\n", " \n", "Dask graph \n", @@ -6295,32 +7290,32 @@ "\n", " \n", " \n", "Data type \n", - "bool numpy.ndarray \n", + "int32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 27 \n", - "1 \n", + "671 \n", + "1 \n", " geometry_dc_polynomial(azimuth_time, degree)float32dask.array<chunksize=(27, 3), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'degree'], 'dimensions': ['azimuth_time', 'degree'], 'dtype': '<f4', 'long_name': 'doppler centroid estimated from orbit, expressed as polynomial with 5 coefficients: doppler centroid = d0 + d1(tsr-t0) + d2(tsr-t0)^2 + d3(tsr-t0)^3 + d4(tsr-t0)^4, where tsr = 2-way slant range time'}
- dtype :
- <f4
- long_name :
- doppler centroid estimated from orbit, expressed as polynomial with 5 coefficients: doppler centroid = d0 + d1(tsr-t0) + d2(tsr-t0)^2 + d3(tsr-t0)^3 + d4(tsr-t0)^4, where tsr = 2-way slant range time
\n", + "
VH_conditions_antenna_pattern_elevation_angle(VH_conditions_antenna_pattern_azimuth_time, VH_conditions_antenna_pattern_count)float32dask.array<chunksize=(27, 730), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'count'], 'dimensions': ['azimuth_time', 'count'], 'dtype': '<f4', 'long_name': 'elevation angle to grid point', 'units': 'degrees'}
- dtype :
- <f4
- long_name :
- elevation angle to grid point
- units :
- degrees
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -6335,14 +7330,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "324 B \n", - "324 B \n", + "76.99 kiB \n", + "76.99 kiB \n", "\n", " \n", "Shape \n", - "(27, 3) \n", - "(27, 3) \n", + "(27, 730) \n", + "(27, 730) \n", "\n", " Dask graph \n", @@ -6356,26 +7351,26 @@ "\n", - " \n", "\n", + " \n", "\n", " \n", - " \n", "\n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 3 \n", - "27 \n", + "730 \n", + "27 \n", " t0(azimuth_time)float64dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'two-way slant range time origin for doppler centroid estimate', 'units': 's'}
- dtype :
- <f8
- long_name :
- two-way slant range time origin for doppler centroid estimate
- units :
- s
\n", + "
VH_conditions_antenna_pattern_incidence_angle(VH_conditions_antenna_pattern_azimuth_time, VH_conditions_antenna_pattern_count)float32dask.array<chunksize=(27, 730), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'count'], 'dimensions': ['azimuth_time', 'count'], 'dtype': '<f4', 'long_name': 'incidence angle to grid point', 'units': 'degrees'}
- dtype :
- <f4
- long_name :
- incidence angle to grid point
- units :
- degrees
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -6390,14 +7385,14 @@ " \n", "
\n", @@ -6422,479 +7417,15 @@ "\n", " \n", " \n", "Bytes \n", - "216 B \n", - "216 B \n", + "76.99 kiB \n", + "76.99 kiB \n", "\n", " \n", "Shape \n", - "(27,) \n", - "(27,) \n", + "(27, 730) \n", + "(27, 730) \n", "\n", " \n", "Dask graph \n", @@ -6405,7 +7400,7 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "float32 numpy.ndarray \n", "\n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 27 \n", - "1 \n", + "730 \n", + "27 \n", "\n", "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - " \n", - " \n", - " \n", - "\n", - " \n", - " \n", - " \n", - " <xarray.DatasetView> Size: 12kB\n", - "Dimensions: (azimuth_time: 10, ground_range: 21)\n", - "Coordinates:\n", - " * azimuth_time (azimuth_time) datetime64[ns] 80B 2026-03-16T16:47:...\n", - " * ground_range (ground_range) float64 168B 0.0 ... 2.664e+05\n", - " line (azimuth_time) uint32 40B dask.array<chunksize=(10,), meta=np.ndarray>\n", - " pixel (ground_range) uint32 84B dask.array<chunksize=(21,), meta=np.ndarray>\n", - "Data variables:\n", - " azimuth_time_gcp (azimuth_time, ground_range) datetime64[ns] 2kB dask.array<chunksize=(10, 21), meta=np.ndarray>\n", - " elevation_angle (azimuth_time, ground_range) float64 2kB dask.array<chunksize=(10, 21), meta=np.ndarray>\n", - " height (azimuth_time, ground_range) float64 2kB dask.array<chunksize=(10, 21), meta=np.ndarray>\n", - " incidence_angle (azimuth_time, ground_range) float64 2kB dask.array<chunksize=(10, 21), meta=np.ndarray>\n", - " latitude (azimuth_time, ground_range) float64 2kB dask.array<chunksize=(10, 21), meta=np.ndarray>\n", - " longitude (azimuth_time, ground_range) float64 2kB dask.array<chunksize=(10, 21), meta=np.ndarray>\n", - " slant_range_time_gcp (azimuth_time, ground_range) float64 2kB dask.array<chunksize=(10, 21), meta=np.ndarray>gcp
- azimuth_time: 10
- ground_range: 21
azimuth_time(azimuth_time)datetime64[ns]2026-03-16T16:47:54.761834 ... 2...array(['2026-03-16T16:47:54.761834000', '2026-03-16T16:47:57.762318000',\n", - " '2026-03-16T16:48:00.762803000', '2026-03-16T16:48:03.763288000',\n", - " '2026-03-16T16:48:06.763773000', '2026-03-16T16:48:09.764257000',\n", - " '2026-03-16T16:48:12.764742000', '2026-03-16T16:48:15.765227000',\n", - " '2026-03-16T16:48:18.765712000', '2026-03-16T16:48:19.760381000'],\n", - " dtype='datetime64[ns]') ground_range(ground_range)float640.0 1.333e+04 ... 2.664e+05array([ 0., 13330., 26660., 39990., 53320., 66650., 79980., 93310.,\n", - " 106640., 119970., 133300., 146630., 159960., 173290., 186620., 199950.,\n", - " 213280., 226610., 239940., 253270., 266410.]) line(azimuth_time)uint32dask.array<chunksize=(10,), meta=np.ndarray>\n", + "
VH_conditions_antenna_pattern_roll(VH_conditions_antenna_pattern_azimuth_time)float64dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'estimated roll angle for this antenna pattern', 'units': 'degrees'}
- dtype :
- <f8
- long_name :
- estimated roll angle for this antenna pattern
- units :
- degrees
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -6909,14 +7440,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "40 B \n", - "40 B \n", + "216 B \n", + "216 B \n", "\n", " \n", "Shape \n", - "(10,) \n", - "(10,) \n", + "(27,) \n", + "(27,) \n", "\n", " \n", "Dask graph \n", @@ -6924,32 +7455,32 @@ "\n", " \n", " \n", "Data type \n", - "uint32 numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 10 \n", - "1 \n", + "27 \n", + "1 \n", " pixel(ground_range)uint32dask.array<chunksize=(21,), meta=np.ndarray>\n", + "
VH_conditions_antenna_pattern_slant_range_time_ap(VH_conditions_antenna_pattern_azimuth_time, VH_conditions_antenna_pattern_count)float64dask.array<chunksize=(27, 730), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'count'], 'dimensions': ['azimuth_time', 'count'], 'dtype': '<f8', 'long_name': 'two-way slant range time to sample', 'units': 's'}
- dtype :
- <f8
- long_name :
- two-way slant range time to sample
- units :
- s
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -6964,14 +7495,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "84 B \n", - "84 B \n", + "153.98 kiB \n", + "153.98 kiB \n", "\n", " \n", "Shape \n", - "(21,) \n", - "(21,) \n", + "(27, 730) \n", + "(27, 730) \n", "\n", " \n", "Dask graph \n", @@ -6979,32 +7510,32 @@ "\n", " \n", " \n", "Data type \n", - "uint32 numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 21 \n", - "1 \n", + "730 \n", + "27 \n", "
azimuth_time_gcp(azimuth_time, ground_range)datetime64[ns]dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", + "
VH_conditions_antenna_pattern_swath(VH_conditions_antenna_pattern_azimuth_time)<U3dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': 'U3', 'long_name': 'Swath'}
- dtype :
- U3
- long_name :
- Swath
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -7019,14 +7550,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "1.64 kiB \n", - "1.64 kiB \n", + "324 B \n", + "324 B \n", "\n", " \n", "Shape \n", - "(10, 21) \n", - "(10, 21) \n", + "(27,) \n", + "(27,) \n", "\n", " \n", "Dask graph \n", @@ -7034,32 +7565,32 @@ "\n", " \n", " \n", "Data type \n", - "datetime64[ns] numpy.ndarray \n", + "\n", " \n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 21 \n", - "10 \n", + "27 \n", + "1 \n", " elevation_angle(azimuth_time, ground_range)float64dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", + "
VH_conditions_antenna_pattern_terrain_height(VH_conditions_antenna_pattern_azimuth_time)float64dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'mean terrain height in range for this antenna pattern (in metres above the ellipsoid) for the given zero-doppler azimuth time', 'units': 'm'}
- dtype :
- <f8
- long_name :
- mean terrain height in range for this antenna pattern (in metres above the ellipsoid) for the given zero-doppler azimuth time
- units :
- m
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -7074,14 +7605,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "1.64 kiB \n", - "1.64 kiB \n", + "216 B \n", + "216 B \n", "\n", " \n", "Shape \n", - "(10, 21) \n", - "(10, 21) \n", + "(27,) \n", + "(27,) \n", "\n", " Dask graph \n", @@ -7095,26 +7626,26 @@ "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 21 \n", - "10 \n", + "27 \n", + "1 \n", " height(azimuth_time, ground_range)float64dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", + "
VH_conditions_attitude_pitch(VH_conditions_attitude_azimuth_time)float64dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'platform pitch angle calculated from ancillary attitude data', 'units': 'degrees'}
- dtype :
- <f8
- long_name :
- platform pitch angle calculated from ancillary attitude data
- units :
- degrees
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -7129,14 +7660,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "1.64 kiB \n", - "1.64 kiB \n", + "200 B \n", + "200 B \n", "\n", " \n", "Shape \n", - "(10, 21) \n", - "(10, 21) \n", + "(25,) \n", + "(25,) \n", "\n", " Dask graph \n", @@ -7150,26 +7681,26 @@ "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 21 \n", - "10 \n", + "25 \n", + "1 \n", " incidence_angle(azimuth_time, ground_range)float64dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", + "
VH_conditions_attitude_q0(VH_conditions_attitude_azimuth_time)float32dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f4', 'long_name': 'q0 attitude quaternion as extracted from ancillary attitude data'}
- dtype :
- <f4
- long_name :
- q0 attitude quaternion as extracted from ancillary attitude data
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -7184,14 +7715,14 @@ " \n", "
\n", "\n", " \n", + "Bytes \n", - "1.64 kiB \n", - "1.64 kiB \n", - "100 B \n", + "100 B \n", + " \n", " \n", "\n", " \n", "Shape \n", - "(10, 21) \n", - "(10, 21) \n", + "(25,) \n", + "(25,) \n", "\n", " \n", "Dask graph \n", @@ -7199,32 +7730,32 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "float32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 21 \n", - "10 \n", + "25 \n", + "1 \n", " latitude(azimuth_time, ground_range)float64dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", + "
VH_conditions_attitude_q1(VH_conditions_attitude_azimuth_time)float32dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f4', 'long_name': 'q1 attitude quaternion as extracted from ancillary attitude data'}
- dtype :
- <f4
- long_name :
- q1 attitude quaternion as extracted from ancillary attitude data
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -7239,14 +7770,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "1.64 kiB \n", - "1.64 kiB \n", + "100 B \n", + "100 B \n", "\n", " \n", "Shape \n", - "(10, 21) \n", - "(10, 21) \n", + "(25,) \n", + "(25,) \n", "\n", " \n", "Dask graph \n", @@ -7254,32 +7785,32 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "float32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 21 \n", - "10 \n", + "25 \n", + "1 \n", " longitude(azimuth_time, ground_range)float64dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", + "
VH_conditions_attitude_q2(VH_conditions_attitude_azimuth_time)float32dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f4', 'long_name': 'q2 attitude quaternion as extracted from ancillary attitude data'}
- dtype :
- <f4
- long_name :
- q2 attitude quaternion as extracted from ancillary attitude data
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -7294,14 +7825,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "1.64 kiB \n", - "1.64 kiB \n", + "100 B \n", + "100 B \n", "\n", " \n", "Shape \n", - "(10, 21) \n", - "(10, 21) \n", + "(25,) \n", + "(25,) \n", "\n", " \n", "Dask graph \n", @@ -7309,32 +7840,32 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "float32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 21 \n", - "10 \n", + "25 \n", + "1 \n", " slant_range_time_gcp(azimuth_time, ground_range)float64dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", + "
VH_conditions_attitude_q3(VH_conditions_attitude_azimuth_time)float32dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f4', 'long_name': 'q3 attitude quaternion as extracted from ancillary attitude data'}
- dtype :
- <f4
- long_name :
- q3 attitude quaternion as extracted from ancillary attitude data
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -7349,14 +7880,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "1.64 kiB \n", - "1.64 kiB \n", + "100 B \n", + "100 B \n", "\n", " \n", "Shape \n", - "(10, 21) \n", - "(10, 21) \n", + "(25,) \n", + "(25,) \n", "\n", " \n", "Dask graph \n", @@ -7364,490 +7895,582 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "float32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 21 \n", - "10 \n", + "25 \n", + "1 \n", "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - " \n", - " \n", - " \n", - "\n", - " \n", - " \n", - " \n", - " <xarray.DatasetView> Size: 964B\n", - "Dimensions: (azimuth_time: 17, axis: 3)\n", - "Coordinates:\n", - " * axis (axis) <U1 12B 'x' 'y' 'z'\n", - " * azimuth_time (azimuth_time) datetime64[ns] 136B 2026-03-16T16:46:46.6816...\n", - "Data variables:\n", - " position (azimuth_time, axis) float64 408B dask.array<chunksize=(17, 3), meta=np.ndarray>\n", - " velocity (azimuth_time, axis) float64 408B dask.array<chunksize=(17, 3), meta=np.ndarray>orbit
- azimuth_time: 17
- axis: 3
axis(axis)<U1'x' 'y' 'z'array(['x', 'y', 'z'], dtype='<U1') azimuth_time(azimuth_time)datetime64[ns]2026-03-16T16:46:46.681692 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- time stamp at which orbit state vectors apply
array(['2026-03-16T16:46:46.681692000', '2026-03-16T16:46:56.681692000',\n", - " '2026-03-16T16:47:06.681692000', '2026-03-16T16:47:16.681692000',\n", - " '2026-03-16T16:47:26.681692000', '2026-03-16T16:47:36.681693000',\n", - " '2026-03-16T16:47:46.681693000', '2026-03-16T16:47:56.681692000',\n", - " '2026-03-16T16:48:06.681692000', '2026-03-16T16:48:16.681692000',\n", - " '2026-03-16T16:48:26.681692000', '2026-03-16T16:48:36.681692000',\n", - " '2026-03-16T16:48:46.681692000', '2026-03-16T16:48:56.681693000',\n", - " '2026-03-16T16:49:06.681693000', '2026-03-16T16:49:16.681692000',\n", - " '2026-03-16T16:49:26.681692000'], dtype='datetime64[ns]')
position(azimuth_time, axis)float64dask.array<chunksize=(17, 3), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'axis'], 'dimensions': ['azimuth_time', 'axis'], 'dtype': '<f8', 'long_name': 'position vector', 'units': 'm'}
- dtype :
- <f8
- long_name :
- position vector
- units :
- m
\n", + " \n", + "
27 \n", + "1 \n", + "\n", + " \n", + " \n", + " VH_conditions_doppler_centroid_geometry_dc_polynomial(VH_conditions_doppler_centroid_azimuth_time, VH_conditions_doppler_centroid_degree)float32dask.array<chunksize=(27, 3), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'degree'], 'dimensions': ['azimuth_time', 'degree'], 'dtype': '<f4', 'long_name': 'doppler centroid estimated from orbit, expressed as polynomial with 5 coefficients: doppler centroid = d0 + d1(tsr-t0) + d2(tsr-t0)^2 + d3(tsr-t0)^3 + d4(tsr-t0)^4, where tsr = 2-way slant range time'}
- dtype :
- <f4
- long_name :
- doppler centroid estimated from orbit, expressed as polynomial with 5 coefficients: doppler centroid = d0 + d1(tsr-t0) + d2(tsr-t0)^2 + d3(tsr-t0)^3 + d4(tsr-t0)^4, where tsr = 2-way slant range time
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -7862,14 +8485,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "408 B \n", - "408 B \n", + "324 B \n", + "324 B \n", "\n", " \n", "Shape \n", - "(17, 3) \n", - "(17, 3) \n", + "(27, 3) \n", + "(27, 3) \n", "\n", " \n", "Dask graph \n", @@ -7877,32 +8500,32 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "float32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", - " \n", "\n", - " \n", + " \n", + " \n", "\n", " \n", " \n", - " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 3 \n", - "17 \n", + "3 \n", + "27 \n", " velocity(azimuth_time, axis)float64dask.array<chunksize=(17, 3), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'axis'], 'dimensions': ['azimuth_time', 'axis'], 'dtype': '<f8', 'long_name': 'velocity vector', 'units': 'm/s'}
- dtype :
- <f8
- long_name :
- velocity vector
- units :
- m/s
\n", + "
VH_conditions_doppler_centroid_t0(VH_conditions_doppler_centroid_azimuth_time)float64dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'two-way slant range time origin for doppler centroid estimate', 'units': 's'}
- dtype :
- <f8
- long_name :
- two-way slant range time origin for doppler centroid estimate
- units :
- s
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -7917,14 +8540,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "408 B \n", - "408 B \n", + "216 B \n", + "216 B \n", "\n", " \n", "Shape \n", - "(17, 3) \n", - "(17, 3) \n", + "(27,) \n", + "(27,) \n", "\n", " Dask graph \n", @@ -7938,481 +8561,26 @@ "\n", - " \n", "\n", + " \n", "\n", " \n", - " \n", "\n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 3 \n", - "17 \n", + "27 \n", + "1 \n", "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - " \n", - " \n", - " \n", - "\n", - " \n", - " \n", - " \n", - " <xarray.DatasetView> Size: 890MB\n", - "Dimensions: (azimuth_time: 16689, ground_range: 26642)\n", - "Coordinates:\n", - " * azimuth_time (azimuth_time) datetime64[ns] 134kB 2026-03-16T16:47:54.761...\n", - " * ground_range (ground_range) float64 213kB 0.0 10.0 ... 2.664e+05 2.664e+05\n", - " line (azimuth_time) int64 134kB dask.array<chunksize=(2048,), meta=np.ndarray>\n", - " pixel (ground_range) int64 213kB dask.array<chunksize=(4096,), meta=np.ndarray>\n", - "Data variables:\n", - " grd (azimuth_time, ground_range) uint16 889MB dask.array<chunksize=(2048, 4096), meta=np.ndarray>measurements
- azimuth_time: 16689
- ground_range: 26642
azimuth_time(azimuth_time)datetime64[ns]2026-03-16T16:47:54.761834 ... 2...array(['2026-03-16T16:47:54.761834000', '2026-03-16T16:47:54.763331995',\n", - " '2026-03-16T16:47:54.764829990', ..., '2026-03-16T16:48:19.757385009',\n", - " '2026-03-16T16:48:19.758883004', '2026-03-16T16:48:19.760381000'],\n", - " shape=(16689,), dtype='datetime64[ns]') ground_range(ground_range)float640.0 10.0 ... 2.664e+05 2.664e+05array([0.0000e+00, 1.0000e+01, 2.0000e+01, ..., 2.6639e+05, 2.6640e+05,\n", - " 2.6641e+05], shape=(26642,)) line(azimuth_time)int64dask.array<chunksize=(2048,), meta=np.ndarray>\n", + "
VH_conditions_gcp_azimuth_time_gcp(VH_conditions_gcp_azimuth_time, VH_conditions_gcp_ground_range)datetime64[ns]dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -8427,55 +8595,47 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "130.38 kiB \n", - "16.00 kiB \n", + "1.64 kiB \n", + "1.64 kiB \n", "\n", " \n", "Shape \n", - "(16689,) \n", - "(2048,) \n", + "(10, 21) \n", + "(10, 21) \n", "\n", " \n", "Dask graph \n", - "9 chunks in 2 graph layers \n", + "1 chunks in 2 graph layers \n", "\n", " \n", " \n", "Data type \n", - "int64 numpy.ndarray \n", + "datetime64[ns] numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 16689 \n", - "1 \n", + "21 \n", + "10 \n", " pixel(ground_range)int64dask.array<chunksize=(4096,), meta=np.ndarray>\n", + "
VH_conditions_gcp_elevation_angle(VH_conditions_gcp_azimuth_time, VH_conditions_gcp_ground_range)float64dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -8490,53 +8650,47 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "208.14 kiB \n", - "32.00 kiB \n", + "1.64 kiB \n", + "1.64 kiB \n", "\n", " \n", "Shape \n", - "(26642,) \n", - "(4096,) \n", + "(10, 21) \n", + "(10, 21) \n", "\n", " \n", "Dask graph \n", - "7 chunks in 2 graph layers \n", + "1 chunks in 2 graph layers \n", "\n", " \n", " \n", "Data type \n", - "int64 numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 26642 \n", - "1 \n", + "21 \n", + "10 \n", "
grd(azimuth_time, ground_range)uint16dask.array<chunksize=(2048, 4096), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'line', 'pixel', 'ground_range'], 'dimensions': ['azimuth_time', 'ground_range'], 'dtype': '<u2', 'long_name': 'measurement data set for GRD IW'}
- dtype :
- <u2
- long_name :
- measurement data set for GRD IW
\n", + "
VH_conditions_gcp_height(VH_conditions_gcp_azimuth_time, VH_conditions_gcp_ground_range)float64dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -8551,975 +8705,838 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "848.06 MiB \n", - "16.00 MiB \n", + "1.64 kiB \n", + "1.64 kiB \n", "\n", " \n", "Shape \n", - "(16689, 26642) \n", - "(2048, 4096) \n", + "(10, 21) \n", + "(10, 21) \n", "\n", " \n", "Dask graph \n", - "63 chunks in 2 graph layers \n", + "1 chunks in 2 graph layers \n", "\n", " \n", " \n", "Data type \n", - "uint16 numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 26642 \n", - "16689 \n", + "21 \n", + "10 \n", "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - " \n", - " \n", - " \n", - "\n", - " \n", - " \n", - " \n", - " <xarray.DatasetView> Size: 0B\n", - "Dimensions: ()\n", - "Data variables:\n", - " *empty*quality
\n", - " \n", - "\n", - " \n", + " \n", + "\n", - " \n", - "\n", - " \n", - " \n", - " \n", - " \n", - "\n", - " \n", - " \n", - " \n", - " 730 \n", + "27 \n", "<xarray.DatasetView> Size: 297kB\n", - "Dimensions: (azimuth_time: 27, ground_range: 668)\n", - "Coordinates:\n", - " * azimuth_time (azimuth_time) datetime64[ns] 216B 2026-03-16T16:47:54.7618...\n", - " * ground_range (ground_range) float64 5kB 0.0 6.675e+06 ... 4.446e+09\n", - " line (azimuth_time) uint32 108B dask.array<chunksize=(27,), meta=np.ndarray>\n", - " pixel (ground_range) uint32 3kB dask.array<chunksize=(668,), meta=np.ndarray>\n", - "Data variables:\n", - " beta_nought (azimuth_time, ground_range) float32 72kB dask.array<chunksize=(27, 668), meta=np.ndarray>\n", - " dn (azimuth_time, ground_range) float32 72kB dask.array<chunksize=(27, 668), meta=np.ndarray>\n", - " gamma (azimuth_time, ground_range) float32 72kB dask.array<chunksize=(27, 668), meta=np.ndarray>\n", - " sigma_nought (azimuth_time, ground_range) float32 72kB dask.array<chunksize=(27, 668), meta=np.ndarray>calibration
- azimuth_time: 27
- ground_range: 668
azimuth_time(azimuth_time)datetime64[ns]2026-03-16T16:47:54.761834 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- zero doppler azimuth time at which calibration vector applies
array(['2026-03-16T16:47:54.761834000', '2026-03-16T16:47:55.761834000',\n", - " '2026-03-16T16:47:56.761834000', '2026-03-16T16:47:57.761834000',\n", - " '2026-03-16T16:47:58.761834000', '2026-03-16T16:47:59.761834000',\n", - " '2026-03-16T16:48:00.761834000', '2026-03-16T16:48:01.761834000',\n", - " '2026-03-16T16:48:02.761834000', '2026-03-16T16:48:03.761834000',\n", - " '2026-03-16T16:48:04.761834000', '2026-03-16T16:48:05.761834000',\n", - " '2026-03-16T16:48:06.761834000', '2026-03-16T16:48:07.761834000',\n", - " '2026-03-16T16:48:08.761834000', '2026-03-16T16:48:09.761834000',\n", - " '2026-03-16T16:48:10.761834000', '2026-03-16T16:48:11.761834000',\n", - " '2026-03-16T16:48:12.761834000', '2026-03-16T16:48:13.761834000',\n", - " '2026-03-16T16:48:14.761834000', '2026-03-16T16:48:15.761834000',\n", - " '2026-03-16T16:48:16.761834000', '2026-03-16T16:48:17.761834000',\n", - " '2026-03-16T16:48:18.761834000', '2026-03-16T16:48:19.761834000',\n", - " '2026-03-16T16:48:20.761834000'], dtype='datetime64[ns]') ground_range(ground_range)float640.0 6.675e+06 ... 4.446e+09
- dimensions :
- ['ground_range']
- dtype :
- <f8
array([0.000000e+00, 6.675200e+06, 1.335040e+07, ..., 4.439008e+09,\n", - " 4.445683e+09, 4.445850e+09], shape=(668,)) line(azimuth_time)uint32dask.array<chunksize=(27,), meta=np.ndarray>
- dimensions :
- ['azimuth_time']
- dtype :
- <u4
- long_name :
- image line at which the calibration vector applies
\n", + " \n", + " \n", + "
VV_conditions_antenna_pattern_incidence_angle(VV_conditions_antenna_pattern_azimuth_time, VV_conditions_antenna_pattern_count)float32dask.array<chunksize=(27, 730), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'count'], 'dimensions': ['azimuth_time', 'count'], 'dtype': '<f4', 'long_name': 'incidence angle to grid point', 'units': 'degrees'}
- dtype :
- <f4
- long_name :
- incidence angle to grid point
- units :
- degrees
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -9534,14 +9551,14 @@ " \n", "
\n", @@ -9566,15 +9583,15 @@ "\n", " \n", " \n", "Bytes \n", - "108 B \n", - "108 B \n", + "76.99 kiB \n", + "76.99 kiB \n", "\n", " \n", "Shape \n", - "(27,) \n", - "(27,) \n", + "(27, 730) \n", + "(27, 730) \n", "\n", " \n", "Dask graph \n", @@ -9549,7 +9566,7 @@ "\n", " \n", " \n", "Data type \n", - "uint32 numpy.ndarray \n", + "float32 numpy.ndarray \n", "\n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 27 \n", - "1 \n", + "730 \n", + "27 \n", "\n", " pixel(ground_range)uint32dask.array<chunksize=(668,), meta=np.ndarray>
- dimensions :
- ['ground_range']
- dtype :
- <u4
- long_name :
- image pixel at which the calibration vector applies (this array contains the count attribute number of integer values (i.e. one value per point in the noise vector); the maximum length of this array is one value for every pixel in an image line, however in general the vector is subsampled)
\n", + "
VV_conditions_antenna_pattern_roll(VV_conditions_antenna_pattern_azimuth_time)float64dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'estimated roll angle for this antenna pattern', 'units': 'degrees'}
- dtype :
- <f8
- long_name :
- estimated roll angle for this antenna pattern
- units :
- degrees
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -9589,14 +9606,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "2.61 kiB \n", - "2.61 kiB \n", + "216 B \n", + "216 B \n", "\n", " \n", "Shape \n", - "(668,) \n", - "(668,) \n", + "(27,) \n", + "(27,) \n", "\n", " \n", "Dask graph \n", @@ -9604,32 +9621,32 @@ "\n", " \n", " \n", "Data type \n", - "uint32 numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 668 \n", - "1 \n", + "27 \n", + "1 \n", "
beta_nought(azimuth_time, ground_range)float32dask.array<chunksize=(27, 668), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'line', 'pixel', 'ground_range'], 'dimensions': ['azimuth_time', 'ground_range'], 'dtype': '<f4', 'long_name': 'beta nought calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)'}
- dtype :
- <f4
- long_name :
- beta nought calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)
\n", + "
VV_conditions_antenna_pattern_slant_range_time_ap(VV_conditions_antenna_pattern_azimuth_time, VV_conditions_antenna_pattern_count)float64dask.array<chunksize=(27, 730), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'count'], 'dimensions': ['azimuth_time', 'count'], 'dtype': '<f8', 'long_name': 'two-way slant range time to sample', 'units': 's'}
- dtype :
- <f8
- long_name :
- two-way slant range time to sample
- units :
- s
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -9644,14 +9661,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "70.45 kiB \n", - "70.45 kiB \n", + "153.98 kiB \n", + "153.98 kiB \n", "\n", " \n", "Shape \n", - "(27, 668) \n", - "(27, 668) \n", + "(27, 730) \n", + "(27, 730) \n", "\n", " \n", "Dask graph \n", @@ -9659,32 +9676,32 @@ "\n", " \n", " \n", "Data type \n", - "float32 numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 668 \n", - "27 \n", + "730 \n", + "27 \n", " dn(azimuth_time, ground_range)float32dask.array<chunksize=(27, 668), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'line', 'pixel', 'ground_range'], 'dimensions': ['azimuth_time', 'ground_range'], 'dtype': '<f4', 'long_name': 'digital number calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)'}
- dtype :
- <f4
- long_name :
- digital number calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)
\n", + "
VV_conditions_antenna_pattern_swath(VV_conditions_antenna_pattern_azimuth_time)<U3dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': 'U3', 'long_name': 'Swath'}
- dtype :
- U3
- long_name :
- Swath
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -9699,14 +9716,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "70.45 kiB \n", - "70.45 kiB \n", + "324 B \n", + "324 B \n", "\n", " \n", "Shape \n", - "(27, 668) \n", - "(27, 668) \n", + "(27,) \n", + "(27,) \n", "\n", " \n", "Dask graph \n", @@ -9714,32 +9731,32 @@ "\n", " \n", " \n", "Data type \n", - "float32 numpy.ndarray \n", + "\n", " \n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 668 \n", - "27 \n", + "27 \n", + "1 \n", " gamma(azimuth_time, ground_range)float32dask.array<chunksize=(27, 668), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'line', 'pixel', 'ground_range'], 'dimensions': ['azimuth_time', 'ground_range'], 'dtype': '<f4', 'long_name': 'gamma calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)'}
- dtype :
- <f4
- long_name :
- gamma calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)
\n", + "
VV_conditions_antenna_pattern_terrain_height(VV_conditions_antenna_pattern_azimuth_time)float64dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'mean terrain height in range for this antenna pattern (in metres above the ellipsoid) for the given zero-doppler azimuth time', 'units': 'm'}
- dtype :
- <f8
- long_name :
- mean terrain height in range for this antenna pattern (in metres above the ellipsoid) for the given zero-doppler azimuth time
- units :
- m
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -9754,14 +9771,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "70.45 kiB \n", - "70.45 kiB \n", + "216 B \n", + "216 B \n", "\n", " \n", "Shape \n", - "(27, 668) \n", - "(27, 668) \n", + "(27,) \n", + "(27,) \n", "\n", " \n", "Dask graph \n", @@ -9769,32 +9786,32 @@ "\n", " \n", " \n", "Data type \n", - "float32 numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 668 \n", - "27 \n", + "27 \n", + "1 \n", " sigma_nought(azimuth_time, ground_range)float32dask.array<chunksize=(27, 668), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'line', 'pixel', 'ground_range'], 'dimensions': ['azimuth_time', 'ground_range'], 'dtype': '<f4', 'long_name': 'sigma nought calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)'}
- dtype :
- <f4
- long_name :
- sigma nought calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)
\n", + "
VV_conditions_attitude_pitch(VV_conditions_attitude_azimuth_time)float64dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'platform pitch angle calculated from ancillary attitude data', 'units': 'degrees'}
- dtype :
- <f8
- long_name :
- platform pitch angle calculated from ancillary attitude data
- units :
- degrees
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -9809,14 +9826,14 @@ " \n", "
\n", @@ -9841,469 +9858,15 @@ "\n", " \n", " \n", "Bytes \n", - "70.45 kiB \n", - "70.45 kiB \n", + "200 B \n", + "200 B \n", "\n", " \n", "Shape \n", - "(27, 668) \n", - "(27, 668) \n", + "(25,) \n", + "(25,) \n", "\n", " \n", "Dask graph \n", @@ -9824,7 +9841,7 @@ "\n", " \n", " \n", "Data type \n", - "float32 numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 668 \n", - "27 \n", + "25 \n", + "1 \n", "\n", "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - " \n", - " \n", - " \n", - "\n", - " \n", - " \n", - " \n", - " <xarray.DatasetView> Size: 41kB\n", - "Dimensions: (swath: 3, azimuth_time: 1688)\n", - "Coordinates:\n", - " first_azimuth_time (swath) int32 12B dask.array<chunksize=(3,), meta=np.ndarray>\n", - " first_range_sample (swath) int32 12B dask.array<chunksize=(3,), meta=np.ndarray>\n", - " last_azimuth_time (swath) int32 12B dask.array<chunksize=(3,), meta=np.ndarray>\n", - " last_range_sample (swath) int32 12B dask.array<chunksize=(3,), meta=np.ndarray>\n", - " line (swath, azimuth_time) int32 20kB dask.array<chunksize=(3, 1688), meta=np.ndarray>\n", - " * swath (swath) <U3 36B 'IW1' 'IW2' 'IW3'\n", - "Dimensions without coordinates: azimuth_time\n", - "Data variables:\n", - " noise_azimuth_lut (swath, azimuth_time) float32 20kB dask.array<chunksize=(3, 1688), meta=np.ndarray>noise_azimuth
- swath: 3
- azimuth_time: 1688
first_azimuth_time(swath)int32dask.array<chunksize=(3,), meta=np.ndarray>
- dtype :
- <i4
- long_name :
- first azimuth line azimuth thermal noise correction
\n", + "
VV_conditions_attitude_q0(VV_conditions_attitude_azimuth_time)float32dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f4', 'long_name': 'q0 attitude quaternion as extracted from ancillary attitude data'}
- dtype :
- <f4
- long_name :
- q0 attitude quaternion as extracted from ancillary attitude data
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -10318,14 +9881,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "12 B \n", - "12 B \n", + "100 B \n", + "100 B \n", "\n", " \n", "Shape \n", - "(3,) \n", - "(3,) \n", + "(25,) \n", + "(25,) \n", "\n", " \n", "Dask graph \n", @@ -10333,32 +9896,32 @@ "\n", " \n", " \n", "Data type \n", - "int32 numpy.ndarray \n", + "float32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 3 \n", - "1 \n", + "25 \n", + "1 \n", " first_range_sample(swath)int32dask.array<chunksize=(3,), meta=np.ndarray>
- dtype :
- <i4
- long_name :
- first range sample azimuth thermal noise correction
\n", + "
VV_conditions_attitude_q1(VV_conditions_attitude_azimuth_time)float32dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f4', 'long_name': 'q1 attitude quaternion as extracted from ancillary attitude data'}
- dtype :
- <f4
- long_name :
- q1 attitude quaternion as extracted from ancillary attitude data
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -10373,14 +9936,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "12 B \n", - "12 B \n", + "100 B \n", + "100 B \n", "\n", " \n", "Shape \n", - "(3,) \n", - "(3,) \n", + "(25,) \n", + "(25,) \n", "\n", " \n", "Dask graph \n", @@ -10388,32 +9951,32 @@ "\n", " \n", " \n", "Data type \n", - "int32 numpy.ndarray \n", + "float32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 3 \n", - "1 \n", + "25 \n", + "1 \n", " last_azimuth_time(swath)int32dask.array<chunksize=(3,), meta=np.ndarray>
- dtype :
- <i4
- long_name :
- last azimuth line azimuth thermal noise correction
\n", + "
VV_conditions_attitude_q2(VV_conditions_attitude_azimuth_time)float32dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f4', 'long_name': 'q2 attitude quaternion as extracted from ancillary attitude data'}
- dtype :
- <f4
- long_name :
- q2 attitude quaternion as extracted from ancillary attitude data
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -10428,14 +9991,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "12 B \n", - "12 B \n", + "100 B \n", + "100 B \n", "\n", " \n", "Shape \n", - "(3,) \n", - "(3,) \n", + "(25,) \n", + "(25,) \n", "\n", " \n", "Dask graph \n", @@ -10443,32 +10006,32 @@ "\n", " \n", " \n", "Data type \n", - "int32 numpy.ndarray \n", + "float32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 3 \n", - "1 \n", + "25 \n", + "1 \n", " last_range_sample(swath)int32dask.array<chunksize=(3,), meta=np.ndarray>
- dtype :
- <i4
- long_name :
- last range sample azimuth thermal noise correction
\n", + "
VV_conditions_attitude_q3(VV_conditions_attitude_azimuth_time)float32dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f4', 'long_name': 'q3 attitude quaternion as extracted from ancillary attitude data'}
- dtype :
- <f4
- long_name :
- q3 attitude quaternion as extracted from ancillary attitude data
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -10483,14 +10046,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "12 B \n", - "12 B \n", + "100 B \n", + "100 B \n", "\n", " \n", "Shape \n", - "(3,) \n", - "(3,) \n", + "(25,) \n", + "(25,) \n", "\n", " \n", "Dask graph \n", @@ -10498,32 +10061,32 @@ "\n", " \n", " \n", "Data type \n", - "int32 numpy.ndarray \n", + "float32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 3 \n", - "1 \n", + "25 \n", + "1 \n", " line(swath, azimuth_time)int32dask.array<chunksize=(3, 1688), meta=np.ndarray>
- dimensions :
- ['swath', 'azimuth_time']
- dtype :
- <i4
- long_name :
- line
\n", + "
VV_conditions_attitude_roll(VV_conditions_attitude_azimuth_time)float64dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'platform roll angle calculated from ancillary attitude data', 'units': 'degrees'}
- dtype :
- <f8
- long_name :
- platform roll angle calculated from ancillary attitude data
- units :
- degrees
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -10538,14 +10101,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "19.78 kiB \n", - "19.78 kiB \n", + "200 B \n", + "200 B \n", "\n", " \n", "Shape \n", - "(3, 1688) \n", - "(3, 1688) \n", + "(25,) \n", + "(25,) \n", "\n", " \n", "Dask graph \n", @@ -10553,32 +10116,32 @@ "\n", " \n", " \n", "Data type \n", - "int32 numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 1688 \n", - "3 \n", + "25 \n", + "1 \n", " swath(swath)<U3'IW1' 'IW2' 'IW3'
- dimensions :
- ['swath']
- dtype :
- U3
- long_name :
- Swath
array(['IW1', 'IW2', 'IW3'], dtype='<U3')
noise_azimuth_lut(swath, azimuth_time)float32dask.array<chunksize=(3, 1688), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['line', 'swath', 'first_azimuth_time', 'last_azimuth_time', 'first_range_sample', 'last_range_sample'], 'dimensions': ['swath', 'azimuth_time'], 'dtype': '<f4', 'long_name': 'azimuth thermal noise correction vector power values (this array contains the count attribute number of floating point values)'}
- dtype :
- <f4
- long_name :
- azimuth thermal noise correction vector power values (this array contains the count attribute number of floating point values)
\n", + "
VV_conditions_attitude_wx(VV_conditions_attitude_azimuth_time)float64dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'x component of angular velocity vector as extracted from ancillary attitude data', 'units': 'degrees/s'}
- dtype :
- <f8
- long_name :
- x component of angular velocity vector as extracted from ancillary attitude data
- units :
- degrees/s
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -10593,14 +10156,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "19.78 kiB \n", - "19.78 kiB \n", + "200 B \n", + "200 B \n", "\n", " \n", "Shape \n", - "(3, 1688) \n", - "(3, 1688) \n", + "(25,) \n", + "(25,) \n", "\n", " \n", "Dask graph \n", @@ -10608,483 +10171,307 @@ "\n", " \n", " \n", "Data type \n", - "float32 numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 1688 \n", - "3 \n", + "25 \n", + "1 \n", "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - " \n", - " \n", - " \n", - "\n", - " \n", - " \n", - " \n", - " <xarray.DatasetView> Size: 279kB\n", - "Dimensions: (azimuth_time: 26, ground_range: 671)\n", - "Coordinates:\n", - " ground_range (azimuth_time, ground_range) float64 140kB dask.array<chunksize=(26, 671), meta=np.ndarray>\n", - " * azimuth_time (azimuth_time) datetime64[ns] 208B 2026-03-16T16:47:54.7...\n", - " line (azimuth_time) int32 104B dask.array<chunksize=(26,), meta=np.ndarray>\n", - " pixel (azimuth_time, ground_range) int32 70kB dask.array<chunksize=(26, 671), meta=np.ndarray>\n", - "Data variables:\n", - " noise_range_lut (azimuth_time, ground_range) float32 70kB dask.array<chunksize=(26, 671), meta=np.ndarray>noise_range
- azimuth_time: 26
- ground_range: 671
ground_range(azimuth_time, ground_range)float64dask.array<chunksize=(26, 671), meta=np.ndarray>\n", + " \n", + "
27 \n", + "1 \n", + "\n", + " \n", + " \n", + " VV_conditions_doppler_centroid_data_dc_rms_error_above_threshold(VV_conditions_doppler_centroid_azimuth_time)booldask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<b1', 'long_name': 'false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold'}
- dtype :
- <b1
- long_name :
- false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -11099,14 +10486,14 @@ " \n", "
\n", @@ -11131,28 +10518,15 @@ "\n", " \n", " \n", "Bytes \n", - "136.30 kiB \n", - "136.30 kiB \n", + "27 B \n", + "27 B \n", "\n", " \n", "Shape \n", - "(26, 671) \n", - "(26, 671) \n", + "(27,) \n", + "(27,) \n", "\n", " \n", "Dask graph \n", @@ -11114,7 +10501,7 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "bool numpy.ndarray \n", "\n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 671 \n", - "26 \n", + "27 \n", + "1 \n", "\n", " azimuth_time(azimuth_time)datetime64[ns]2026-03-16T16:47:54.761834 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- zero doppler azimuth time at which noise vector applies
array(['2026-03-16T16:47:54.761834000', '2026-03-16T16:47:55.762495000',\n", - " '2026-03-16T16:47:56.763156000', '2026-03-16T16:47:57.763817000',\n", - " '2026-03-16T16:47:58.764478000', '2026-03-16T16:47:59.765139000',\n", - " '2026-03-16T16:48:00.765800000', '2026-03-16T16:48:01.766461000',\n", - " '2026-03-16T16:48:02.767122000', '2026-03-16T16:48:03.767783000',\n", - " '2026-03-16T16:48:04.768444000', '2026-03-16T16:48:05.769104000',\n", - " '2026-03-16T16:48:06.769765000', '2026-03-16T16:48:07.770426000',\n", - " '2026-03-16T16:48:08.771087000', '2026-03-16T16:48:09.771748000',\n", - " '2026-03-16T16:48:10.772409000', '2026-03-16T16:48:11.773070000',\n", - " '2026-03-16T16:48:12.773731000', '2026-03-16T16:48:13.774392000',\n", - " '2026-03-16T16:48:14.775053000', '2026-03-16T16:48:15.775714000',\n", - " '2026-03-16T16:48:16.776375000', '2026-03-16T16:48:17.777036000',\n", - " '2026-03-16T16:48:18.777697000', '2026-03-16T16:48:19.760382000'],\n", - " dtype='datetime64[ns]') line(azimuth_time)int32dask.array<chunksize=(26,), meta=np.ndarray>
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- line
\n", + "
VV_conditions_doppler_centroid_fine_dce_azimuth_start_time(VV_conditions_doppler_centroid_azimuth_time)booldask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<b1', 'long_name': 'false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold'}
- dtype :
- <b1
- long_name :
- false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -11167,14 +10541,14 @@ " \n", "
\n", @@ -11199,15 +10573,15 @@ "\n", " \n", " \n", "Bytes \n", - "104 B \n", - "104 B \n", + "27 B \n", + "27 B \n", "\n", " \n", "Shape \n", - "(26,) \n", - "(26,) \n", + "(27,) \n", + "(27,) \n", "\n", " \n", "Dask graph \n", @@ -11182,7 +10556,7 @@ "\n", " \n", " \n", "Data type \n", - "int32 numpy.ndarray \n", + "bool numpy.ndarray \n", "\n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 26 \n", - "1 \n", + "27 \n", + "1 \n", "\n", " pixel(azimuth_time, ground_range)int32dask.array<chunksize=(26, 671), meta=np.ndarray>\n", + "
VV_conditions_doppler_centroid_fine_dce_azimuth_stop_time(VV_conditions_doppler_centroid_azimuth_time)booldask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<b1', 'long_name': 'false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold'}
- dtype :
- <b1
- long_name :
- false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -11222,14 +10596,14 @@ " \n", "
\n", @@ -11254,15 +10628,15 @@ "\n", " \n", " \n", "Bytes \n", - "68.15 kiB \n", - "68.15 kiB \n", + "27 B \n", + "27 B \n", "\n", " \n", "Shape \n", - "(26, 671) \n", - "(26, 671) \n", + "(27,) \n", + "(27,) \n", "\n", " \n", "Dask graph \n", @@ -11237,7 +10611,7 @@ "\n", " \n", " \n", "Data type \n", - "int32 numpy.ndarray \n", + "bool numpy.ndarray \n", "\n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 671 \n", - "26 \n", + "27 \n", + "1 \n", "\n", "
noise_range_lut(azimuth_time, ground_range)float32dask.array<chunksize=(26, 671), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'line', 'pixel', 'ground_range'], 'dimensions': ['azimuth_time', 'ground_range'], 'dtype': '<f4', 'long_name': 'range thermal noise correction vector power values (this array contains the count attribute number of floating point values)'}
- dtype :
- <f4
- long_name :
- range thermal noise correction vector power values (this array contains the count attribute number of floating point values)
\n", + "
VV_conditions_doppler_centroid_geometry_dc_polynomial(VV_conditions_doppler_centroid_azimuth_time, VV_conditions_doppler_centroid_degree)float32dask.array<chunksize=(27, 3), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'degree'], 'dimensions': ['azimuth_time', 'degree'], 'dtype': '<f4', 'long_name': 'doppler centroid estimated from orbit, expressed as polynomial with 5 coefficients: doppler centroid = d0 + d1(tsr-t0) + d2(tsr-t0)^2 + d3(tsr-t0)^3 + d4(tsr-t0)^4, where tsr = 2-way slant range time'}
- dtype :
- <f4
- long_name :
- doppler centroid estimated from orbit, expressed as polynomial with 5 coefficients: doppler centroid = d0 + d1(tsr-t0) + d2(tsr-t0)^2 + d3(tsr-t0)^3 + d4(tsr-t0)^4, where tsr = 2-way slant range time
\n", "
\n", " \n", + "\n", " \n", "\n", @@ -11277,14 +10651,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "68.15 kiB \n", - "68.15 kiB \n", + "324 B \n", + "324 B \n", "\n", " \n", "Shape \n", - "(26, 671) \n", - "(26, 671) \n", + "(27, 3) \n", + "(27, 3) \n", "\n", " Dask graph \n", @@ -11298,6 +10672,61 @@ "\n", + " \n", + "\n", + "\n", + " \n", + " \n", + "\n", + " \n", + "\n", + " \n", + " \n", + " \n", + "\n", + " \n", + " \n", + "\n", + " \n", + " 3 \n", + "27 \n", + " VV_conditions_doppler_centroid_t0(VV_conditions_doppler_centroid_azimuth_time)float64dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'two-way slant range time origin for doppler centroid estimate', 'units': 's'}
- dtype :
- <f8
- long_name :
- two-way slant range time origin for doppler centroid estimate
- units :
- s
\n", + "
\n", + " \n", - "\n", + " \n", + "\n", + " \n", + "
\n", + "\n", + " \n", + " \n", + " \n", + " \n", + "\n", + " Array \n", + "Chunk \n", + "\n", + " \n", + " \n", + "Bytes \n", + "216 B \n", + "216 B \n", + "\n", + " \n", + "Shape \n", + "(27,) \n", + "(27,) \n", + "\n", + " \n", + "Dask graph \n", + "1 chunks in 2 graph layers \n", + "\n", + " \n", + " \n", + "Data type \n", + "float64 numpy.ndarray \n", + "\n", " \n", "\n", "\n", " \n", @@ -11309,908 +10738,1001 @@ " \n", "\n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 671 \n", - "26 \n", + "27 \n", + "1 \n", "
- other_metadata :
- {'azimuth_steering_rate': 1.590368784, 'downlink_information': {'azimuth_time': '2026-03-16T16:47:50.757728', 'baq_block_length': 256, 'decimation_filter_bandwidth': 56590000.0, 'ecc_number': 8, 'filter_length': 36, 'first_line_sensing_time': '2026-03-16T16:42:01.593452', 'instrument_config_id': 5, 'last_line_sensing_time': '2026-03-16T16:42:32.143255', 'mean_bit_rate': 0.2662843699455962, 'num_err_azimuth_beam_address': 0, 'num_err_baq_block_length': 0, 'num_err_baq_mode': 0, 'num_err_cal_mode': 0, 'num_err_cal_type': 0, 'num_err_calibration_beam_address': 0, 'num_err_data_take_id': 0, 'num_err_ecc_number': 0, 'num_err_elevation_beam_address': 0, 'num_err_instrument_config_id': 0, 'num_err_number_of_quads': 0, 'num_err_packet_count': 0, 'num_err_polarisation': 0, 'num_err_pri': 0, 'num_err_pri_count': 0, 'num_err_range_decimation': 0, 'num_err_rank': 0, 'num_err_rx_channel_id': 0, 'num_err_rx_gain': 0, 'num_err_sas_test_mode': 0, 'num_err_signal_type': 0, 'num_err_ssb_error_flag': 0, 'num_err_swap_flag': 0, 'num_err_swath_number': 0, 'num_err_swl': 0, 'num_err_swst': 0, 'num_err_sync_marker': 0, 'num_err_temp_comp': 0, 'num_err_test_mode': 0, 'num_err_tx_pulse_number': 0, 'num_err_tx_pulse_start_frequency': 0, 'num_err_tx_ramp_rate': 0, 'num_isp_header_errors': 0, 'pointing_status': {'azimuth_time': '2026-03-16T16:42:01.112039'}, 'prf': 1717.128973878037, 'pri': 0.0005823674372819869, 'rank': 9, 'rx_channel_id': 1, 'rx_gain': -4.0, 'sampling_frequency_after_decimation': 64345238.12571429, 'swath': 'IW1', 'swath_number': 10, 'swl_azimuth_time': ['2026-03-16T16:47:51.903772', '2026-03-16T16:48:00.178598', '2026-03-16T16:47:52.723896', '2026-03-16T16:48:00.998722', '2026-03-16T16:47:53.800376', '2026-03-16T16:48:02.075218'], 'swl_value': ['3.725084179549267e-04', '3.722952819698287e-04', '4.438024049701879e-04', '4.435359849888155e-04', '4.234479183933346e-04', '4.231282144156876e-04'], 'swst_azimuth_time': ['2026-03-16T16:47:51.903772', 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1.007580041885376, 'iq_gain_lower_bound': 0.9988974928855896, 'iq_gain_upper_bound': 1.001101970672607, 'iq_quadrature_departure': 0.09657777845859528, 'iq_quadrature_departure_lower_bound': -0.8294360041618347, 'iq_quadrature_departure_upper_bound': 1.022565960884094, 'iq_quadrature_departure_used_for_correction': 0.05972424894571304, 'q_bias': 0.1909915953874588, 'q_bias_lower_bound': -0.007619955111294985, 'q_bias_upper_bound': 0.007619955111294985, 'q_bias_used_for_correction': 0.09456537663936615}, 'reference_replica': {'azimuth_time': '2026-03-16T16:47:51.903759', 'chirp_source': 'Nominal', 'pg_source': 'Extracted', 'time_delay': 4.291048e-07}, 'rfi': {'radio_frequency_interference': {'rfi_burst_report': {'azimuth_time': ['2026-03-16T16:47:50.757728', '2026-03-16T16:47:53.518340', '2026-03-16T16:47:56.276897', '2026-03-16T16:47:59.031342', '2026-03-16T16:48:01.791954', '2026-03-16T16:48:04.548455', '2026-03-16T16:48:07.307012', '2026-03-16T16:48:10.063513', '2026-03-16T16:48:12.822069', '2026-03-16T16:48:15.578570', '2026-03-16T16:48:18.337127', '2026-03-16T16:47:51.705339', '2026-03-16T16:47:54.463896', '2026-03-16T16:47:57.222452', '2026-03-16T16:47:59.983064', '2026-03-16T16:48:02.741621', '2026-03-16T16:48:05.500177', '2026-03-16T16:48:08.256678', '2026-03-16T16:48:11.011124', '2026-03-16T16:48:13.765569', '2026-03-16T16:48:16.526181', '2026-03-16T16:48:19.280627', '2026-03-16T16:47:52.669395', '2026-03-16T16:47:55.425896', '2026-03-16T16:47:58.182397', '2026-03-16T16:48:00.938898', '2026-03-16T16:48:03.695399', '2026-03-16T16:48:06.453956', '2026-03-16T16:48:09.216623', '2026-03-16T16:48:11.966958', '2026-03-16T16:48:14.725514', '2026-03-16T16:48:17.488182', '2026-03-16T16:48:20.242627'], 'frequency_domain': {'max_percentage_affected_bw': [1.779343, 1.556925, 1.556925, 1.556925, 1.556925, 2.001761, 1.556925, 1.334507, 1.334507, 1.112089, 1.334507, 1.765761, 5.738722, 4.419001, 1.549639, 6.400883, 9.049524, 1.765761, 1.545041, 1.324321, 1.545041, 1.765761, 2.127193, 2.565789, 2.560307, 1.716009, 2.143641, 2.357456, 1.929825, 1.502193, 2.143641, 3.201754, 2.560307], 'max_percentage_bw_affected_persistent_rfi': [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], 'num_sub_blocks': [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3], 'percentage_affected_lines': [48.47839, 54.44114, 50.395, 38.0306, 38.16402, 41.27047, 33.98818, 23.24022, 22.43002, 21.13437, 19.9457, 35.06824, 32.37559, 30.55374, 38.38581, 25.57141, 34.89888, 42.50509, 41.70071, 33.23726, 31.23523, 34.38243, 62.29629, 66.96047, 47.63647, 39.87685, 39.87372, 24.71303, 12.85819, 16.95723, 32.61474, 72.37092, 92.04929], 'percentage_blocks_persistent_rfi': [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], 'sub_block_size': [537, 537, 537, 537, 537, 537, 537, 537, 537, 537, 537, 583, 583, 583, 583, 583, 583, 583, 583, 583, 583, 583, 537, 537, 537, 537, 537, 537, 537, 537, 537, 537, 537]}, 'in_band_out_band_power_ratio': [6.040483, 5.885845, 5.770032, 5.33534, 5.739498, 6.480892, 6.939073, 6.906009, 7.050421, 6.340687, 5.752688, 3.835001, 3.319923, 2.069375, 1.427945, 1.739582, 2.307185, 4.2729, 5.899227, 5.842138, 5.231568, 4.665253, 1.280412, 1.344367, 2.986798, 4.159164, 4.051703, 4.874695, 5.00666, 4.071457, 2.378007, 1.351661, 1.04332], 'time_domain': {'avg_percentage_affected_samples': [0.03072282, 0.02541306, 0.02900477, 0.02216469, 0.02230422, 0.0327036, 0.02128726, 0.0310719, 0.03200946, 0.02720804, 0.03276924, 0.02132807, 0.03892438, 0.02845037, 0.02325107, 0.1596922, 0.374319, 0.02000132, 0.01872421, 0.03915716, 0.02229234, 0.03514876, 0.03153514, 0.02917108, 0.03309658, 0.0319356, 0.02673698, 0.04061222, 0.02720815, 0.04185823, 0.06881663, 0.02263948, 0.02056231], 'max_percentage_affected_samples': [0.4939305, 1.025534, 0.9418166, 0.4897447, 0.5776476, 1.075764, 0.2637087, 0.1632482, 0.3223106, 0.1339473, 0.2469653, 0.5792304, 3.814646, 0.7405875, 0.2606537, 3.971866, 12.42036, 0.3764998, 0.2482416, 0.3020273, 0.3227141, 0.8895324, 0.6812677, 1.175817, 1.221235, 0.6055713, 0.6711748, 1.145539, 0.6308034, 3.174202, 4.784013, 0.2422285, 0.3381106], 'percentage_affected_lines': [22.35628, 40.88006, 53.15826, 36.55075, 43.86089, 34.13769, 10.78779, 1.84528, 2.413059, 1.84528, 2.484031, 56.26615, 66.02068, 72.15762, 41.79586, 16.21447, 21.44703, 21.83463, 10.07752, 1.808785, 8.65633, 14.21189, 71.20567, 65.60284, 77.0922, 66.52482, 55.17731, 34.18439, 23.5461, 40.92199, 56.80851, 15.46099, 9.503547]}}, 'rfi_detection_from_noise_report': {'max_fisher_z': [29.50416, 4.590335, 27.0361, 9.515205, 6.524429, 8.818636, 4.148534, 3.308747, 3.465118, 10.62549, 5.714411, 14.31397, 3.102887, 3.137011, 4.052643, 5.175268, 17.6979, 2.843202], 'max_kl_divergence': [259975.0, 4.807519, 279972.0, 19.79907, 9.58111, 17.15115, 3.910321, 2.868378, 2.873281, 10023.04, 7.236189, 149995.0, 2.383656, 2.435508, 3.756703, 6.133147, 289971.0, 1.960016], 'max_rfi_psd': [42.35976, 0.0, 32.62078, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 21.42714, 0.0, 0.0, 0.0, 0.0, 27.95378, 0.0], 'noise_sensing_time': ['2026-03-16T16:47:52.722175', '2026-03-16T16:47:58.238731', '2026-03-16T16:48:03.755271', '2026-03-16T16:48:09.271827', '2026-03-16T16:48:14.788383', '2026-03-16T16:48:20.304939', '2026-03-16T16:47:53.799354', '2026-03-16T16:47:59.315910', '2026-03-16T16:48:04.832466', '2026-03-16T16:48:10.349021', '2026-03-16T16:48:15.865562', '2026-03-16T16:48:21.382118', '2026-03-16T16:47:54.648155', '2026-03-16T16:48:00.164710', '2026-03-16T16:48:05.681266', '2026-03-16T16:48:11.197822', '2026-03-16T16:48:16.714378', '2026-03-16T16:48:22.230934'], 'rfi_detected': ['true', 'false', 'true', 'false', 'false', 'false', 'false', 'false', 'false', 'false', 'false', 'true', 'false', 'false', 'false', 'false', 'true', 'false']}}}, 'swath_merging': {'swath_merge_list': [{'swath': 'IW1', 'swath_bounds_list': [{'azimuth_time': '2026-03-16T16:47:54.761834', 'first_azimuth_line': 0, 'first_range_sample': 0, 'last_azimuth_line': 16688, 'last_range_sample': 8871}]}, {'swath': 'IW2', 'swath_bounds_list': [{'azimuth_time': '2026-03-16T16:47:54.761834', 'first_azimuth_line': 0, 'first_range_sample': 8872, 'last_azimuth_line': 16688, 'last_range_sample': 17677}]}, {'swath': 'IW3', 'swath_bounds_list': [{'azimuth_time': '2026-03-16T16:47:54.761834', 'first_azimuth_line': 0, 'first_range_sample': 17678, 'last_azimuth_line': 16688, 'last_range_sample': 26641}]}]}, 'swath_timing': {'burst_list': {}, 'lines_per_burst': 0, 'samples_per_burst': 0}, 'timeliness_category': 'NRT-3h', 'title': 'S01SIWGRD'}
- processing_history :
- {'Level-0 Product': [{'facility': 'Unknown', 'inputs': [], 'outputs': ['Downlinked Stream'], 'processor': 'Unknown', 'time': '2026-03-16T16:44:59.039521Z', 'version': 'Unknown'}, {'facility': 'Unknown', 'inputs': [], 'outputs': ['Downlinked Stream'], 'processor': 'Unknown', 'time': '2026-03-16T16:45:26.324421Z', 'version': 'Unknown'}, {'facility': 'Unknown', 'inputs': ['S-1 Core PDGS S-1 Level-0 Product Format Specifications S1PD.SP.00110.ASTR', 'Sentinel-1 SAR Space Packet Protocol Data Unit S1-IF-ASD-PL-0007', 'Downlinked Stream'], 'outputs': ['Unknown'], 'processor': 'Unknown', 'time': '2026-03-16T17:07:12.306670Z', 'version': 'Unknown'}, {'facility': 'Unknown', 'inputs': ['S-1 Core PDGS S-1 Level-0 Product Format Specifications S1PD.SP.00110.ASTR', 'Sentinel-1 SAR Space Packet Protocol Data Unit S1-IF-ASD-PL-0007', 'Downlinked Stream'], 'outputs': ['Unknown'], 'processor': 'Unknown', 'time': '2026-03-16T17:12:02.055507Z', 'version': 'Unknown'}, {'facility': 'ESA-S1C-PS', 'inputs': ['S-1 Core PDGS S-1 Level-0 Product Format Specifications S1PD.SP.00110.ASTR', 'Sentinel-1 SAR Space Packet Protocol Data Unit S1-IF-ASD-PL-0007', 'Unknown', 'Unknown'], 'outputs': ['/data_pwa/cps/wd/eops-cps-pnode-s1-l1-0/IW_RAW__0_GRDH_1_4_03_IW_RAW__0_GRDH_1_4_03_301675188/S1C_IW_RAW__0SDV_20260316T164751_20260316T164823_006792_00DBA6_DA02.SAFE'], 'processor': '', 'time': '2026-03-16T17:15:28.685180Z', 'version': ''}], 'Level-1 Intermediate SLC Product': [{'adfs': ['/data_pwa/cps/wd/eops-cps-pnode-s1-l1-0/IW_RAW__0_GRDH_1_4_03_IW_RAW__0_GRDH_1_4_03_301675188/S1C_AUX_PP1_V20250427T000000_G20260203T152141.SAFE', '/data_pwa/cps/wd/eops-cps-pnode-s1-l1-0/IW_RAW__0_GRDH_1_4_03_IW_RAW__0_GRDH_1_4_03_301675188/S1C_AUX_CAL_V20250427T000000_G20260212T132118.SAFE', '/data_pwa/cps/wd/eops-cps-pnode-s1-l1-0/IW_RAW__0_GRDH_1_4_03_IW_RAW__0_GRDH_1_4_03_301675188/S1C_AUX_INS_V20250224T000000_G20251015T082332.SAFE', '/data_pwa/cps/wd/eops-cps-pnode-s1-l1-0/IW_RAW__0_GRDH_1_4_03_IW_RAW__0_GRDH_1_4_03_301675188/S1C_OPER_AUX_PREORB_OPOD_20260316T170705_V20260316T163717_20260316T231217.EOF'], 'facility': 'ESA-S1C-PS', 'inputs': ['/data_pwa/cps/wd/eops-cps-pnode-s1-l1-0/IW_RAW__0_GRDH_1_4_03_IW_RAW__0_GRDH_1_4_03_301675188/S1C_IW_RAW__0ADV_20260316T164201_20260316T165701_006792_00DBA6_2189.SAFE', '/data_pwa/cps/wd/eops-cps-pnode-s1-l1-0/IW_RAW__0_GRDH_1_4_03_IW_RAW__0_GRDH_1_4_03_301675188/S1C_IW_RAW__0CDV_20260316T164201_20260316T165701_006792_00DBA6_9E95.SAFE', '/data_pwa/cps/wd/eops-cps-pnode-s1-l1-0/IW_RAW__0_GRDH_1_4_03_IW_RAW__0_GRDH_1_4_03_301675188/S1C_IW_RAW__0NDV_20260316T164201_20260316T165701_006792_00DBA6_97E5.SAFE', '/data_pwa/cps/wd/eops-cps-pnode-s1-l1-0/IW_RAW__0_GRDH_1_4_03_IW_RAW__0_GRDH_1_4_03_301675188/S1C_IW_RAW__0SDV_20260316T164751_20260316T164823_006792_00DBA6_DA02.SAFE', 'Sentinel-1 Product Definition (S1-RS-MDA-52-7440) release 2/7', 'Sentinel-1 Product Specification (S1-RS-MDA-52-7441) release 3/14'], 'outputs': ['S1C_IW_SL1__1_DV_20260316T164751_20260316T164824_006792_00DBA6_1763.SAFE'], 'processor': 'Sentinel-1 IPF', 'time': '2026-03-16T17:55:39.000000Z', 'version': '004.03'}], 'Level-1 Product': [{'facility': 'ESA-S1C-PS', 'inputs': ['S1C_IW_SL1__1_DV_20260316T164751_20260316T164824_006792_00DBA6_1763.SAFE'], 'outputs': ['S1C_IW_GRDH_1SDV_20260316T164754_20260316T164819_006792_00DBA6_8EA0.SAFE'], 'processor': 'Sentinel-1 IPF', 'time': '2026-03-16T17:57:14.000000Z', 'version': '004.03'}, {'facility': 'CS-SopraSteria', 'inputs': ['S1C_IW_GRDH_1SDV_20260316T164754_20260316T164819_006792_00DBA6_8EA0.SAFE'], 'outputs': ['S1C_IW_GRDH_1SDV_20260316T164754_20260316T164819_006792_00DBA6_8EA0.zarr.zarr'], 'processor': 'EOPF-CPM', 'time': '2026-03-16T18:51:01.944012Z', 'version': '2.6.2'}]}
- stac_discovery :
- {'assets': {}, 'bbox': [18.688345, 39.213028, 15.261218, 41.126934], 'detectionPerformed': 'true', 'geometry': {'coordinates': [[[15.261218, 40.715069], [18.376741, 41.126934], [18.688345, 39.626194], [15.640784, 39.213028], [15.261218, 40.715069]]], 'type': 'Polygon'}, 'id': 'S01SIWGRD_20260316T164754_0024_C146_TF31', 'links': [{'href': './.zattrs.json', 'rel': 'self', 'type': 'application/json'}], 'properties': {'constellation': 'sentinel-1', 'created': '2026-03-16T17:57:14.000000Z', 'datetime': 'None', 'end_datetime': '2026-03-16T16:48:19.760381Z', 'instruments': ['sar'], 'platform': 'sentinel-1c', 'processing:software': {'Sentinel-1 IPF': '004.03'}, 'processing:version': '004.00', 'product:timeliness': 'PT3H', 'product:timeliness_category': 'NRT-3h', 'product:type': 'S01SIWGRD', 'sar:center_frequency': 5405000454.33435, 'sar:frequency_band': 'C', 'sar:instrument_mode': 'IW', 'sar:pixel_spacing_azimuth': 10.0, 'sar:pixel_spacing_range': 10.0, 'sat:absolute_orbit': 6792, 'sat:anx_datetime': '2026-03-16T16:37:16.668595', 'sat:orbit_state': 'ascending', 'sat:platform_international_designator': '2024-235A', 'sat:relative_orbit': 146, 'start_datetime': '2026-03-16T16:47:54.761834Z', 'view:incidence_angle': 39.13511618906348}, 'stac_extensions': ['https://stac-extensions.github.io/eopf/v1.2.0/schema.json', 'https://stac-extensions.github.io/product/v0.1.0/schema.json', 'https://stac-extensions.github.io/eo/v1.1.0/schema.json', 'https://stac-extensions.github.io/sat/v1.1.0/schema.json', 'https://stac-extensions.github.io/view/v1.0.0/schema.json', 'https://stac-extensions.github.io/scientific/v1.0.0/schema.json', 'https://stac-extensions.github.io/processing/v1.2.0/schema.json', 'https://stac-extensions.github.io/sar/v1.2.0/schema.json'], 'stac_version': '1.1.0', 'thermalNoiseCorrectionPerformed': 'false', 'type': 'Feature'}
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- other_metadata :
- {'eopf_category': 'eocontainer', 'title': 'S01SIWGRD'}
- stac_discovery :
- {'assets': {'S01SIWGRD_20260316T164754_0025_C039_8EA0_00DBA6_VH': {'href': 'S01SIWGRD_20260316T164754_0025_C039_8EA0_00DBA6_VH'}, 'S01SIWGRD_20260316T164754_0025_C039_8EA0_00DBA6_VV': {'href': 'S01SIWGRD_20260316T164754_0025_C039_8EA0_00DBA6_VV'}}, 'bbox': [18.688345, 39.213028, 15.261218, 41.126934], 'geometry': {'coordinates': [[[15.261218, 40.715069], [18.376741, 41.126934], [18.688345, 39.626194], [15.640784, 39.213028], [15.261218, 40.715069]]], 'type': 'Polygon'}, 'id': 'SAR Standard L1 Product', 'links': [{'href': './.zattrs.json', 'rel': 'self', 'type': 'application/json'}], 'properties': {'constellation': 'sentinel-1', 'created': '2026-03-16T17:57:14.000000Z', 'datetime': '2026-03-16T16:48:07.261108Z', 'end_datetime': '2026-03-16T16:48:19.760381Z', 'eopf:datatake_id': '56230', 'instruments': ['sar'], 'platform': 'sentinel-1c', 'processing:lineage': 'systematic', 'processing:software': {'Sentinel-1 IPF': '004.03'}, 'product:timeliness': 'PT3H', 'product:timeliness_category': 'NRT-3h', 'product:type': 'S01SIWGRD', 'provider': [{'name': 'S1C-PS', 'roles': ['processor']}, {'name': 'ESA', 'roles': ['producer']}], 'sar:frequency_band': 'C', 'sar:instrument_mode': 'IW', 'sar:polarizations': ['VV', 'VH'], 'sar:product_type': 'GRD', 'sat:absolute_orbit': 6792, 'sat:anx_datetime': '2026-03-16T16:37:16.668595', 'sat:orbit_state': 'ascending', 'sat:platform_international_designator': '2024-235A', 'sat:relative_orbit': 146, 'start_datetime': '2026-03-16T16:47:54.761834Z'}, 'stac_extensions': ['https://stac-extensions.github.io/eopf/v1.2.0/schema.json', 'https://stac-extensions.github.io/product/v0.1.0/schema.json', 'https://stac-extensions.github.io/eo/v1.1.0/schema.json', 'https://stac-extensions.github.io/sat/v1.1.0/schema.json', 'https://stac-extensions.github.io/view/v1.0.0/schema.json', 'https://stac-extensions.github.io/scientific/v1.0.0/schema.json', 'https://stac-extensions.github.io/processing/v1.2.0/schema.json', 'https://stac-extensions.github.io/sar/v1.2.0/schema.json'], 'stac_version': '1.1.0', 'type': 'Feature'}
<xarray.DatasetView> Size: 322kB\n", - "Dimensions: (azimuth_time: 27, count: 730)\n", - "Coordinates:\n", - " * azimuth_time (azimuth_time) datetime64[ns] 216B 2026-03-16T16:47:...\n", - " * count (count) int64 6kB 0 1 2 3 4 5 ... 725 726 727 728 729\n", - "Data variables:\n", - " elevation_angle (azimuth_time, count) float32 79kB dask.array<chunksize=(27, 730), meta=np.ndarray>\n", - " incidence_angle (azimuth_time, count) float32 79kB dask.array<chunksize=(27, 730), meta=np.ndarray>\n", - " roll (azimuth_time) float64 216B dask.array<chunksize=(27,), meta=np.ndarray>\n", - " slant_range_time_ap (azimuth_time, count) float64 158kB dask.array<chunksize=(27, 730), meta=np.ndarray>\n", - " swath (azimuth_time) <U3 324B dask.array<chunksize=(27,), meta=np.ndarray>\n", - " terrain_height (azimuth_time) float64 216B dask.array<chunksize=(27,), meta=np.ndarray>
array(['2026-03-16T16:47:55.425896000', '2026-03-16T16:47:56.276897000',\n", - " '2026-03-16T16:47:57.222452000', '2026-03-16T16:47:58.182397000',\n", + "<xarray.Dataset> Size: 890MB\n", + "Dimensions: (\n", + " VH/conditions/antenna_pattern/azimuth_time: 27,\n", + " VH/conditions/antenna_pattern/count: 730,\n", + " VH/conditions/attitude/azimuth_time: 25,\n", + " VH/conditions/doppler_centroid/azimuth_time: 27,\n", + " VH/conditions/doppler_centroid/degree: 3,\n", + " ...\n", + " VH/quality/calibration/azimuth_time: 27,\n", + " VH/quality/calibration/ground_range: 668,\n", + " VH/quality/azimuth/swath: 3,\n", + " VH/quality/azimuth/azimuth_time: 1688,\n", + " VH/quality/range/azimuth_time: 26,\n", + " VH/quality/range/ground_range: 671)\n", + "Coordinates: (12/16)\n", + " * VH/conditions/antenna_pattern/azimuth_time (VH/conditions/antenna_pattern/azimuth_time) datetime64[ns] 216B ...\n", + " * VH/conditions/antenna_pattern/count (VH/conditions/antenna_pattern/count) int64 6kB ...\n", + " * VH/conditions/attitude/azimuth_time (VH/conditions/attitude/azimuth_time) datetime64[ns] 200B ...\n", + " * VH/conditions/doppler_centroid/azimuth_time (VH/conditions/doppler_centroid/azimuth_time) datetime64[ns] 216B ...\n", + " * VH/conditions/doppler_centroid/degree (VH/conditions/doppler_centroid/degree) int64 24B ...\n", + " * VH/conditions/gcp/azimuth_time (VH/conditions/gcp/azimuth_time) datetime64[ns] 80B ...\n", + " ... ...\n", + " * VH/measurements/ground_range (VH/measurements/ground_range) float64 213kB ...\n", + " * VH/quality/calibration/azimuth_time (VH/quality/calibration/azimuth_time) datetime64[ns] 216B ...\n", + " * VH/quality/calibration/ground_range (VH/quality/calibration/ground_range) float64 5kB ...\n", + " * VH/quality/azimuth/swath (VH/quality/azimuth/swath) <U3 36B ...\n", + " * VH/quality/range/azimuth_time (VH/quality/range/azimuth_time) datetime64[ns] 208B ...\n", + " * VH/quality/range/ground_range (VH/quality/range/ground_range) float64 5kB ...\n", + "Dimensions without coordinates: VH/quality/azimuth/azimuth_time\n", + "Data variables: (12/39)\n", + " VH/conditions/antenna_pattern/elevation_angle (VH/conditions/antenna_pattern/azimuth_time, VH/conditions/antenna_pattern/count) float32 79kB dask.array<chunksize=(27, 730), meta=np.ndarray>\n", + " VH/conditions/antenna_pattern/incidence_angle (VH/conditions/antenna_pattern/azimuth_time, VH/conditions/antenna_pattern/count) float32 79kB dask.array<chunksize=(27, 730), meta=np.ndarray>\n", + " VH/conditions/antenna_pattern/roll (VH/conditions/antenna_pattern/azimuth_time) float64 216B dask.array<chunksize=(27,), meta=np.ndarray>\n", + " VH/conditions/antenna_pattern/slant_range_time_ap (VH/conditions/antenna_pattern/azimuth_time, VH/conditions/antenna_pattern/count) float64 158kB dask.array<chunksize=(27, 730), meta=np.ndarray>\n", + " VH/conditions/antenna_pattern/swath (VH/conditions/antenna_pattern/azimuth_time) <U3 324B dask.array<chunksize=(27,), meta=np.ndarray>\n", + " VH/conditions/antenna_pattern/terrain_height (VH/conditions/antenna_pattern/azimuth_time) float64 216B dask.array<chunksize=(27,), meta=np.ndarray>\n", + " ... ...\n", + " VH/quality/calibration/beta_nought (VH/quality/calibration/azimuth_time, VH/quality/calibration/ground_range) float32 72kB dask.array<chunksize=(27, 668), meta=np.ndarray>\n", + " VH/quality/calibration/dn (VH/quality/calibration/azimuth_time, VH/quality/calibration/ground_range) float32 72kB dask.array<chunksize=(27, 668), meta=np.ndarray>\n", + " VH/quality/calibration/gamma (VH/quality/calibration/azimuth_time, VH/quality/calibration/ground_range) float32 72kB dask.array<chunksize=(27, 668), meta=np.ndarray>\n", + " VH/quality/calibration/sigma_nought (VH/quality/calibration/azimuth_time, VH/quality/calibration/ground_range) float32 72kB dask.array<chunksize=(27, 668), meta=np.ndarray>\n", + " VH/quality/azimuth/noise_azimuth_lut (VH/quality/azimuth/swath, VH/quality/azimuth/azimuth_time) float32 20kB dask.array<chunksize=(3, 1688), meta=np.ndarray>\n", + " VH/quality/range/noise_range_lut (VH/quality/range/azimuth_time, VH/quality/range/ground_range) float32 70kB dask.array<chunksize=(26, 671), meta=np.ndarray>\n", + "Attributes: (2)xarray.Dataset
- VH/conditions/antenna_pattern/azimuth_time: 27
- VH/conditions/antenna_pattern/count: 730
- VH/conditions/attitude/azimuth_time: 25
- VH/conditions/doppler_centroid/azimuth_time: 27
- VH/conditions/doppler_centroid/degree: 3
- VH/conditions/gcp/azimuth_time: 10
- VH/conditions/gcp/ground_range: 21
- VH/conditions/orbit/azimuth_time: 17
- VH/conditions/orbit/axis: 3
- VH/measurements/azimuth_time: 16689
- VH/measurements/ground_range: 26642
- VH/quality/calibration/azimuth_time: 27
- VH/quality/calibration/ground_range: 668
- VH/quality/azimuth/swath: 3
- VH/quality/azimuth/azimuth_time: 1688
- VH/quality/range/azimuth_time: 26
- VH/quality/range/ground_range: 671
VH/conditions/antenna_pattern/azimuth_time(VH/conditions/antenna_pattern/azimuth_time)datetime64[ns]2026-03-16T16:47:55.425896 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- zero doppler azimuth time of antenna pattern measurement
array(['2026-03-16T16:47:55.425896000', '2026-03-16T16:47:56.276897000',\n", + " '2026-03-16T16:47:57.222452000', '2026-03-16T16:47:58.182397000',\n", " '2026-03-16T16:47:59.031342000', '2026-03-16T16:47:59.983064000',\n", " '2026-03-16T16:48:00.938898000', '2026-03-16T16:48:01.791954000',\n", " '2026-03-16T16:48:02.741621000', '2026-03-16T16:48:03.695399000',\n", @@ -12677,7 +12330,77 @@ " '2026-03-16T16:48:13.765569000', '2026-03-16T16:48:14.725514000',\n", " '2026-03-16T16:48:15.578570000', '2026-03-16T16:48:16.526181000',\n", " '2026-03-16T16:48:17.488182000', '2026-03-16T16:48:18.337127000',\n", - " '2026-03-16T16:48:19.280627000'], dtype='datetime64[ns]') count(count)int640 1 2 3 4 5 ... 725 726 727 728 729array([ 0, 1, 2, ..., 727, 728, 729], shape=(730,))
elevation_angle(azimuth_time, count)float32dask.array<chunksize=(27, 730), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'count'], 'dimensions': ['azimuth_time', 'count'], 'dtype': '<f4', 'long_name': 'elevation angle to grid point', 'units': 'degrees'}
- dtype :
- <f4
- long_name :
- elevation angle to grid point
- units :
- degrees
\n", + " '2026-03-16T16:48:19.280627000'], dtype='datetime64[ns]')
VH/conditions/antenna_pattern/count(VH/conditions/antenna_pattern/count)int640 1 2 3 4 5 ... 725 726 727 728 729array([ 0, 1, 2, ..., 727, 728, 729], shape=(730,)) VH/conditions/attitude/azimuth_time(VH/conditions/attitude/azimuth_time)datetime64[ns]2026-03-16T16:47:55.000002 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- time stamp at which orbit state vectors apply
array(['2026-03-16T16:47:55.000002000', '2026-03-16T16:47:55.999998000',\n", + " '2026-03-16T16:47:57.000002000', '2026-03-16T16:47:57.999996000',\n", + " '2026-03-16T16:47:59.000000000', '2026-03-16T16:47:59.999995000',\n", + " '2026-03-16T16:48:01.000000000', '2026-03-16T16:48:01.999995000',\n", + " '2026-03-16T16:48:03.000000000', '2026-03-16T16:48:04.000003000',\n", + " '2026-03-16T16:48:04.999998000', '2026-03-16T16:48:06.000003000',\n", + " '2026-03-16T16:48:06.999997000', '2026-03-16T16:48:08.000002000',\n", + " '2026-03-16T16:48:08.999996000', '2026-03-16T16:48:10.000001000',\n", + " '2026-03-16T16:48:10.999996000', '2026-03-16T16:48:12.000000000',\n", + " '2026-03-16T16:48:12.999995000', '2026-03-16T16:48:14.000000000',\n", + " '2026-03-16T16:48:14.999994000', '2026-03-16T16:48:16.000000000',\n", + " '2026-03-16T16:48:17.000004000', '2026-03-16T16:48:17.999998000',\n", + " '2026-03-16T16:48:19.000004000'], dtype='datetime64[ns]') VH/conditions/doppler_centroid/azimuth_time(VH/conditions/doppler_centroid/azimuth_time)datetime64[ns]2026-03-16T16:47:56.021426 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- zero doppler azimuth time of terrain height measurement
array(['2026-03-16T16:47:56.021426000', '2026-03-16T16:47:56.022979000',\n", + " '2026-03-16T16:47:56.035054000', '2026-03-16T16:47:58.779703000',\n", + " '2026-03-16T16:47:58.781256000', '2026-03-16T16:47:58.793331000',\n", + " '2026-03-16T16:48:01.537980000', '2026-03-16T16:48:01.539533000',\n", + " '2026-03-16T16:48:01.551608000', '2026-03-16T16:48:04.296257000',\n", + " '2026-03-16T16:48:04.297810000', '2026-03-16T16:48:04.309885000',\n", + " '2026-03-16T16:48:07.054533000', '2026-03-16T16:48:07.056086000',\n", + " '2026-03-16T16:48:07.068161000', '2026-03-16T16:48:09.812810000',\n", + " '2026-03-16T16:48:09.814363000', '2026-03-16T16:48:09.826438000',\n", + " '2026-03-16T16:48:12.571087000', '2026-03-16T16:48:12.572640000',\n", + " '2026-03-16T16:48:12.584715000', '2026-03-16T16:48:15.329364000',\n", + " '2026-03-16T16:48:15.330917000', '2026-03-16T16:48:15.342992000',\n", + " '2026-03-16T16:48:18.087641000', '2026-03-16T16:48:18.089194000',\n", + " '2026-03-16T16:48:18.101269000'], dtype='datetime64[ns]') VH/conditions/doppler_centroid/degree(VH/conditions/doppler_centroid/degree)int642 1 0array([2, 1, 0]) VH/conditions/gcp/azimuth_time(VH/conditions/gcp/azimuth_time)datetime64[ns]2026-03-16T16:47:54.761834 ... 2...array(['2026-03-16T16:47:54.761834000', '2026-03-16T16:47:57.762318000',\n", + " '2026-03-16T16:48:00.762803000', '2026-03-16T16:48:03.763288000',\n", + " '2026-03-16T16:48:06.763773000', '2026-03-16T16:48:09.764257000',\n", + " '2026-03-16T16:48:12.764742000', '2026-03-16T16:48:15.765227000',\n", + " '2026-03-16T16:48:18.765712000', '2026-03-16T16:48:19.760381000'],\n", + " dtype='datetime64[ns]') VH/conditions/gcp/ground_range(VH/conditions/gcp/ground_range)float640.0 1.333e+04 ... 2.664e+05array([ 0., 13330., 26660., 39990., 53320., 66650., 79980., 93310.,\n", + " 106640., 119970., 133300., 146630., 159960., 173290., 186620., 199950.,\n", + " 213280., 226610., 239940., 253270., 266410.]) VH/conditions/orbit/azimuth_time(VH/conditions/orbit/azimuth_time)datetime64[ns]2026-03-16T16:46:46.681692 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- time stamp at which orbit state vectors apply
array(['2026-03-16T16:46:46.681692000', '2026-03-16T16:46:56.681692000',\n", + " '2026-03-16T16:47:06.681692000', '2026-03-16T16:47:16.681692000',\n", + " '2026-03-16T16:47:26.681692000', '2026-03-16T16:47:36.681693000',\n", + " '2026-03-16T16:47:46.681693000', '2026-03-16T16:47:56.681692000',\n", + " '2026-03-16T16:48:06.681692000', '2026-03-16T16:48:16.681692000',\n", + " '2026-03-16T16:48:26.681692000', '2026-03-16T16:48:36.681692000',\n", + " '2026-03-16T16:48:46.681692000', '2026-03-16T16:48:56.681693000',\n", + " '2026-03-16T16:49:06.681693000', '2026-03-16T16:49:16.681692000',\n", + " '2026-03-16T16:49:26.681692000'], dtype='datetime64[ns]') VH/conditions/orbit/axis(VH/conditions/orbit/axis)<U1'x' 'y' 'z'array(['x', 'y', 'z'], dtype='<U1') VH/measurements/azimuth_time(VH/measurements/azimuth_time)datetime64[ns]2026-03-16T16:47:54.761834 ... 2...array(['2026-03-16T16:47:54.761834000', '2026-03-16T16:47:54.763331000',\n", + " '2026-03-16T16:47:54.764829000', ..., '2026-03-16T16:48:19.757385000',\n", + " '2026-03-16T16:48:19.758883000', '2026-03-16T16:48:19.760381000'],\n", + " shape=(16689,), dtype='datetime64[ns]') VH/measurements/ground_range(VH/measurements/ground_range)float640.0 10.0 ... 2.664e+05 2.664e+05array([0.0000e+00, 1.0000e+01, 2.0000e+01, ..., 2.6639e+05, 2.6640e+05,\n", + " 2.6641e+05], shape=(26642,)) VH/quality/calibration/azimuth_time(VH/quality/calibration/azimuth_time)datetime64[ns]2026-03-16T16:47:54.761834 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- zero doppler azimuth time at which calibration vector applies
array(['2026-03-16T16:47:54.761834000', '2026-03-16T16:47:55.761834000',\n", + " '2026-03-16T16:47:56.761834000', '2026-03-16T16:47:57.761834000',\n", + " '2026-03-16T16:47:58.761834000', '2026-03-16T16:47:59.761834000',\n", + " '2026-03-16T16:48:00.761834000', '2026-03-16T16:48:01.761834000',\n", + " '2026-03-16T16:48:02.761834000', '2026-03-16T16:48:03.761834000',\n", + " '2026-03-16T16:48:04.761834000', '2026-03-16T16:48:05.761834000',\n", + " '2026-03-16T16:48:06.761834000', '2026-03-16T16:48:07.761834000',\n", + " '2026-03-16T16:48:08.761834000', '2026-03-16T16:48:09.761834000',\n", + " '2026-03-16T16:48:10.761834000', '2026-03-16T16:48:11.761834000',\n", + " '2026-03-16T16:48:12.761834000', '2026-03-16T16:48:13.761834000',\n", + " '2026-03-16T16:48:14.761834000', '2026-03-16T16:48:15.761834000',\n", + " '2026-03-16T16:48:16.761834000', '2026-03-16T16:48:17.761834000',\n", + " '2026-03-16T16:48:18.761834000', '2026-03-16T16:48:19.761834000',\n", + " '2026-03-16T16:48:20.761834000'], dtype='datetime64[ns]') VH/quality/calibration/ground_range(VH/quality/calibration/ground_range)float640.0 400.0 ... 2.664e+05 2.664e+05array([ 0., 400., 800., ..., 266000., 266400., 266410.], shape=(668,)) VH/quality/azimuth/swath(VH/quality/azimuth/swath)<U3'IW1' 'IW2' 'IW3'
- dimensions :
- ['swath']
- dtype :
- U3
- long_name :
- Swath
array(['IW1', 'IW2', 'IW3'], dtype='<U3') VH/quality/range/azimuth_time(VH/quality/range/azimuth_time)datetime64[ns]2026-03-16T16:47:54.761834 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- zero doppler azimuth time at which noise vector applies
array(['2026-03-16T16:47:54.761834000', '2026-03-16T16:47:55.762495000',\n", + " '2026-03-16T16:47:56.763156000', '2026-03-16T16:47:57.763817000',\n", + " '2026-03-16T16:47:58.764478000', '2026-03-16T16:47:59.765139000',\n", + " '2026-03-16T16:48:00.765800000', '2026-03-16T16:48:01.766461000',\n", + " '2026-03-16T16:48:02.767122000', '2026-03-16T16:48:03.767783000',\n", + " '2026-03-16T16:48:04.768444000', '2026-03-16T16:48:05.769104000',\n", + " '2026-03-16T16:48:06.769765000', '2026-03-16T16:48:07.770426000',\n", + " '2026-03-16T16:48:08.771087000', '2026-03-16T16:48:09.771748000',\n", + " '2026-03-16T16:48:10.772409000', '2026-03-16T16:48:11.773070000',\n", + " '2026-03-16T16:48:12.773731000', '2026-03-16T16:48:13.774392000',\n", + " '2026-03-16T16:48:14.775053000', '2026-03-16T16:48:15.775714000',\n", + " '2026-03-16T16:48:16.776375000', '2026-03-16T16:48:17.777036000',\n", + " '2026-03-16T16:48:18.777697000', '2026-03-16T16:48:19.760382000'],\n", + " dtype='datetime64[ns]') VH/quality/range/ground_range(VH/quality/range/ground_range)float640.0 400.0 ... 2.664e+05 2.664e+05array([ 0., 400., 800., ..., 265980., 266380., 266410.], shape=(671,))
VH/conditions/antenna_pattern/elevation_angle(VH/conditions/antenna_pattern/azimuth_time, VH/conditions/antenna_pattern/count)float32dask.array<chunksize=(27, 730), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'count'], 'dimensions': ['azimuth_time', 'count'], 'dtype': '<f4', 'long_name': 'elevation angle to grid point', 'units': 'degrees'}
- dtype :
- <f4
- long_name :
- elevation angle to grid point
- units :
- degrees
\n", "
\n", " \n", " \n", @@ -12727,12 +12450,12 @@ "
\n", "\n", " \n", - " 730 \n", - "27 \n", + "730 \n", + "27 \n", "\n", " \n", " \n", - " incidence_angle(azimuth_time, count)float32dask.array<chunksize=(27, 730), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'count'], 'dimensions': ['azimuth_time', 'count'], 'dtype': '<f4', 'long_name': 'incidence angle to grid point', 'units': 'degrees'}
- dtype :
- <f4
- long_name :
- incidence angle to grid point
- units :
- degrees
\n", + "
VH/conditions/antenna_pattern/incidence_angle(VH/conditions/antenna_pattern/azimuth_time, VH/conditions/antenna_pattern/count)float32dask.array<chunksize=(27, 730), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'count'], 'dimensions': ['azimuth_time', 'count'], 'dtype': '<f4', 'long_name': 'incidence angle to grid point', 'units': 'degrees'}
- dtype :
- <f4
- long_name :
- incidence angle to grid point
- units :
- degrees
\n", "
\n", " \n", " \n", @@ -12782,12 +12505,12 @@ "
\n", "\n", " \n", - " 730 \n", - "27 \n", + "730 \n", + "27 \n", "\n", " \n", " \n", - " roll(azimuth_time)float64dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'estimated roll angle for this antenna pattern', 'units': 'degrees'}
- dtype :
- <f8
- long_name :
- estimated roll angle for this antenna pattern
- units :
- degrees
\n", + "
VH/conditions/antenna_pattern/roll(VH/conditions/antenna_pattern/azimuth_time)float64dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'estimated roll angle for this antenna pattern', 'units': 'degrees'}
- dtype :
- <f8
- long_name :
- estimated roll angle for this antenna pattern
- units :
- degrees
\n", "
\n", " \n", " \n", @@ -12837,12 +12560,12 @@ "
\n", "\n", " \n", - " 27 \n", - "1 \n", + "27 \n", + "1 \n", "\n", " \n", " \n", - " slant_range_time_ap(azimuth_time, count)float64dask.array<chunksize=(27, 730), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'count'], 'dimensions': ['azimuth_time', 'count'], 'dtype': '<f8', 'long_name': 'two-way slant range time to sample', 'units': 's'}
- dtype :
- <f8
- long_name :
- two-way slant range time to sample
- units :
- s
\n", + "
VH/conditions/antenna_pattern/slant_range_time_ap(VH/conditions/antenna_pattern/azimuth_time, VH/conditions/antenna_pattern/count)float64dask.array<chunksize=(27, 730), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'count'], 'dimensions': ['azimuth_time', 'count'], 'dtype': '<f8', 'long_name': 'two-way slant range time to sample', 'units': 's'}
- dtype :
- <f8
- long_name :
- two-way slant range time to sample
- units :
- s
\n", "
\n", " \n", " \n", @@ -12892,12 +12615,12 @@ "
\n", "\n", " \n", - " 730 \n", - "27 \n", + "730 \n", + "27 \n", "\n", " \n", " \n", - " swath(azimuth_time)<U3dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': 'U3', 'long_name': 'Swath'}
- dtype :
- U3
- long_name :
- Swath
\n", + "
VH/conditions/antenna_pattern/swath(VH/conditions/antenna_pattern/azimuth_time)<U3dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': 'U3', 'long_name': 'Swath'}
- dtype :
- U3
- long_name :
- Swath
\n", "
\n", " \n", " \n", @@ -12947,12 +12670,12 @@ "
\n", "\n", " \n", - " 27 \n", - "1 \n", + "27 \n", + "1 \n", "\n", " \n", " \n", - " terrain_height(azimuth_time)float64dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'mean terrain height in range for this antenna pattern (in metres above the ellipsoid) for the given zero-doppler azimuth time', 'units': 'm'}
- dtype :
- <f8
- long_name :
- mean terrain height in range for this antenna pattern (in metres above the ellipsoid) for the given zero-doppler azimuth time
- units :
- m
\n", + "
VH/conditions/antenna_pattern/terrain_height(VH/conditions/antenna_pattern/azimuth_time)float64dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'mean terrain height in range for this antenna pattern (in metres above the ellipsoid) for the given zero-doppler azimuth time', 'units': 'm'}
- dtype :
- <f8
- long_name :
- mean terrain height in range for this antenna pattern (in metres above the ellipsoid) for the given zero-doppler azimuth time
- units :
- m
\n", "
\n", " \n", " \n", @@ -13002,481 +12725,287 @@ "
\n", "\n", " \n", - " 27 \n", - "1 \n", + "27 \n", + "1 \n", "\n", " \n", " \n", - "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - " \n", - " \n", - " \n", - "\n", - " \n", - " \n", - " \n", - " <xarray.DatasetView> Size: 2kB\n", - "Dimensions: (azimuth_time: 25)\n", - "Coordinates:\n", - " * azimuth_time (azimuth_time) datetime64[ns] 200B 2026-03-16T16:47:55.0000...\n", - "Data variables:\n", - " pitch (azimuth_time) float64 200B dask.array<chunksize=(25,), meta=np.ndarray>\n", - " q0 (azimuth_time) float32 100B dask.array<chunksize=(25,), meta=np.ndarray>\n", - " q1 (azimuth_time) float32 100B dask.array<chunksize=(25,), meta=np.ndarray>\n", - " q2 (azimuth_time) float32 100B dask.array<chunksize=(25,), meta=np.ndarray>\n", - " q3 (azimuth_time) float32 100B dask.array<chunksize=(25,), meta=np.ndarray>\n", - " roll (azimuth_time) float64 200B dask.array<chunksize=(25,), meta=np.ndarray>\n", - " wx (azimuth_time) float64 200B dask.array<chunksize=(25,), meta=np.ndarray>\n", - " wy (azimuth_time) float64 200B dask.array<chunksize=(25,), meta=np.ndarray>\n", - " wz (azimuth_time) float64 200B dask.array<chunksize=(25,), meta=np.ndarray>\n", - " yaw (azimuth_time) float64 200B dask.array<chunksize=(25,), meta=np.ndarray>attitude
- azimuth_time: 25
azimuth_time(azimuth_time)datetime64[ns]2026-03-16T16:47:55.000002 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- time stamp at which orbit state vectors apply
array(['2026-03-16T16:47:55.000002000', '2026-03-16T16:47:55.999998000',\n", - " '2026-03-16T16:47:57.000002000', '2026-03-16T16:47:57.999996000',\n", - " '2026-03-16T16:47:59.000000000', '2026-03-16T16:47:59.999995000',\n", - " '2026-03-16T16:48:01.000000000', '2026-03-16T16:48:01.999995000',\n", - " '2026-03-16T16:48:03.000000000', '2026-03-16T16:48:04.000003000',\n", - " '2026-03-16T16:48:04.999998000', '2026-03-16T16:48:06.000003000',\n", - " '2026-03-16T16:48:06.999997000', '2026-03-16T16:48:08.000002000',\n", - " '2026-03-16T16:48:08.999996000', '2026-03-16T16:48:10.000001000',\n", - " '2026-03-16T16:48:10.999996000', '2026-03-16T16:48:12.000000000',\n", - " '2026-03-16T16:48:12.999995000', '2026-03-16T16:48:14.000000000',\n", - " '2026-03-16T16:48:14.999994000', '2026-03-16T16:48:16.000000000',\n", - " '2026-03-16T16:48:17.000004000', '2026-03-16T16:48:17.999998000',\n", - " '2026-03-16T16:48:19.000004000'], dtype='datetime64[ns]')
pitch(azimuth_time)float64dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'platform pitch angle calculated from ancillary attitude data', 'units': 'degrees'}
- dtype :
- <f8
- long_name :
- platform pitch angle calculated from ancillary attitude data
- units :
- degrees
\n", + " \n", + "
25 \n", + "1 \n", + "\n", + " \n", + " \n", + " VH/conditions/attitude/roll(VH/conditions/attitude/azimuth_time)float64dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'platform roll angle calculated from ancillary attitude data', 'units': 'degrees'}
- dtype :
- <f8
- long_name :
- platform roll angle calculated from ancillary attitude data
- units :
- degrees
\n", "
\n", " \n", " \n", @@ -13526,12 +13055,12 @@ "
\n", "\n", " \n", - " 25 \n", - "1 \n", + "25 \n", + "1 \n", "\n", " \n", " \n", - " q0(azimuth_time)float32dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f4', 'long_name': 'q0 attitude quaternion as extracted from ancillary attitude data'}
- dtype :
- <f4
- long_name :
- q0 attitude quaternion as extracted from ancillary attitude data
\n", + "
VH/conditions/attitude/wx(VH/conditions/attitude/azimuth_time)float64dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'x component of angular velocity vector as extracted from ancillary attitude data', 'units': 'degrees/s'}
- dtype :
- <f8
- long_name :
- x component of angular velocity vector as extracted from ancillary attitude data
- units :
- degrees/s
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -13546,8 +13075,8 @@ " \n", "
\n", @@ -13581,12 +13110,12 @@ "\n", " \n", " \n", "Bytes \n", - "100 B \n", - "100 B \n", + "200 B \n", + "200 B \n", "\n", @@ -13561,7 +13090,7 @@ " \n", "\n", " \n", " \n", "Data type \n", - "float32 numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", "\n", " \n", - " 25 \n", - "1 \n", + "25 \n", + "1 \n", "\n", " q1(azimuth_time)float32dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f4', 'long_name': 'q1 attitude quaternion as extracted from ancillary attitude data'}
- dtype :
- <f4
- long_name :
- q1 attitude quaternion as extracted from ancillary attitude data
\n", + "
VH/conditions/attitude/wy(VH/conditions/attitude/azimuth_time)float64dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'y component of angular velocity vector as extracted from ancillary attitude data', 'units': 'degrees/s'}
- dtype :
- <f8
- long_name :
- y component of angular velocity vector as extracted from ancillary attitude data
- units :
- degrees/s
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -13601,8 +13130,8 @@ " \n", "
\n", @@ -13636,12 +13165,12 @@ "\n", " \n", " \n", "Bytes \n", - "100 B \n", - "100 B \n", + "200 B \n", + "200 B \n", "\n", @@ -13616,7 +13145,7 @@ " \n", "\n", " \n", " \n", "Data type \n", - "float32 numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", "\n", " \n", - " 25 \n", - "1 \n", + "25 \n", + "1 \n", "\n", " q2(azimuth_time)float32dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f4', 'long_name': 'q2 attitude quaternion as extracted from ancillary attitude data'}
- dtype :
- <f4
- long_name :
- q2 attitude quaternion as extracted from ancillary attitude data
\n", + "
VH/conditions/attitude/wz(VH/conditions/attitude/azimuth_time)float64dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'z component of angular velocity vector as extracted from ancillary attitude data', 'units': 'degrees/s'}
- dtype :
- <f8
- long_name :
- z component of angular velocity vector as extracted from ancillary attitude data
- units :
- degrees/s
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -13656,8 +13185,8 @@ " \n", "
\n", @@ -13691,12 +13220,12 @@ "\n", " \n", " \n", "Bytes \n", - "100 B \n", - "100 B \n", + "200 B \n", + "200 B \n", "\n", @@ -13671,7 +13200,7 @@ " \n", "\n", " \n", " \n", "Data type \n", - "float32 numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", "\n", " \n", - " 25 \n", - "1 \n", + "25 \n", + "1 \n", "\n", " q3(azimuth_time)float32dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f4', 'long_name': 'q3 attitude quaternion as extracted from ancillary attitude data'}
- dtype :
- <f4
- long_name :
- q3 attitude quaternion as extracted from ancillary attitude data
\n", + "
VH/conditions/attitude/yaw(VH/conditions/attitude/azimuth_time)float64dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'platform yaw angle calculated from ancillary attitude data', 'units': 'degrees'}
- dtype :
- <f8
- long_name :
- platform yaw angle calculated from ancillary attitude data
- units :
- degrees
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -13711,8 +13240,8 @@ " \n", "
\n", @@ -13746,12 +13275,12 @@ "\n", " \n", " \n", "Bytes \n", - "100 B \n", - "100 B \n", + "200 B \n", + "200 B \n", "\n", @@ -13726,7 +13255,7 @@ " \n", "\n", " \n", " \n", "Data type \n", - "float32 numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", "\n", " \n", - " 25 \n", - "1 \n", + "25 \n", + "1 \n", "\n", " roll(azimuth_time)float64dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'platform roll angle calculated from ancillary attitude data', 'units': 'degrees'}
- dtype :
- <f8
- long_name :
- platform roll angle calculated from ancillary attitude data
- units :
- degrees
\n", + "
VH/conditions/doppler_centroid/data_dc_polynomial(VH/conditions/doppler_centroid/azimuth_time, VH/conditions/doppler_centroid/degree)float32dask.array<chunksize=(27, 3), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'degree'], 'dimensions': ['azimuth_time', 'degree'], 'dtype': '<f4', 'long_name': 'doppler centroid estimated from data, expressed as polynomial with 5 coefficients: doppler centroid = d0 + d1(tsr-t0) + d2(tsr-t0)^2 + d3(tsr-t0)^3 + d4(tsr-t0)^4, where tsr = 2-way slant range time'}
- dtype :
- <f4
- long_name :
- doppler centroid estimated from data, expressed as polynomial with 5 coefficients: doppler centroid = d0 + d1(tsr-t0) + d2(tsr-t0)^2 + d3(tsr-t0)^3 + d4(tsr-t0)^4, where tsr = 2-way slant range time
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -13766,14 +13295,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "200 B \n", - "200 B \n", + "324 B \n", + "324 B \n", "\n", " \n", "Shape \n", - "(25,) \n", - "(25,) \n", + "(27, 3) \n", + "(27, 3) \n", "\n", " \n", "Dask graph \n", @@ -13781,32 +13310,32 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "float32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", - " \n", "\n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 25 \n", - "1 \n", + "3 \n", + "27 \n", " wx(azimuth_time)float64dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'x component of angular velocity vector as extracted from ancillary attitude data', 'units': 'degrees/s'}
- dtype :
- <f8
- long_name :
- x component of angular velocity vector as extracted from ancillary attitude data
- units :
- degrees/s
\n", + "
VH/conditions/doppler_centroid/data_dc_rms_error(VH/conditions/doppler_centroid/azimuth_time)float64dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'RMS error of the doppler centroid estimate (calculated as the average of the individual RMS residual errors between input fine doppler centroid estimates and the fitted polynomial; if the doppler centroid was not estimated from data, this is set to 0)'}
- dtype :
- <f8
- long_name :
- RMS error of the doppler centroid estimate (calculated as the average of the individual RMS residual errors between input fine doppler centroid estimates and the fitted polynomial; if the doppler centroid was not estimated from data, this is set to 0)
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -13821,14 +13350,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "200 B \n", - "200 B \n", + "216 B \n", + "216 B \n", "\n", " \n", "Shape \n", - "(25,) \n", - "(25,) \n", + "(27,) \n", + "(27,) \n", "\n", " Dask graph \n", @@ -13842,26 +13371,26 @@ "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 25 \n", - "1 \n", + "27 \n", + "1 \n", " wy(azimuth_time)float64dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'y component of angular velocity vector as extracted from ancillary attitude data', 'units': 'degrees/s'}
- dtype :
- <f8
- long_name :
- y component of angular velocity vector as extracted from ancillary attitude data
- units :
- degrees/s
\n", + "
VH/conditions/doppler_centroid/data_dc_rms_error_above_threshold(VH/conditions/doppler_centroid/azimuth_time)booldask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<b1', 'long_name': 'false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold'}
- dtype :
- <b1
- long_name :
- false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -13876,14 +13405,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "200 B \n", - "200 B \n", + "27 B \n", + "27 B \n", "\n", " \n", "Shape \n", - "(25,) \n", - "(25,) \n", + "(27,) \n", + "(27,) \n", "\n", " \n", "Dask graph \n", @@ -13891,32 +13420,32 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "bool numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 25 \n", - "1 \n", + "27 \n", + "1 \n", " wz(azimuth_time)float64dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'z component of angular velocity vector as extracted from ancillary attitude data', 'units': 'degrees/s'}
- dtype :
- <f8
- long_name :
- z component of angular velocity vector as extracted from ancillary attitude data
- units :
- degrees/s
\n", + "
VH/conditions/doppler_centroid/fine_dce_azimuth_start_time(VH/conditions/doppler_centroid/azimuth_time)booldask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<b1', 'long_name': 'false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold'}
- dtype :
- <b1
- long_name :
- false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -13931,14 +13460,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "200 B \n", - "200 B \n", + "27 B \n", + "27 B \n", "\n", " \n", "Shape \n", - "(25,) \n", - "(25,) \n", + "(27,) \n", + "(27,) \n", "\n", " \n", "Dask graph \n", @@ -13946,32 +13475,32 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "bool numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 25 \n", - "1 \n", + "27 \n", + "1 \n", " yaw(azimuth_time)float64dask.array<chunksize=(25,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'platform yaw angle calculated from ancillary attitude data', 'units': 'degrees'}
- dtype :
- <f8
- long_name :
- platform yaw angle calculated from ancillary attitude data
- units :
- degrees
\n", + "
VH/conditions/doppler_centroid/fine_dce_azimuth_stop_time(VH/conditions/doppler_centroid/azimuth_time)booldask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<b1', 'long_name': 'false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold'}
- dtype :
- <b1
- long_name :
- false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -13986,14 +13515,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "200 B \n", - "200 B \n", + "27 B \n", + "27 B \n", "\n", " \n", "Shape \n", - "(25,) \n", - "(25,) \n", + "(27,) \n", + "(27,) \n", "\n", " \n", "Dask graph \n", @@ -14001,500 +13530,87 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "bool numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 25 \n", - "1 \n", + "27 \n", + "1 \n", "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - " \n", - " \n", - " \n", - "\n", - " \n", - " \n", - " \n", - " <xarray.DatasetView> Size: 1kB\n", - "Dimensions: (azimuth_time: 27, degree: 3)\n", - "Coordinates:\n", - " * azimuth_time (azimuth_time) datetime64[ns] 216B 202...\n", - " * degree (degree) int64 24B 2 1 0\n", - "Data variables:\n", - " data_dc_polynomial (azimuth_time, degree) float32 324B dask.array<chunksize=(27, 3), meta=np.ndarray>\n", - " data_dc_rms_error (azimuth_time) float64 216B dask.array<chunksize=(27,), meta=np.ndarray>\n", - " data_dc_rms_error_above_threshold (azimuth_time) bool 27B dask.array<chunksize=(27,), meta=np.ndarray>\n", - " fine_dce_azimuth_start_time (azimuth_time) bool 27B dask.array<chunksize=(27,), meta=np.ndarray>\n", - " fine_dce_azimuth_stop_time (azimuth_time) bool 27B dask.array<chunksize=(27,), meta=np.ndarray>\n", - " geometry_dc_polynomial (azimuth_time, degree) float32 324B dask.array<chunksize=(27, 3), meta=np.ndarray>\n", - " t0 (azimuth_time) float64 216B dask.array<chunksize=(27,), meta=np.ndarray>doppler_centroid
- azimuth_time: 27
- degree: 3
azimuth_time(azimuth_time)datetime64[ns]2026-03-16T16:47:56.021426 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- zero doppler azimuth time of terrain height measurement
array(['2026-03-16T16:47:56.021426000', '2026-03-16T16:47:56.022979000',\n", - " '2026-03-16T16:47:56.035054000', '2026-03-16T16:47:58.779703000',\n", - " '2026-03-16T16:47:58.781256000', '2026-03-16T16:47:58.793331000',\n", - " '2026-03-16T16:48:01.537980000', '2026-03-16T16:48:01.539533000',\n", - " '2026-03-16T16:48:01.551608000', '2026-03-16T16:48:04.296257000',\n", - " '2026-03-16T16:48:04.297810000', '2026-03-16T16:48:04.309885000',\n", - " '2026-03-16T16:48:07.054533000', '2026-03-16T16:48:07.056086000',\n", - " '2026-03-16T16:48:07.068161000', '2026-03-16T16:48:09.812810000',\n", - " '2026-03-16T16:48:09.814363000', '2026-03-16T16:48:09.826438000',\n", - " '2026-03-16T16:48:12.571087000', '2026-03-16T16:48:12.572640000',\n", - " '2026-03-16T16:48:12.584715000', '2026-03-16T16:48:15.329364000',\n", - " '2026-03-16T16:48:15.330917000', '2026-03-16T16:48:15.342992000',\n", - " '2026-03-16T16:48:18.087641000', '2026-03-16T16:48:18.089194000',\n", - " '2026-03-16T16:48:18.101269000'], dtype='datetime64[ns]') degree(degree)int642 1 0array([2, 1, 0])
data_dc_polynomial(azimuth_time, degree)float32dask.array<chunksize=(27, 3), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'degree'], 'dimensions': ['azimuth_time', 'degree'], 'dtype': '<f4', 'long_name': 'doppler centroid estimated from data, expressed as polynomial with 5 coefficients: doppler centroid = d0 + d1(tsr-t0) + d2(tsr-t0)^2 + d3(tsr-t0)^3 + d4(tsr-t0)^4, where tsr = 2-way slant range time'}
- dtype :
- <f4
- long_name :
- doppler centroid estimated from data, expressed as polynomial with 5 coefficients: doppler centroid = d0 + d1(tsr-t0) + d2(tsr-t0)^2 + d3(tsr-t0)^3 + d4(tsr-t0)^4, where tsr = 2-way slant range time
\n", + " \n", + "
3 \n", + "27 \n", + "\n", + " \n", + " \n", + " VH/conditions/doppler_centroid/t0(VH/conditions/doppler_centroid/azimuth_time)float64dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'two-way slant range time origin for doppler centroid estimate', 'units': 's'}
- dtype :
- <f8
- long_name :
- two-way slant range time origin for doppler centroid estimate
- units :
- s
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -14509,14 +13625,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "324 B \n", - "324 B \n", + "216 B \n", + "216 B \n", "\n", " \n", "Shape \n", - "(27, 3) \n", - "(27, 3) \n", + "(27,) \n", + "(27,) \n", "\n", " \n", "Dask graph \n", @@ -14524,32 +13640,32 @@ "\n", " \n", " \n", "Data type \n", - "float32 numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", - " \n", "\n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 3 \n", - "27 \n", + "27 \n", + "1 \n", " data_dc_rms_error(azimuth_time)float64dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'RMS error of the doppler centroid estimate (calculated as the average of the individual RMS residual errors between input fine doppler centroid estimates and the fitted polynomial; if the doppler centroid was not estimated from data, this is set to 0)'}
- dtype :
- <f8
- long_name :
- RMS error of the doppler centroid estimate (calculated as the average of the individual RMS residual errors between input fine doppler centroid estimates and the fitted polynomial; if the doppler centroid was not estimated from data, this is set to 0)
\n", + "
VH/conditions/gcp/azimuth_time_gcp(VH/conditions/gcp/azimuth_time, VH/conditions/gcp/ground_range)datetime64[ns]dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -14564,14 +13680,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "216 B \n", - "216 B \n", + "1.64 kiB \n", + "1.64 kiB \n", "\n", " \n", "Shape \n", - "(27,) \n", - "(27,) \n", + "(10, 21) \n", + "(10, 21) \n", "\n", " \n", "Dask graph \n", @@ -14579,32 +13695,32 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "datetime64[ns] numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 27 \n", - "1 \n", + "21 \n", + "10 \n", " data_dc_rms_error_above_threshold(azimuth_time)booldask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<b1', 'long_name': 'false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold'}
- dtype :
- <b1
- long_name :
- false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold
\n", + "
VH/conditions/gcp/elevation_angle(VH/conditions/gcp/azimuth_time, VH/conditions/gcp/ground_range)float64dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -14619,14 +13735,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "27 B \n", - "27 B \n", + "1.64 kiB \n", + "1.64 kiB \n", "\n", " \n", "Shape \n", - "(27,) \n", - "(27,) \n", + "(10, 21) \n", + "(10, 21) \n", "\n", " \n", "Dask graph \n", @@ -14634,32 +13750,32 @@ "\n", " \n", " \n", "Data type \n", - "bool numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 27 \n", - "1 \n", + "21 \n", + "10 \n", " fine_dce_azimuth_start_time(azimuth_time)booldask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<b1', 'long_name': 'false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold'}
- dtype :
- <b1
- long_name :
- false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold
\n", + "
VH/conditions/gcp/height(VH/conditions/gcp/azimuth_time, VH/conditions/gcp/ground_range)float64dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -14674,14 +13790,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "27 B \n", - "27 B \n", + "1.64 kiB \n", + "1.64 kiB \n", "\n", " \n", "Shape \n", - "(27,) \n", - "(27,) \n", + "(10, 21) \n", + "(10, 21) \n", "\n", " \n", "Dask graph \n", @@ -14689,32 +13805,32 @@ "\n", " \n", " \n", "Data type \n", - "bool numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 27 \n", - "1 \n", + "21 \n", + "10 \n", " fine_dce_azimuth_stop_time(azimuth_time)booldask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<b1', 'long_name': 'false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold'}
- dtype :
- <b1
- long_name :
- false if the RMS error is less than the acceptable threshold for the doppler centroid estimated from the data; true if the RMS error is more than or equal to the acceptable threshold
\n", + "
VH/conditions/gcp/incidence_angle(VH/conditions/gcp/azimuth_time, VH/conditions/gcp/ground_range)float64dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -14729,14 +13845,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "27 B \n", - "27 B \n", + "1.64 kiB \n", + "1.64 kiB \n", "\n", " \n", "Shape \n", - "(27,) \n", - "(27,) \n", + "(10, 21) \n", + "(10, 21) \n", "\n", " \n", "Dask graph \n", @@ -14744,32 +13860,32 @@ "\n", " \n", " \n", "Data type \n", - "bool numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 27 \n", - "1 \n", + "21 \n", + "10 \n", " geometry_dc_polynomial(azimuth_time, degree)float32dask.array<chunksize=(27, 3), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'degree'], 'dimensions': ['azimuth_time', 'degree'], 'dtype': '<f4', 'long_name': 'doppler centroid estimated from orbit, expressed as polynomial with 5 coefficients: doppler centroid = d0 + d1(tsr-t0) + d2(tsr-t0)^2 + d3(tsr-t0)^3 + d4(tsr-t0)^4, where tsr = 2-way slant range time'}
- dtype :
- <f4
- long_name :
- doppler centroid estimated from orbit, expressed as polynomial with 5 coefficients: doppler centroid = d0 + d1(tsr-t0) + d2(tsr-t0)^2 + d3(tsr-t0)^3 + d4(tsr-t0)^4, where tsr = 2-way slant range time
\n", + "
VH/conditions/gcp/latitude(VH/conditions/gcp/azimuth_time, VH/conditions/gcp/ground_range)float64dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -14784,14 +13900,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "324 B \n", - "324 B \n", + "1.64 kiB \n", + "1.64 kiB \n", "\n", " \n", "Shape \n", - "(27, 3) \n", - "(27, 3) \n", + "(10, 21) \n", + "(10, 21) \n", "\n", " \n", "Dask graph \n", @@ -14799,32 +13915,32 @@ "\n", " \n", " \n", "Data type \n", - "float32 numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", - " \n", "\n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 3 \n", - "27 \n", + "21 \n", + "10 \n", " t0(azimuth_time)float64dask.array<chunksize=(27,), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time'], 'dimensions': ['azimuth_time'], 'dtype': '<f8', 'long_name': 'two-way slant range time origin for doppler centroid estimate', 'units': 's'}
- dtype :
- <f8
- long_name :
- two-way slant range time origin for doppler centroid estimate
- units :
- s
\n", + "
VH/conditions/gcp/longitude(VH/conditions/gcp/azimuth_time, VH/conditions/gcp/ground_range)float64dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -14839,14 +13955,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "216 B \n", - "216 B \n", + "1.64 kiB \n", + "1.64 kiB \n", "\n", " \n", "Shape \n", - "(27,) \n", - "(27,) \n", + "(10, 21) \n", + "(10, 21) \n", "\n", " Dask graph \n", @@ -14860,490 +13976,26 @@ "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 27 \n", - "1 \n", + "21 \n", + "10 \n", "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - " \n", - " \n", - " \n", - "\n", - " \n", - " \n", - " \n", - " <xarray.DatasetView> Size: 12kB\n", - "Dimensions: (azimuth_time: 10, ground_range: 21)\n", - "Coordinates:\n", - " * azimuth_time (azimuth_time) datetime64[ns] 80B 2026-03-16T16:47:...\n", - " * ground_range (ground_range) float64 168B 0.0 ... 2.664e+05\n", - " line (azimuth_time) uint32 40B dask.array<chunksize=(10,), meta=np.ndarray>\n", - " pixel (ground_range) uint32 84B dask.array<chunksize=(21,), meta=np.ndarray>\n", - "Data variables:\n", - " azimuth_time_gcp (azimuth_time, ground_range) datetime64[ns] 2kB dask.array<chunksize=(10, 21), meta=np.ndarray>\n", - " elevation_angle (azimuth_time, ground_range) float64 2kB dask.array<chunksize=(10, 21), meta=np.ndarray>\n", - " height (azimuth_time, ground_range) float64 2kB dask.array<chunksize=(10, 21), meta=np.ndarray>\n", - " incidence_angle (azimuth_time, ground_range) float64 2kB dask.array<chunksize=(10, 21), meta=np.ndarray>\n", - " latitude (azimuth_time, ground_range) float64 2kB dask.array<chunksize=(10, 21), meta=np.ndarray>\n", - " longitude (azimuth_time, ground_range) float64 2kB dask.array<chunksize=(10, 21), meta=np.ndarray>\n", - " slant_range_time_gcp (azimuth_time, ground_range) float64 2kB dask.array<chunksize=(10, 21), meta=np.ndarray>gcp
- azimuth_time: 10
- ground_range: 21
azimuth_time(azimuth_time)datetime64[ns]2026-03-16T16:47:54.761834 ... 2...array(['2026-03-16T16:47:54.761834000', '2026-03-16T16:47:57.762318000',\n", - " '2026-03-16T16:48:00.762803000', '2026-03-16T16:48:03.763288000',\n", - " '2026-03-16T16:48:06.763773000', '2026-03-16T16:48:09.764257000',\n", - " '2026-03-16T16:48:12.764742000', '2026-03-16T16:48:15.765227000',\n", - " '2026-03-16T16:48:18.765712000', '2026-03-16T16:48:19.760381000'],\n", - " dtype='datetime64[ns]') ground_range(ground_range)float640.0 1.333e+04 ... 2.664e+05array([ 0., 13330., 26660., 39990., 53320., 66650., 79980., 93310.,\n", - " 106640., 119970., 133300., 146630., 159960., 173290., 186620., 199950.,\n", - " 213280., 226610., 239940., 253270., 266410.]) line(azimuth_time)uint32dask.array<chunksize=(10,), meta=np.ndarray>\n", + "
VH/conditions/gcp/slant_range_time_gcp(VH/conditions/gcp/azimuth_time, VH/conditions/gcp/ground_range)float64dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -15358,14 +14010,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "40 B \n", - "40 B \n", + "1.64 kiB \n", + "1.64 kiB \n", "\n", " \n", "Shape \n", - "(10,) \n", - "(10,) \n", + "(10, 21) \n", + "(10, 21) \n", "\n", " \n", "Dask graph \n", @@ -15373,32 +14025,32 @@ "\n", " \n", " \n", "Data type \n", - "uint32 numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 10 \n", - "1 \n", + "21 \n", + "10 \n", " pixel(ground_range)uint32dask.array<chunksize=(21,), meta=np.ndarray>\n", + "
VH/conditions/orbit/position(VH/conditions/orbit/azimuth_time, VH/conditions/orbit/axis)float64dask.array<chunksize=(17, 3), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'axis'], 'dimensions': ['azimuth_time', 'axis'], 'dtype': '<f8', 'long_name': 'position vector', 'units': 'm'}
- dtype :
- <f8
- long_name :
- position vector
- units :
- m
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -15413,14 +14065,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "84 B \n", - "84 B \n", + "408 B \n", + "408 B \n", "\n", " \n", "Shape \n", - "(21,) \n", - "(21,) \n", + "(17, 3) \n", + "(17, 3) \n", "\n", " \n", "Dask graph \n", @@ -15428,32 +14080,32 @@ "\n", " \n", " \n", "Data type \n", - "uint32 numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", - " \n", "\n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 21 \n", - "1 \n", + "3 \n", + "17 \n", "
azimuth_time_gcp(azimuth_time, ground_range)datetime64[ns]dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", + "
VH/conditions/orbit/velocity(VH/conditions/orbit/azimuth_time, VH/conditions/orbit/axis)float64dask.array<chunksize=(17, 3), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'axis'], 'dimensions': ['azimuth_time', 'axis'], 'dtype': '<f8', 'long_name': 'velocity vector', 'units': 'm/s'}
- dtype :
- <f8
- long_name :
- velocity vector
- units :
- m/s
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -15468,14 +14120,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "1.64 kiB \n", - "1.64 kiB \n", + "408 B \n", + "408 B \n", "\n", " \n", "Shape \n", - "(10, 21) \n", - "(10, 21) \n", + "(17, 3) \n", + "(17, 3) \n", "\n", " \n", "Dask graph \n", @@ -15483,32 +14135,32 @@ "\n", " \n", " \n", "Data type \n", - "datetime64[ns] numpy.ndarray \n", + "float64 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", - " \n", "\n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 21 \n", - "10 \n", + "3 \n", + "17 \n", " elevation_angle(azimuth_time, ground_range)float64dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", + "
VH/measurements/grd(VH/measurements/azimuth_time, VH/measurements/ground_range)uint16dask.array<chunksize=(2048, 2048), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'line', 'pixel', 'ground_range'], 'dimensions': ['azimuth_time', 'ground_range'], 'dtype': '<u2', 'long_name': 'measurement data set for GRD IW'}
- dtype :
- <u2
- long_name :
- measurement data set for GRD IW
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -15523,47 +14175,68 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "1.64 kiB \n", - "1.64 kiB \n", + "848.06 MiB \n", + "8.00 MiB \n", "\n", " \n", "Shape \n", - "(10, 21) \n", - "(10, 21) \n", + "(16689, 26642) \n", + "(2048, 2048) \n", "\n", " \n", "Dask graph \n", - "1 chunks in 2 graph layers \n", + "126 chunks in 2 graph layers \n", "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "uint16 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 21 \n", - "10 \n", + "26642 \n", + "16689 \n", " height(azimuth_time, ground_range)float64dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", + "
VH/quality/calibration/beta_nought(VH/quality/calibration/azimuth_time, VH/quality/calibration/ground_range)float32dask.array<chunksize=(27, 668), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'line', 'pixel', 'ground_range'], 'dimensions': ['azimuth_time', 'ground_range'], 'dtype': '<f4', 'long_name': 'beta nought calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)'}
- dtype :
- <f4
- long_name :
- beta nought calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -15578,14 +14251,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "1.64 kiB \n", - "1.64 kiB \n", + "70.45 kiB \n", + "70.45 kiB \n", "\n", " \n", "Shape \n", - "(10, 21) \n", - "(10, 21) \n", + "(27, 668) \n", + "(27, 668) \n", "\n", " \n", "Dask graph \n", @@ -15593,32 +14266,32 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "float32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 21 \n", - "10 \n", + "668 \n", + "27 \n", " incidence_angle(azimuth_time, ground_range)float64dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", + "
VH/quality/calibration/dn(VH/quality/calibration/azimuth_time, VH/quality/calibration/ground_range)float32dask.array<chunksize=(27, 668), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'line', 'pixel', 'ground_range'], 'dimensions': ['azimuth_time', 'ground_range'], 'dtype': '<f4', 'long_name': 'digital number calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)'}
- dtype :
- <f4
- long_name :
- digital number calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -15633,14 +14306,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "1.64 kiB \n", - "1.64 kiB \n", + "70.45 kiB \n", + "70.45 kiB \n", "\n", " \n", "Shape \n", - "(10, 21) \n", - "(10, 21) \n", + "(27, 668) \n", + "(27, 668) \n", "\n", " \n", "Dask graph \n", @@ -15648,32 +14321,32 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "float32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 21 \n", - "10 \n", + "668 \n", + "27 \n", " latitude(azimuth_time, ground_range)float64dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", + "
VH/quality/calibration/gamma(VH/quality/calibration/azimuth_time, VH/quality/calibration/ground_range)float32dask.array<chunksize=(27, 668), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'line', 'pixel', 'ground_range'], 'dimensions': ['azimuth_time', 'ground_range'], 'dtype': '<f4', 'long_name': 'gamma calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)'}
- dtype :
- <f4
- long_name :
- gamma calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -15688,14 +14361,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "1.64 kiB \n", - "1.64 kiB \n", + "70.45 kiB \n", + "70.45 kiB \n", "\n", " \n", "Shape \n", - "(10, 21) \n", - "(10, 21) \n", + "(27, 668) \n", + "(27, 668) \n", "\n", " \n", "Dask graph \n", @@ -15703,32 +14376,32 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "float32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 21 \n", - "10 \n", + "668 \n", + "27 \n", " longitude(azimuth_time, ground_range)float64dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", + "
VH/quality/calibration/sigma_nought(VH/quality/calibration/azimuth_time, VH/quality/calibration/ground_range)float32dask.array<chunksize=(27, 668), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'line', 'pixel', 'ground_range'], 'dimensions': ['azimuth_time', 'ground_range'], 'dtype': '<f4', 'long_name': 'sigma nought calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)'}
- dtype :
- <f4
- long_name :
- sigma nought calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -15743,14 +14416,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "1.64 kiB \n", - "1.64 kiB \n", + "70.45 kiB \n", + "70.45 kiB \n", "\n", " \n", "Shape \n", - "(10, 21) \n", - "(10, 21) \n", + "(27, 668) \n", + "(27, 668) \n", "\n", " \n", "Dask graph \n", @@ -15758,32 +14431,32 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "float32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 21 \n", - "10 \n", + "668 \n", + "27 \n", " slant_range_time_gcp(azimuth_time, ground_range)float64dask.array<chunksize=(10, 21), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'ground_range', 'line', 'pixel'], 'dimensions': ['azimuth_time', 'ground_range']}
\n", + "
VH/quality/azimuth/noise_azimuth_lut(VH/quality/azimuth/swath, VH/quality/azimuth/azimuth_time)float32dask.array<chunksize=(3, 1688), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['line', 'swath', 'first_azimuth_time', 'last_azimuth_time', 'first_range_sample', 'last_range_sample'], 'dimensions': ['swath', 'azimuth_time'], 'dtype': '<f4', 'long_name': 'azimuth thermal noise correction vector power values (this array contains the count attribute number of floating point values)'}
- dtype :
- <f4
- long_name :
- azimuth thermal noise correction vector power values (this array contains the count attribute number of floating point values)
\n", "
\n", " \n", - "\n", " \n", "\n", @@ -15798,14 +14471,14 @@ " \n", "
\n", "\n", " \n", " \n", "Bytes \n", - "1.64 kiB \n", - "1.64 kiB \n", + "19.78 kiB \n", + "19.78 kiB \n", "\n", " \n", "Shape \n", - "(10, 21) \n", - "(10, 21) \n", + "(3, 1688) \n", + "(3, 1688) \n", "\n", " \n", "Dask graph \n", @@ -15813,30349 +14486,5131 @@ "\n", " \n", " \n", "Data type \n", - "float64 numpy.ndarray \n", + "float32 numpy.ndarray \n", "\n", - " \n", "\n", + " \n", "\n", " \n", " \n", "\n", - " \n", + " \n", "\n", " \n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", - " 21 \n", - "10 \n", + "1688 \n", + "3 \n", "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - " \n", - " \n", - " \n", - "\n", - " \n", - " \n", - " \n", - " <xarray.DatasetView> Size: 964B\n", - "Dimensions: (azimuth_time: 17, axis: 3)\n", - "Coordinates:\n", - " * axis (axis) <U1 12B 'x' 'y' 'z'\n", - " * azimuth_time (azimuth_time) datetime64[ns] 136B 2026-03-16T16:46:46.6816...\n", - "Data variables:\n", - " position (azimuth_time, axis) float64 408B dask.array<chunksize=(17, 3), meta=np.ndarray>\n", - " velocity (azimuth_time, axis) float64 408B dask.array<chunksize=(17, 3), meta=np.ndarray>orbit
- azimuth_time: 17
- axis: 3
axis(axis)<U1'x' 'y' 'z'array(['x', 'y', 'z'], dtype='<U1') azimuth_time(azimuth_time)datetime64[ns]2026-03-16T16:46:46.681692 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- time stamp at which orbit state vectors apply
array(['2026-03-16T16:46:46.681692000', '2026-03-16T16:46:56.681692000',\n", - " '2026-03-16T16:47:06.681692000', '2026-03-16T16:47:16.681692000',\n", - " '2026-03-16T16:47:26.681692000', '2026-03-16T16:47:36.681693000',\n", - " '2026-03-16T16:47:46.681693000', '2026-03-16T16:47:56.681692000',\n", - " '2026-03-16T16:48:06.681692000', '2026-03-16T16:48:16.681692000',\n", - " '2026-03-16T16:48:26.681692000', '2026-03-16T16:48:36.681692000',\n", - " '2026-03-16T16:48:46.681692000', '2026-03-16T16:48:56.681693000',\n", - " '2026-03-16T16:49:06.681693000', '2026-03-16T16:49:16.681692000',\n", - " '2026-03-16T16:49:26.681692000'], dtype='datetime64[ns]')
position(azimuth_time, axis)float64dask.array<chunksize=(17, 3), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'axis'], 'dimensions': ['azimuth_time', 'axis'], 'dtype': '<f8', 'long_name': 'position vector', 'units': 'm'}
- dtype :
- <f8
- long_name :
- position vector
- units :
- m
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- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'axis'], 'dimensions': ['azimuth_time', 'axis'], 'dtype': '<f8', 'long_name': 'velocity vector', 'units': 'm/s'}
- dtype :
- <f8
- long_name :
- velocity vector
- units :
- m/s
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- azimuth_time: 16689
- ground_range: 26642
azimuth_time(azimuth_time)datetime64[ns]2026-03-16T16:47:54.761834 ... 2...array(['2026-03-16T16:47:54.761834000', '2026-03-16T16:47:54.763331995',\n", - " '2026-03-16T16:47:54.764829990', ..., '2026-03-16T16:48:19.757385009',\n", - " '2026-03-16T16:48:19.758883004', '2026-03-16T16:48:19.760381000'],\n", - " shape=(16689,), dtype='datetime64[ns]') ground_range(ground_range)float640.0 10.0 ... 2.664e+05 2.664e+05array([0.0000e+00, 1.0000e+01, 2.0000e+01, ..., 2.6639e+05, 2.6640e+05,\n", - " 2.6641e+05], shape=(26642,)) line(azimuth_time)int64dask.array<chunksize=(2048,), meta=np.ndarray>\n", - "
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grd(azimuth_time, ground_range)uint16dask.array<chunksize=(2048, 4096), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'line', 'pixel', 'ground_range'], 'dimensions': ['azimuth_time', 'ground_range'], 'dtype': '<u2', 'long_name': 'measurement data set for GRD IW'}
- dtype :
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- long_name :
- measurement data set for GRD IW
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- azimuth_time: 27
- ground_range: 668
azimuth_time(azimuth_time)datetime64[ns]2026-03-16T16:47:54.761834 ... 2...
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- zero doppler azimuth time at which calibration vector applies
array(['2026-03-16T16:47:54.761834000', '2026-03-16T16:47:55.761834000',\n", - " '2026-03-16T16:47:56.761834000', '2026-03-16T16:47:57.761834000',\n", - " '2026-03-16T16:47:58.761834000', '2026-03-16T16:47:59.761834000',\n", - " '2026-03-16T16:48:00.761834000', '2026-03-16T16:48:01.761834000',\n", - " '2026-03-16T16:48:02.761834000', '2026-03-16T16:48:03.761834000',\n", - " '2026-03-16T16:48:04.761834000', '2026-03-16T16:48:05.761834000',\n", - " '2026-03-16T16:48:06.761834000', '2026-03-16T16:48:07.761834000',\n", - " '2026-03-16T16:48:08.761834000', '2026-03-16T16:48:09.761834000',\n", - " '2026-03-16T16:48:10.761834000', '2026-03-16T16:48:11.761834000',\n", - " '2026-03-16T16:48:12.761834000', '2026-03-16T16:48:13.761834000',\n", - " '2026-03-16T16:48:14.761834000', '2026-03-16T16:48:15.761834000',\n", - " '2026-03-16T16:48:16.761834000', '2026-03-16T16:48:17.761834000',\n", - " '2026-03-16T16:48:18.761834000', '2026-03-16T16:48:19.761834000',\n", - " '2026-03-16T16:48:20.761834000'], dtype='datetime64[ns]') ground_range(ground_range)float640.0 6.675e+06 ... 4.446e+09
- dimensions :
- ['ground_range']
- dtype :
- <f8
array([0.000000e+00, 6.675200e+06, 1.335040e+07, ..., 4.439008e+09,\n", - " 4.445683e+09, 4.445850e+09], shape=(668,)) line(azimuth_time)uint32dask.array<chunksize=(27,), meta=np.ndarray>
- dimensions :
- ['azimuth_time']
- dtype :
- <u4
- long_name :
- image line at which the calibration vector applies
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- dimensions :
- ['ground_range']
- dtype :
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- long_name :
- image pixel at which the calibration vector applies (this array contains the count attribute number of integer values (i.e. one value per point in the noise vector); the maximum length of this array is one value for every pixel in an image line, however in general the vector is subsampled)
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beta_nought(azimuth_time, ground_range)float32dask.array<chunksize=(27, 668), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'line', 'pixel', 'ground_range'], 'dimensions': ['azimuth_time', 'ground_range'], 'dtype': '<f4', 'long_name': 'beta nought calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)'}
- dtype :
- <f4
- long_name :
- beta nought calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)
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- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'line', 'pixel', 'ground_range'], 'dimensions': ['azimuth_time', 'ground_range'], 'dtype': '<f4', 'long_name': 'digital number calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)'}
- dtype :
- <f4
- long_name :
- digital number calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)
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- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'line', 'pixel', 'ground_range'], 'dimensions': ['azimuth_time', 'ground_range'], 'dtype': '<f4', 'long_name': 'gamma calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)'}
- dtype :
- <f4
- long_name :
- gamma calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)
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- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'line', 'pixel', 'ground_range'], 'dimensions': ['azimuth_time', 'ground_range'], 'dtype': '<f4', 'long_name': 'sigma nought calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)'}
- dtype :
- <f4
- long_name :
- sigma nought calibration vector (this array contains the count attribute number of floating point values; the values in this vector are aligned with the pixel vector)
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- swath: 3
- azimuth_time: 1688
first_azimuth_time(swath)int32dask.array<chunksize=(3,), meta=np.ndarray>
- dtype :
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- long_name :
- first azimuth line azimuth thermal noise correction
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- dtype :
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- long_name :
- first range sample azimuth thermal noise correction
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- dtype :
- <i4
- long_name :
- last azimuth line azimuth thermal noise correction
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- dtype :
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- long_name :
- last range sample azimuth thermal noise correction
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- dimensions :
- ['swath', 'azimuth_time']
- dtype :
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- long_name :
- line
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array(['IW1', 'IW2', 'IW3'], dtype='<U3')
noise_azimuth_lut(swath, azimuth_time)float32dask.array<chunksize=(3, 1688), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['line', 'swath', 'first_azimuth_time', 'last_azimuth_time', 'first_range_sample', 'last_range_sample'], 'dimensions': ['swath', 'azimuth_time'], 'dtype': '<f4', 'long_name': 'azimuth thermal noise correction vector power values (this array contains the count attribute number of floating point values)'}
- dtype :
- <f4
- long_name :
- azimuth thermal noise correction vector power values (this array contains the count attribute number of floating point values)
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- azimuth_time: 26
- ground_range: 671
ground_range(azimuth_time, ground_range)float64dask.array<chunksize=(26, 671), meta=np.ndarray>\n", - "
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- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
- long_name :
- zero doppler azimuth time at which noise vector applies
array(['2026-03-16T16:47:54.761834000', '2026-03-16T16:47:55.762495000',\n", - " '2026-03-16T16:47:56.763156000', '2026-03-16T16:47:57.763817000',\n", - " '2026-03-16T16:47:58.764478000', '2026-03-16T16:47:59.765139000',\n", - " '2026-03-16T16:48:00.765800000', '2026-03-16T16:48:01.766461000',\n", - " '2026-03-16T16:48:02.767122000', '2026-03-16T16:48:03.767783000',\n", - " '2026-03-16T16:48:04.768444000', '2026-03-16T16:48:05.769104000',\n", - " '2026-03-16T16:48:06.769765000', '2026-03-16T16:48:07.770426000',\n", - " '2026-03-16T16:48:08.771087000', '2026-03-16T16:48:09.771748000',\n", - " '2026-03-16T16:48:10.772409000', '2026-03-16T16:48:11.773070000',\n", - " '2026-03-16T16:48:12.773731000', '2026-03-16T16:48:13.774392000',\n", - " '2026-03-16T16:48:14.775053000', '2026-03-16T16:48:15.775714000',\n", - " '2026-03-16T16:48:16.776375000', '2026-03-16T16:48:17.777036000',\n", - " '2026-03-16T16:48:18.777697000', '2026-03-16T16:48:19.760382000'],\n", - " dtype='datetime64[ns]') line(azimuth_time)int32dask.array<chunksize=(26,), meta=np.ndarray>
- dimensions :
- ['azimuth_time']
- dtype :
- <M8[ns]
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noise_range_lut(azimuth_time, ground_range)float32dask.array<chunksize=(26, 671), meta=np.ndarray>
- _eopf_attrs :
- {'coordinates': ['azimuth_time', 'line', 'pixel', 'ground_range'], 'dimensions': ['azimuth_time', 'ground_range'], 'dtype': '<f4', 'long_name': 'range thermal noise correction vector power values (this array contains the count attribute number of floating point values)'}
- dtype :
- <f4
- long_name :
- range thermal noise correction vector power values (this array contains the count attribute number of floating point values)
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- other_metadata :
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'num_err_swap_flag': 0, 'num_err_swath_number': 0, 'num_err_swl': 0, 'num_err_swst': 0, 'num_err_sync_marker': 0, 'num_err_temp_comp': 0, 'num_err_test_mode': 0, 'num_err_tx_pulse_number': 0, 'num_err_tx_pulse_start_frequency': 0, 'num_err_tx_ramp_rate': 0, 'num_isp_header_errors': 0, 'pointing_status': {'azimuth_time': '2026-03-16T16:42:01.112039'}, 'prf': 1717.128973878037, 'pri': 0.0005823674372819869, 'rank': 9, 'rx_channel_id': 0, 'rx_gain': -4.0, 'sampling_frequency_after_decimation': 64345238.12571429, 'swath': 'IW1', 'swath_number': 10, 'swl_azimuth_time': ['2026-03-16T16:47:51.903772', '2026-03-16T16:48:00.178598', '2026-03-16T16:47:52.723896', '2026-03-16T16:48:00.998722', '2026-03-16T16:47:53.800376', '2026-03-16T16:48:02.075218'], 'swl_value': ['3.725084179549267e-04', '3.722952819698287e-04', '4.438024049701879e-04', '4.435359849888155e-04', '4.234479183933346e-04', '4.231282144156876e-04'], 'swst_azimuth_time': ['2026-03-16T16:47:51.903772', '2026-03-16T16:48:05.695154', '2026-03-16T16:47:52.723896', '2026-03-16T16:48:06.515278', '2026-03-16T16:47:53.800376', '2026-03-16T16:48:07.591758'], 'swst_value': ['1.021987048544628e-04', '1.035574467594622e-04', '1.416555040957191e-04', '1.428810360100323e-04', '9.095578164054638e-05', '9.204810356417333e-05'], 'tx_pulse_length': 5.240481033595628e-05, 'tx_pulse_ramp_rate': 1078230321255.894, 'tx_pulse_start_frequency': -28251534.19637256}, 'eopf_category': 'eoproduct', 'general_annotation': {'attitude_list': [{'frame': 'GM2000', 'pitch': -55.17261231188552, 'q_0': -0.4113218, 'q_1': 0.3290825, 'q_2': -0.1024825, 'q_3': 0.8438106, 'roll': 38.80744740949537, 'time': '2026-03-16T16:47:55.000002', 'wx': 7.1674570790492e-05, 'wy': -0.0009378587710671127, 'wz': -0.0005000680102966726, 'yaw': -34.70487602857855}, {'frame': 'GM2000', 'pitch': -55.12904739969731, 'q_0': -0.4108475, 'q_1': 0.3291059, 'q_2': -0.102416, 'q_3': 0.8440407, 'roll': 38.76535946512109, 'time': '2026-03-16T16:47:55.999998', 'wx': 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259974.0, 13.58421, 17.17076, 99996.08, 3.668005, 9.935549, 2.093246, 8.637241, 9.066045, 12.11973, 1.929122, 2.642891, 19.77823, 2.044533, 219979.3, 3.642163], 'max_rfi_psd': [22.79415, 0.0, 20.73992, 0.0, 0.0, 21.51024, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 32.18208, 0.0], 'noise_sensing_time': ['2026-03-16T16:47:52.722175', '2026-03-16T16:47:58.238731', '2026-03-16T16:48:03.755271', '2026-03-16T16:48:09.271827', '2026-03-16T16:48:14.788383', '2026-03-16T16:48:20.304939', '2026-03-16T16:47:53.799354', '2026-03-16T16:47:59.315910', '2026-03-16T16:48:04.832466', '2026-03-16T16:48:10.349021', '2026-03-16T16:48:15.865562', '2026-03-16T16:48:21.382118', '2026-03-16T16:47:54.648155', '2026-03-16T16:48:00.164710', '2026-03-16T16:48:05.681266', '2026-03-16T16:48:11.197822', '2026-03-16T16:48:16.714378', '2026-03-16T16:48:22.230934'], 'rfi_detected': ['true', 'false', 'true', 'false', 'false', 'true', 'false', 'false', 'false', 'false', 'false', 'false', 'false', 'false', 'false', 'false', 'true', 'false']}}}, 'swath_merging': {'swath_merge_list': [{'swath': 'IW1', 'swath_bounds_list': [{'azimuth_time': '2026-03-16T16:47:54.761834', 'first_azimuth_line': 0, 'first_range_sample': 0, 'last_azimuth_line': 16688, 'last_range_sample': 8871}]}, {'swath': 'IW2', 'swath_bounds_list': [{'azimuth_time': '2026-03-16T16:47:54.761834', 'first_azimuth_line': 0, 'first_range_sample': 8872, 'last_azimuth_line': 16688, 'last_range_sample': 17677}]}, {'swath': 'IW3', 'swath_bounds_list': [{'azimuth_time': '2026-03-16T16:47:54.761834', 'first_azimuth_line': 0, 'first_range_sample': 17678, 'last_azimuth_line': 16688, 'last_range_sample': 26641}]}]}, 'swath_timing': {'burst_list': {}, 'lines_per_burst': 0, 'samples_per_burst': 0}, 'timeliness_category': 'NRT-3h', 'title': 'S01SIWGRD'}
- processing_history :
- {'Level-0 Product': [{'facility': 'Unknown', 'inputs': [], 'outputs': ['Downlinked Stream'], 'processor': 'Unknown', 'time': '2026-03-16T16:44:59.039521Z', 'version': 'Unknown'}, {'facility': 'Unknown', 'inputs': [], 'outputs': ['Downlinked Stream'], 'processor': 'Unknown', 'time': '2026-03-16T16:45:26.324421Z', 'version': 'Unknown'}, {'facility': 'Unknown', 'inputs': ['S-1 Core PDGS S-1 Level-0 Product Format Specifications S1PD.SP.00110.ASTR', 'Sentinel-1 SAR Space Packet Protocol Data Unit S1-IF-ASD-PL-0007', 'Downlinked Stream'], 'outputs': ['Unknown'], 'processor': 'Unknown', 'time': '2026-03-16T17:07:12.306670Z', 'version': 'Unknown'}, {'facility': 'Unknown', 'inputs': ['S-1 Core PDGS S-1 Level-0 Product Format Specifications S1PD.SP.00110.ASTR', 'Sentinel-1 SAR Space Packet Protocol Data Unit S1-IF-ASD-PL-0007', 'Downlinked Stream'], 'outputs': ['Unknown'], 'processor': 'Unknown', 'time': '2026-03-16T17:12:02.055507Z', 'version': 'Unknown'}, {'facility': 'ESA-S1C-PS', 'inputs': ['S-1 Core PDGS S-1 Level-0 Product Format Specifications S1PD.SP.00110.ASTR', 'Sentinel-1 SAR Space Packet Protocol Data Unit S1-IF-ASD-PL-0007', 'Unknown', 'Unknown'], 'outputs': ['/data_pwa/cps/wd/eops-cps-pnode-s1-l1-0/IW_RAW__0_GRDH_1_4_03_IW_RAW__0_GRDH_1_4_03_301675188/S1C_IW_RAW__0SDV_20260316T164751_20260316T164823_006792_00DBA6_DA02.SAFE'], 'processor': '', 'time': '2026-03-16T17:15:28.685180Z', 'version': ''}], 'Level-1 Intermediate SLC Product': [{'adfs': ['/data_pwa/cps/wd/eops-cps-pnode-s1-l1-0/IW_RAW__0_GRDH_1_4_03_IW_RAW__0_GRDH_1_4_03_301675188/S1C_AUX_PP1_V20250427T000000_G20260203T152141.SAFE', '/data_pwa/cps/wd/eops-cps-pnode-s1-l1-0/IW_RAW__0_GRDH_1_4_03_IW_RAW__0_GRDH_1_4_03_301675188/S1C_AUX_CAL_V20250427T000000_G20260212T132118.SAFE', '/data_pwa/cps/wd/eops-cps-pnode-s1-l1-0/IW_RAW__0_GRDH_1_4_03_IW_RAW__0_GRDH_1_4_03_301675188/S1C_AUX_INS_V20250224T000000_G20251015T082332.SAFE', '/data_pwa/cps/wd/eops-cps-pnode-s1-l1-0/IW_RAW__0_GRDH_1_4_03_IW_RAW__0_GRDH_1_4_03_301675188/S1C_OPER_AUX_PREORB_OPOD_20260316T170705_V20260316T163717_20260316T231217.EOF'], 'facility': 'ESA-S1C-PS', 'inputs': ['/data_pwa/cps/wd/eops-cps-pnode-s1-l1-0/IW_RAW__0_GRDH_1_4_03_IW_RAW__0_GRDH_1_4_03_301675188/S1C_IW_RAW__0ADV_20260316T164201_20260316T165701_006792_00DBA6_2189.SAFE', '/data_pwa/cps/wd/eops-cps-pnode-s1-l1-0/IW_RAW__0_GRDH_1_4_03_IW_RAW__0_GRDH_1_4_03_301675188/S1C_IW_RAW__0CDV_20260316T164201_20260316T165701_006792_00DBA6_9E95.SAFE', '/data_pwa/cps/wd/eops-cps-pnode-s1-l1-0/IW_RAW__0_GRDH_1_4_03_IW_RAW__0_GRDH_1_4_03_301675188/S1C_IW_RAW__0NDV_20260316T164201_20260316T165701_006792_00DBA6_97E5.SAFE', '/data_pwa/cps/wd/eops-cps-pnode-s1-l1-0/IW_RAW__0_GRDH_1_4_03_IW_RAW__0_GRDH_1_4_03_301675188/S1C_IW_RAW__0SDV_20260316T164751_20260316T164823_006792_00DBA6_DA02.SAFE', 'Sentinel-1 Product Definition (S1-RS-MDA-52-7440) release 2/7', 'Sentinel-1 Product Specification (S1-RS-MDA-52-7441) release 3/14'], 'outputs': ['S1C_IW_SL1__1_DV_20260316T164751_20260316T164824_006792_00DBA6_1763.SAFE'], 'processor': 'Sentinel-1 IPF', 'time': '2026-03-16T17:55:39.000000Z', 'version': '004.03'}], 'Level-1 Product': [{'facility': 'ESA-S1C-PS', 'inputs': ['S1C_IW_SL1__1_DV_20260316T164751_20260316T164824_006792_00DBA6_1763.SAFE'], 'outputs': ['S1C_IW_GRDH_1SDV_20260316T164754_20260316T164819_006792_00DBA6_8EA0.SAFE'], 'processor': 'Sentinel-1 IPF', 'time': '2026-03-16T17:57:14.000000Z', 'version': '004.03'}, {'facility': 'CS-SopraSteria', 'inputs': ['S1C_IW_GRDH_1SDV_20260316T164754_20260316T164819_006792_00DBA6_8EA0.SAFE'], 'outputs': ['S1C_IW_GRDH_1SDV_20260316T164754_20260316T164819_006792_00DBA6_8EA0.zarr.zarr'], 'processor': 'EOPF-CPM', 'time': '2026-03-16T18:51:01.944012Z', 'version': '2.6.2'}]}
- stac_discovery :
- {'assets': {}, 'bbox': [18.688345, 39.213028, 15.261218, 41.126934], 'detectionPerformed': 'true', 'geometry': {'coordinates': [[[15.261218, 40.715069], [18.376741, 41.126934], [18.688345, 39.626194], [15.640784, 39.213028], [15.261218, 40.715069]]], 'type': 'Polygon'}, 'id': 'S01SIWGRD_20260316T164754_0024_C146_T1CE', 'links': [{'href': './.zattrs.json', 'rel': 'self', 'type': 'application/json'}], 'properties': {'constellation': 'sentinel-1', 'created': '2026-03-16T17:57:14.000000Z', 'datetime': 'None', 'end_datetime': '2026-03-16T16:48:19.760381Z', 'instruments': ['sar'], 'platform': 'sentinel-1c', 'processing:software': {'Sentinel-1 IPF': '004.03'}, 'processing:version': '004.00', 'product:timeliness': 'PT3H', 'product:timeliness_category': 'NRT-3h', 'product:type': 'S01SIWGRD', 'sar:center_frequency': 5405000454.33435, 'sar:frequency_band': 'C', 'sar:instrument_mode': 'IW', 'sar:pixel_spacing_azimuth': 10.0, 'sar:pixel_spacing_range': 10.0, 'sat:absolute_orbit': 6792, 'sat:anx_datetime': '2026-03-16T16:37:16.668595', 'sat:orbit_state': 'ascending', 'sat:platform_international_designator': '2024-235A', 'sat:relative_orbit': 146, 'start_datetime': '2026-03-16T16:47:54.761834Z', 'view:incidence_angle': 39.13511618906348}, 'stac_extensions': ['https://stac-extensions.github.io/eopf/v1.2.0/schema.json', 'https://stac-extensions.github.io/product/v0.1.0/schema.json', 'https://stac-extensions.github.io/eo/v1.1.0/schema.json', 'https://stac-extensions.github.io/sat/v1.1.0/schema.json', 'https://stac-extensions.github.io/view/v1.0.0/schema.json', 'https://stac-extensions.github.io/scientific/v1.0.0/schema.json', 'https://stac-extensions.github.io/processing/v1.2.0/schema.json', 'https://stac-extensions.github.io/sar/v1.2.0/schema.json'], 'stac_version': '1.1.0', 'thermalNoiseCorrectionPerformed': 'false', 'type': 'Feature'}
- " - ], - "text/plain": [ - "
- other_metadata :
- {'eopf_category': 'eocontainer', 'title': 'S01SIWGRD'}
- stac_discovery :
- {'assets': {'S01SIWGRD_20260316T164754_0025_C039_8EA0_00DBA6_VH': {'href': 'S01SIWGRD_20260316T164754_0025_C039_8EA0_00DBA6_VH'}, 'S01SIWGRD_20260316T164754_0025_C039_8EA0_00DBA6_VV': {'href': 'S01SIWGRD_20260316T164754_0025_C039_8EA0_00DBA6_VV'}}, 'bbox': [18.688345, 39.213028, 15.261218, 41.126934], 'geometry': {'coordinates': [[[15.261218, 40.715069], [18.376741, 41.126934], [18.688345, 39.626194], [15.640784, 39.213028], [15.261218, 40.715069]]], 'type': 'Polygon'}, 'id': 'SAR Standard L1 Product', 'links': [{'href': './.zattrs.json', 'rel': 'self', 'type': 'application/json'}], 'properties': {'constellation': 'sentinel-1', 'created': '2026-03-16T17:57:14.000000Z', 'datetime': '2026-03-16T16:48:07.261108Z', 'end_datetime': '2026-03-16T16:48:19.760381Z', 'eopf:datatake_id': '56230', 'eopf:instrument_mode': 'IW', 'instruments': ['sar'], 'platform': 'sentinel-1c', 'processing:lineage': 'systematic', 'processing:software': {'Sentinel-1 IPF': '004.03'}, 'product:timeliness': 'PT3H', 'product:timeliness_category': 'NRT-3h', 'product:type': 'S01SIWGRD', 'provider': [{'name': 'S1C-PS', 'roles': ['processor']}, {'name': 'ESA', 'roles': ['producer']}], 'sar:frequency_band': 'C', 'sar:instrument_mode': 'IW', 'sar:polarizations': ['VV', 'VH'], 'sar:product_type': 'GRD', 'sat:absolute_orbit': 6792, 'sat:anx_datetime': '2026-03-16T16:37:16.668595', 'sat:orbit_state': 'ascending', 'sat:platform_international_designator': '2024-235A', 'sat:relative_orbit': 146, 'start_datetime': '2026-03-16T16:47:54.761834Z'}, 'stac_extensions': ['https://stac-extensions.github.io/eopf/v1.2.0/schema.json', 'https://stac-extensions.github.io/product/v0.1.0/schema.json', 'https://stac-extensions.github.io/eo/v1.1.0/schema.json', 'https://stac-extensions.github.io/sat/v1.1.0/schema.json', 'https://stac-extensions.github.io/view/v1.0.0/schema.json', 'https://stac-extensions.github.io/scientific/v1.0.0/schema.json', 'https://stac-extensions.github.io/processing/v1.2.0/schema.json', 'https://stac-extensions.github.io/sar/v1.2.0/schema.json'], 'stac_version': '1.1.0', 'type': 'Feature'}
\n", - "Group: /\n", - "│ Attributes: (2)\n", - "├── Group: /S01SIWGRD_20260316T164754_0025_C039_8EA0_00DBA6_VH\n", - "│ │ Attributes: (3)\n", - "│ ├── Group: /S01SIWGRD_20260316T164754_0025_C039_8EA0_00DBA6_VH/conditions\n", - "│ │ ├── Group: /S01SIWGRD_20260316T164754_0025_C039_8EA0_00DBA6_VH/conditions/antenna_pattern\n", - "│ │ │ Dimensions: (azimuth_time: 27, count: 730)\n", - "│ │ │ Coordinates:\n", - "│ │ │ * azimuth_time (azimuth_time) datetime64[ns] 216B 2026-03-16T16:47:...\n", - "│ │ │ * count (count) int64 6kB 0 1 2 3 4 5 ... 725 726 727 728 729\n", - "│ │ │ Data variables:\n", - "│ │ │ elevation_angle (azimuth_time, count) float32 79kB dask.array \n", - "│ │ │ incidence_angle (azimuth_time, count) float32 79kB dask.array \n", - "│ │ │ roll (azimuth_time) float64 216B dask.array \n", - "│ │ │ slant_range_time_ap (azimuth_time, count) float64 158kB dask.array \n", - "│ │ │ swath (azimuth_time) \n", - "│ │ │ terrain_height (azimuth_time) float64 216B dask.array \n", - "│ │ ├── Group: /S01SIWGRD_20260316T164754_0025_C039_8EA0_00DBA6_VH/conditions/attitude\n", - "│ │ │ Dimensions: (azimuth_time: 25)\n", - "│ │ │ Coordinates:\n", - "│ │ │ * azimuth_time (azimuth_time) datetime64[ns] 200B 2026-03-16T16:47:55.0000...\n", - "│ │ │ Data variables:\n", - "│ │ │ pitch (azimuth_time) float64 200B dask.array \n", - "│ │ │ q0 (azimuth_time) float32 100B dask.array \n", - "│ │ │ q1 (azimuth_time) float32 100B dask.array \n", - "│ │ │ q2 (azimuth_time) float32 100B dask.array \n", - "│ │ │ q3 (azimuth_time) float32 100B dask.array \n", - "│ │ │ roll (azimuth_time) float64 200B dask.array \n", - "│ │ │ wx (azimuth_time) float64 200B dask.array \n", - "│ │ │ wy (azimuth_time) float64 200B dask.array \n", - "│ │ │ wz (azimuth_time) float64 200B dask.array \n", - "│ │ │ yaw (azimuth_time) float64 200B dask.array \n", - "│ │ ├── Group: /S01SIWGRD_20260316T164754_0025_C039_8EA0_00DBA6_VH/conditions/doppler_centroid\n", - "│ │ │ Dimensions: (azimuth_time: 27, degree: 3)\n", - "│ │ │ Coordinates:\n", - "│ │ │ * azimuth_time (azimuth_time) datetime64[ns] 216B 202...\n", - "│ │ │ * degree (degree) int64 24B 2 1 0\n", - "│ │ │ Data variables:\n", - "│ │ │ data_dc_polynomial (azimuth_time, degree) float32 324B dask.array \n", - "│ │ │ data_dc_rms_error (azimuth_time) float64 216B dask.array \n", - "│ │ │ data_dc_rms_error_above_threshold (azimuth_time) bool 27B dask.array \n", - "│ │ │ fine_dce_azimuth_start_time (azimuth_time) bool 27B dask.array \n", - "│ │ │ fine_dce_azimuth_stop_time (azimuth_time) bool 27B dask.array \n", - "│ │ │ geometry_dc_polynomial (azimuth_time, degree) float32 324B dask.array \n", - "│ │ │ t0 (azimuth_time) float64 216B dask.array \n", - "│ │ ├── Group: /S01SIWGRD_20260316T164754_0025_C039_8EA0_00DBA6_VH/conditions/gcp\n", - "│ │ │ Dimensions: (azimuth_time: 10, ground_range: 21)\n", - "│ │ │ Coordinates:\n", - "│ │ │ * azimuth_time (azimuth_time) datetime64[ns] 80B 2026-03-16T16:47:...\n", - "│ │ │ * ground_range (ground_range) float64 168B 0.0 ... 2.664e+05\n", - "│ │ │ line (azimuth_time) uint32 40B dask.array \n", - "│ │ │ pixel (ground_range) uint32 84B dask.array \n", - "│ │ │ Data variables:\n", - "│ │ │ azimuth_time_gcp (azimuth_time, ground_range) datetime64[ns] 2kB dask.array \n", - "│ │ │ elevation_angle (azimuth_time, ground_range) float64 2kB dask.array \n", - "│ │ │ height (azimuth_time, ground_range) float64 2kB dask.array