Sentinel-1 Coherence

Product description

The Sentinel-1 Coherence product available in the SALDi Data Cube (SDC) has been sourced from the Alaska Satellite Facility (ASF) using their On Demand InSAR products. The product was generated for VV-polarization and ascending orbits only.

Detailed information can be found here.

The product abbreviation used in this package is s1_coh

Loading data

from sdc.load import load_product

vec = "../../_assets/vec_01_06_01.geojson"
ds = load_product(product="s1_coh", vec=vec)
ds

<xarray.DataArray 'coh_vv' (time: 175, latitude: 1450, longitude: 1987)>
dask.array<coh_vv, shape=(175, 1450, 1987), dtype=float32, chunksize=(175, 437, 437), chunktype=numpy.ndarray>
Coordinates:
  * latitude     (latitude) float64 -29.0 -29.0 -29.0 ... -29.29 -29.29 -29.29
  * longitude    (longitude) float64 24.31 24.31 24.31 24.31 ... 24.7 24.7 24.7
    spatial_ref  int32 4326
  * time         (time) datetime64[ns] 2018-01-11T17:02:23 ... 2023-10-24T17:...
Attributes:
    nodata:   0.0

xarray.DataArray

'coh_vv'

• time: 175
• latitude: 1450
• longitude: 1987

• dask.array<chunksize=(175, 437, 437), meta=np.ndarray>

  Array Chunk Bytes 1.88 GiB 127.49 MiB Shape (175, 1450, 1987) (175, 437, 437) Dask graph 20 chunks in 1 graph layer Data type float32 numpy.ndarray

• Coordinates: (4)
  • latitude
    (latitude)
    float64
    -29.0 -29.0 -29.0 ... -29.29 -29.29

    units :

    degrees_north

    resolution :

    -0.0002

    crs :

    EPSG:4326

    array([-29.0025, -29.0027, -29.0029, ..., -29.2919, -29.2921, -29.2923])

  • longitude
    (longitude)
    float64
    24.31 24.31 24.31 ... 24.7 24.7

    units :

    degrees_east

    resolution :

    0.0002

    crs :

    EPSG:4326

    array([24.3057, 24.3059, 24.3061, ..., 24.7025, 24.7027, 24.7029])

  • spatial_ref
    ()
    int32
    4326

    spatial_ref :

    GEOGCRS["WGS 84",ENSEMBLE["World Geodetic System 1984 ensemble",MEMBER["World Geodetic System 1984 (Transit)"],MEMBER["World Geodetic System 1984 (G730)"],MEMBER["World Geodetic System 1984 (G873)"],MEMBER["World Geodetic System 1984 (G1150)"],MEMBER["World Geodetic System 1984 (G1674)"],MEMBER["World Geodetic System 1984 (G1762)"],MEMBER["World Geodetic System 1984 (G2139)"],ELLIPSOID["WGS 84",6378137,298.257223563,LENGTHUNIT["metre",1]],ENSEMBLEACCURACY[2.0]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433]],CS[ellipsoidal,2],AXIS["geodetic latitude (Lat)",north,ORDER[1],ANGLEUNIT["degree",0.0174532925199433]],AXIS["geodetic longitude (Lon)",east,ORDER[2],ANGLEUNIT["degree",0.0174532925199433]],USAGE[SCOPE["Horizontal component of 3D system."],AREA["World."],BBOX[-90,-180,90,180]],ID["EPSG",4326]]

    crs_wkt :

    GEOGCRS["WGS 84",ENSEMBLE["World Geodetic System 1984 ensemble",MEMBER["World Geodetic System 1984 (Transit)"],MEMBER["World Geodetic System 1984 (G730)"],MEMBER["World Geodetic System 1984 (G873)"],MEMBER["World Geodetic System 1984 (G1150)"],MEMBER["World Geodetic System 1984 (G1674)"],MEMBER["World Geodetic System 1984 (G1762)"],MEMBER["World Geodetic System 1984 (G2139)"],ELLIPSOID["WGS 84",6378137,298.257223563,LENGTHUNIT["metre",1]],ENSEMBLEACCURACY[2.0]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433]],CS[ellipsoidal,2],AXIS["geodetic latitude (Lat)",north,ORDER[1],ANGLEUNIT["degree",0.0174532925199433]],AXIS["geodetic longitude (Lon)",east,ORDER[2],ANGLEUNIT["degree",0.0174532925199433]],USAGE[SCOPE["Horizontal component of 3D system."],AREA["World."],BBOX[-90,-180,90,180]],ID["EPSG",4326]]

    semi_major_axis :

    6378137.0

    semi_minor_axis :

    6356752.314245179

    inverse_flattening :

    298.257223563

    reference_ellipsoid_name :

    WGS 84

    longitude_of_prime_meridian :

    0.0

    prime_meridian_name :

    Greenwich

    geographic_crs_name :

    WGS 84

    horizontal_datum_name :

    World Geodetic System 1984 ensemble

    grid_mapping_name :

    latitude_longitude

    GeoTransform :

    24.305600000000002 0.0002 0.0 -29.0024 0.0 -0.0002

    array(4326, dtype=int32)

  • time
    (time)
    datetime64[ns]
    2018-01-11T17:02:23 ... 2023-10-...

    array(['2018-01-11T17:02:23.000000000', '2018-01-23T17:02:23.000000000',
           '2018-02-04T17:02:23.000000000', '2018-02-16T17:02:22.000000000',
           '2018-02-28T17:02:22.000000000', '2018-03-12T17:02:22.000000000',
           '2018-03-24T17:02:23.000000000', '2018-04-05T17:02:23.000000000',
           '2018-04-17T17:02:23.000000000', '2018-04-29T17:02:24.000000000',
           '2018-05-11T17:02:25.000000000', '2018-05-23T17:02:25.000000000',
           '2018-06-04T17:02:26.000000000', '2018-06-16T17:02:27.000000000',
           '2018-06-28T17:02:27.000000000', '2018-07-10T17:02:28.000000000',
           '2018-07-22T17:02:29.000000000', '2018-08-03T17:02:29.000000000',
           '2018-08-15T17:02:30.000000000', '2018-08-27T17:02:31.000000000',
           '2018-09-08T17:02:32.000000000', '2018-09-20T17:02:32.000000000',
           '2018-10-02T17:02:32.000000000', '2018-10-14T17:02:32.000000000',
           '2018-10-26T17:02:32.000000000', '2018-11-07T17:02:32.000000000',
           '2018-11-19T17:02:32.000000000', '2018-12-01T17:02:31.000000000',
           '2018-12-13T17:02:31.000000000', '2018-12-25T17:02:31.000000000',
           '2019-01-06T17:02:30.000000000', '2019-01-18T17:02:30.000000000',
           '2019-01-30T17:02:29.000000000', '2019-02-11T17:02:29.000000000',
           '2019-02-23T17:02:29.000000000', '2019-03-07T17:02:29.000000000',
           '2019-03-19T17:02:29.000000000', '2019-03-31T17:02:29.000000000',
           '2019-04-12T17:02:29.000000000', '2019-04-24T17:02:30.000000000',
           '2019-04-30T17:01:47.000000000', '2019-05-06T17:02:30.000000000',
           '2019-05-18T17:02:31.000000000', '2019-05-30T17:02:32.000000000',
           '2019-06-11T17:02:32.000000000', '2019-06-23T17:02:33.000000000',
           '2019-07-05T17:02:34.000000000', '2019-07-17T17:02:35.000000000',
           '2019-07-29T17:02:35.000000000', '2019-08-10T17:02:36.000000000',
           '2019-08-22T17:02:37.000000000', '2019-09-03T17:02:37.000000000',
           '2019-09-15T17:02:38.000000000', '2019-09-27T17:02:38.000000000',
           '2019-10-09T17:02:38.000000000', '2019-10-21T17:02:38.000000000',
           '2019-11-02T17:02:39.000000000', '2019-11-14T17:02:38.000000000',
           '2019-11-26T17:02:38.000000000', '2019-12-08T17:02:38.000000000',
           '2019-12-20T17:02:37.000000000', '2020-01-01T17:02:37.000000000',
           '2020-01-13T17:02:36.000000000', '2020-01-25T17:02:36.000000000',
           '2020-02-06T17:02:35.000000000', '2020-02-18T17:02:35.000000000',
           '2020-03-01T17:02:35.000000000', '2020-03-13T17:02:35.000000000',
           '2020-03-25T17:02:35.000000000', '2020-04-06T17:02:36.000000000',
           '2020-04-18T17:02:36.000000000', '2020-04-30T17:02:37.000000000',
           '2020-05-12T17:02:37.000000000', '2020-05-24T17:02:38.000000000',
           '2020-06-05T17:02:39.000000000', '2020-06-17T17:02:39.000000000',
           '2020-06-29T17:02:40.000000000', '2020-07-11T17:02:41.000000000',
           '2020-07-23T17:02:42.000000000', '2020-08-04T17:02:42.000000000',
           '2020-08-16T17:02:43.000000000', '2020-08-28T17:02:44.000000000',
           '2020-09-09T17:02:44.000000000', '2020-09-21T17:02:45.000000000',
           '2020-10-03T17:02:45.000000000', '2020-10-15T17:02:45.000000000',
           '2020-10-27T17:02:45.000000000', '2020-11-08T17:02:45.000000000',
           '2020-11-20T17:02:45.000000000', '2020-12-02T17:02:44.000000000',
           '2020-12-14T17:02:44.000000000', '2020-12-26T17:02:43.000000000',
           '2021-01-07T17:02:42.000000000', '2021-01-19T17:02:42.000000000',
           '2021-01-31T17:02:42.000000000', '2021-02-12T17:02:41.000000000',
           '2021-02-24T17:02:41.000000000', '2021-03-08T17:02:41.000000000',
           '2021-03-20T17:02:41.000000000', '2021-04-01T17:02:41.000000000',
           '2021-04-13T17:02:42.000000000', '2021-04-25T17:02:42.000000000',
           '2021-05-07T17:02:43.000000000', '2021-05-19T17:02:43.000000000',
           '2021-05-31T17:02:44.000000000', '2021-06-12T17:02:45.000000000',
           '2021-06-24T17:02:46.000000000', '2021-07-06T17:02:46.000000000',
           '2021-07-18T17:02:47.000000000', '2021-07-30T17:02:48.000000000',
           '2021-08-11T17:02:48.000000000', '2021-08-23T17:02:49.000000000',
           '2021-09-04T17:02:50.000000000', '2021-09-16T17:02:50.000000000',
           '2021-09-28T17:02:51.000000000', '2021-10-10T17:02:51.000000000',
           '2021-11-15T17:02:50.000000000', '2021-11-27T17:02:50.000000000',
           '2021-12-09T17:02:49.000000000', '2021-12-21T17:02:49.000000000',
           '2022-01-02T17:02:48.000000000', '2022-01-14T17:02:48.000000000',
           '2022-01-26T17:02:47.000000000', '2022-02-07T17:02:47.000000000',
           '2022-02-19T17:02:47.000000000', '2022-03-03T17:02:46.000000000',
           '2022-03-15T17:02:47.000000000', '2022-03-27T17:02:47.000000000',
           '2022-04-08T17:02:47.000000000', '2022-04-20T17:02:48.000000000',
           '2022-05-02T17:02:48.000000000', '2022-05-14T17:02:46.000000000',
           '2022-05-26T17:02:47.000000000', '2022-06-07T17:02:48.000000000',
           '2022-06-19T17:02:49.000000000', '2022-07-01T17:02:50.000000000',
           '2022-07-13T17:02:50.000000000', '2022-07-25T17:02:51.000000000',
           '2022-08-06T17:02:52.000000000', '2022-08-18T17:02:52.000000000',
           '2022-08-30T17:02:53.000000000', '2022-09-23T17:02:53.000000000',
           '2022-10-05T17:02:54.000000000', '2022-10-17T17:02:54.000000000',
           '2022-10-29T17:02:54.000000000', '2022-11-10T17:02:53.000000000',
           '2022-11-22T17:02:54.000000000', '2022-12-04T17:02:53.000000000',
           '2022-12-16T17:02:52.000000000', '2022-12-28T17:02:52.000000000',
           '2023-01-09T17:02:51.000000000', '2023-01-21T17:02:51.000000000',
           '2023-02-02T17:02:50.000000000', '2023-02-14T17:02:52.000000000',
           '2023-02-26T17:02:53.000000000', '2023-03-10T17:02:52.000000000',
           '2023-03-22T17:02:52.000000000', '2023-04-03T17:02:53.000000000',
           '2023-04-15T17:02:53.000000000', '2023-04-27T17:02:54.000000000',
           '2023-05-09T17:02:54.000000000', '2023-05-21T17:02:55.000000000',
           '2023-06-02T17:02:56.000000000', '2023-06-14T17:02:56.000000000',
           '2023-06-26T17:02:56.000000000', '2023-07-08T17:02:58.000000000',
           '2023-07-20T17:02:58.000000000', '2023-08-01T17:02:59.000000000',
           '2023-08-13T17:02:59.000000000', '2023-08-25T17:03:00.000000000',
           '2023-09-06T17:03:01.000000000', '2023-09-18T17:03:02.000000000',
           '2023-09-30T17:03:02.000000000', '2023-10-12T17:03:01.000000000',
           '2023-10-24T17:03:02.000000000'], dtype='datetime64[ns]')

• Indexes: (3)
  • latitude
    PandasIndex

    PandasIndex(Index([           -29.0025,            -29.0027,            -29.0029,
                      -29.0031, -29.003300000000003, -29.003500000000003,
           -29.003700000000002,            -29.0039,            -29.0041,
                      -29.0043,
           ...
                      -29.2905,            -29.2907,            -29.2909,
                      -29.2911,            -29.2913, -29.291500000000003,
           -29.291700000000002, -29.291900000000002,            -29.2921,
                      -29.2923],
          dtype='float64', name='latitude', length=1450))

  • longitude
    PandasIndex

    PandasIndex(Index([           24.3057,            24.3059,            24.3061,
                      24.3063, 24.306500000000003, 24.306700000000003,
           24.306900000000002, 24.307100000000002,            24.3073,
                      24.3075,
           ...
                      24.7011, 24.701300000000003, 24.701500000000003,
           24.701700000000002, 24.701900000000002,            24.7021,
                      24.7023,            24.7025,            24.7027,
           24.702900000000003],
          dtype='float64', name='longitude', length=1987))

  • time
    PandasIndex

    PandasIndex(DatetimeIndex(['2018-01-11 17:02:23', '2018-01-23 17:02:23',
                   '2018-02-04 17:02:23', '2018-02-16 17:02:22',
                   '2018-02-28 17:02:22', '2018-03-12 17:02:22',
                   '2018-03-24 17:02:23', '2018-04-05 17:02:23',
                   '2018-04-17 17:02:23', '2018-04-29 17:02:24',
                   ...
                   '2023-07-08 17:02:58', '2023-07-20 17:02:58',
                   '2023-08-01 17:02:59', '2023-08-13 17:02:59',
                   '2023-08-25 17:03:00', '2023-09-06 17:03:01',
                   '2023-09-18 17:03:02', '2023-09-30 17:03:02',
                   '2023-10-12 17:03:01', '2023-10-24 17:03:02'],
                  dtype='datetime64[ns]', name='time', length=175, freq=None))

• Attributes: (1)

  nodata :

  0.0

Let’s visualize the standard deviation for the whole time series:

coh_std = ds.std(dim="time").compute()

coh_std.plot()

<matplotlib.collections.QuadMesh at 0x7f464e257b90>