Download this notebook from github.

---

Open multiples datasets

Some safe files have multiples subdatasets, like WV or IW_SLC. This notebook show how to handle them, or how to handle multiple datasets.

import xsar
import xarray as xr
import glob
import holoviews as hv
import geoviews as gv
hv.extension('bokeh')

/home/datawork-cersat-public/cache/project/mpc-sentinel1/workspace/mamba/envs/testgeoviewsnumpy/lib/python3.11/site-packages/dask/dataframe/__init__.py:42: FutureWarning:
Dask dataframe query planning is disabled because dask-expr is not installed.

You can install it with `pip install dask[dataframe]` or `conda install dask`.
This will raise in a future version.

  warnings.warn(msg, FutureWarning)

SAFES containings multiples subdatasets like WV_SLC cannot be openned with xsar.open_dataset given the safe path.

try:
    wv_slc_ds = xsar.open_dataset(xsar.get_test_file('S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE'))
except IndexError as e:
    print(str(e))

/home1/datahome/agrouaze/sources/git/xsar/src/xsar/xsar.py:212: UserWarning: Downloading https://cyclobs.ifremer.fr/static/sarwing_datarmor/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE.zip
  warnings.warn("Downloading %s" % file_url)
/home1/datahome/agrouaze/sources/git/xsar/src/xsar/xsar.py:214: UserWarning: Unzipping /home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE
  warnings.warn("Unzipping %s" % os.path.join(res_path, fname))

multidataset
Can't open an multi-dataset. Use `xsar.Sentinel1Meta('/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE').subdatasets` to show availables ones

An IndexError is raised, with an advice to use xsar.Sentinel1Meta to get the available subdatasets list.

wv_slc_meta = xsar.Sentinel1Meta(xsar.get_test_file('S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE'))
wv_slc_meta

multidataset

<Sentinel1Meta multi (24) object>

Note that the abose wv_slc_meta object is a multi dataset

Subdatasets list is available with xsar.Sentinel1Meta.subdatasets property

wv_slc_meta.subdatasets

	geometry
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_001	POLYGON ((-59.85301 41.55527, -60.09758 41.592...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_002	POLYGON ((-62.25718 40.99591, -62.49659 41.028...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_003	POLYGON ((-60.32554 39.79482, -60.56392 39.832...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_004	POLYGON ((-62.67301 39.23473, -62.90617 39.267...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_005	POLYGON ((-60.78958 38.03459, -61.02192 38.071...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_006	POLYGON ((-63.07917 37.47335, -63.30661 37.505...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_007	POLYGON ((-61.24056 36.27251, -61.46734 36.309...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_008	POLYGON ((-63.47426 35.71019, -63.69651 35.742...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_009	POLYGON ((-61.67968 34.5095, -61.90138 34.5464...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_010	POLYGON ((-63.86507 33.94662, -64.0825 33.9794...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_011	POLYGON ((-62.10818 32.74584, -62.32521 32.782...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_012	POLYGON ((-64.24941 32.18295, -64.46241 32.215...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_013	POLYGON ((-62.52305 30.98017, -62.73606 31.016...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_014	POLYGON ((-64.62841 30.41779, -64.83735 30.450...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_015	POLYGON ((-62.93453 29.21381, -63.14361 29.250...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_016	POLYGON ((-65.00266 28.65192, -65.20787 28.685...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_017	POLYGON ((-63.33859 27.44647, -63.54408 27.483...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_018	POLYGON ((-65.37115 26.88431, -65.57301 26.917...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_019	POLYGON ((-63.73628 25.67826, -63.93849 25.715...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_020	POLYGON ((-65.73824 25.11662, -65.93698 25.150...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_021	POLYGON ((-64.12556 23.90869, -64.32495 23.945...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_022	POLYGON ((-66.10242 23.3486, -66.29834 23.3826...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_023	POLYGON ((-64.51285 22.13895, -64.70954 22.175...
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_024	POLYGON ((-66.46441 21.57984, -66.65776 21.614...

A subdataset can be directly be opened by xsar.open_dataset

wv_slc_ds1 = xsar.open_dataset(wv_slc_meta.subdatasets.index[0])
wv_slc_ds1

/home/datawork-cersat-public/cache/project/mpc-sentinel1/workspace/mamba/envs/testgeoviewsnumpy/lib/python3.11/site-packages/dask/array/utils.py:105: ComplexWarning: Casting complex values to real discards the imaginary part
  meta = meta.astype(dtype)

<xarray.Dataset> Size: 448MB
Dimensions:         (line: 4923, sample: 5681, pol: 1)
Coordinates:
  * line            (line) int64 39kB 0 1 2 3 4 5 ... 4918 4919 4920 4921 4922
  * sample          (sample) int64 45kB 0 1 2 3 4 5 ... 5676 5677 5678 5679 5680
  * pol             (pol) object 8B 'VV'
Data variables:
    digital_number  (pol, line, sample) complex128 447MB dask.array<chunksize=(1, 4923, 5000), meta=np.ndarray>
    time            (line) datetime64[ns] 39kB 2016-05-10T10:16:03.843409920 ...
    sampleSpacing   float64 8B 1.498
    lineSpacing     float64 8B 4.125
Attributes: (12/15)
    name:              SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsar...
    short_name:        SENTINEL1_DS:S1A_WV_SLC__1SSV_20160510T101603_20160510...
    product:           SLC
    safe:              S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_01119...
    swath:             WV
    multidataset:      False
    ...                ...
    start_date:        2016-05-10 10:16:03.843410
    stop_date:         2016-05-10 10:16:06.826137
    footprint:         POLYGON ((-59.80263505017974 41.73435353976264, -60.04...
    coverage:          20km * 20km (line * sample )
    orbit_pass:        Descending
    platform_heading:  -166.3012322109123

xarray.Dataset

• Dimensions:
  • line: 4923
  • sample: 5681
  • pol: 1
• Coordinates: (3)
  • line
    (line)
    int64
    0 1 2 3 4 ... 4919 4920 4921 4922

    array([   0,    1,    2, ..., 4920, 4921, 4922])

  • sample
    (sample)
    int64
    0 1 2 3 4 ... 5677 5678 5679 5680

    array([   0,    1,    2, ..., 5678, 5679, 5680])

  • pol
    (pol)
    object
    'VV'

    array(['VV'], dtype=object)

• Data variables: (4)
  • digital_number
    (pol, line, sample)
    complex128
    dask.array<chunksize=(1, 4923, 5000), meta=np.ndarray>

    comment :

    denoised digital number, read at full resolution

    history :

    digital_number: measurement/s1a-wv1-slc-vv-20160510t101603-20160510t101606-011195-010ea1-001.tiff

    Array Chunk Bytes 426.75 MiB 375.60 MiB Shape (1, 4923, 5681) (1, 4923, 5000) Dask graph 2 chunks in 2 graph layers Data type complex128 numpy.ndarray

  • time
    (line)
    datetime64[ns]
    2016-05-10T10:16:03.843409920 .....

    description :

    azimuth times interpolated along line dimension at the middle of range dimension

    array(['2016-05-10T10:16:03.843409920', '2016-05-10T10:16:03.844015872',
           '2016-05-10T10:16:03.844621824', ...,
           '2016-05-10T10:16:06.824925184', '2016-05-10T10:16:06.825531136',
           '2016-05-10T10:16:06.826137088'], dtype='datetime64[ns]')

  • sampleSpacing
    ()
    float64
    1.498

    units :

    m

    referential :

    slant

    array(1.497576)

  • lineSpacing
    ()
    float64
    4.125

    units :

    m

    array(4.124774)

• Indexes: (3)
  • line
    PandasIndex

    PandasIndex(RangeIndex(start=0, stop=4923, step=1, name='line'))

  • sample
    PandasIndex

    PandasIndex(RangeIndex(start=0, stop=5681, step=1, name='sample'))

  • pol
    PandasIndex

    PandasIndex(Index(['VV'], dtype='object', name='pol'))

• Attributes: (15)

  name :

  SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_001

  short_name :

  SENTINEL1_DS:S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_001

  product :

  SLC

  safe :

  S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE

  swath :

  WV

  multidataset :

  False

  ipf :

  2.7

  platform :

  SENTINEL-1A

  pols :

  VV

  start_date :

  2016-05-10 10:16:03.843410

  stop_date :

  2016-05-10 10:16:06.826137

  footprint :

  POLYGON ((-59.80263505017974 41.73435353976264, -60.04794367802916 41.77204176347002, -60.09752876528052 41.59309352477252, -59.85296208623707 41.55544353659125, -59.80263505017974 41.73435353976264))

  coverage :

  20km * 20km (line * sample )

  orbit_pass :

  Descending

  platform_heading :

  -166.3012322109123

Or we can get a single dataset by using xsar.Sentinel1Meta

wv_slc_meta1 = xsar.Sentinel1Meta(wv_slc_meta.subdatasets.index[0])
wv_slc_meta1

<Sentinel1Meta single object>

And use this wv_slc_meta1 object with xsar.open_dataset

wv_slc_ds1 = xsar.open_dataset(wv_slc_meta1)

/home/datawork-cersat-public/cache/project/mpc-sentinel1/workspace/mamba/envs/testgeoviewsnumpy/lib/python3.11/site-packages/dask/array/utils.py:105: ComplexWarning: Casting complex values to real discards the imaginary part
  meta = meta.astype(dtype)

Getting all xsar.Sentinel1Meta objects from a list of path

xsar.Sentinel1Meta can only handle one path at a time.

With xsar.product_info, you can provide a list of path, and get a pandas.DataFrame with all meta objects.

df_info = xsar.product_info([
    xsar.get_test_file('S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE'),
    xsar.get_test_file('S1A_IW_SLC__1SDV_20170907T102951_20170907T103021_018268_01EB76_Z010.SAFE')
])
df_info

/home1/datahome/agrouaze/sources/git/xsar/src/xsar/xsar.py:212: UserWarning: Downloading https://cyclobs.ifremer.fr/static/sarwing_datarmor/xsardata/S1A_IW_SLC__1SDV_20170907T102951_20170907T103021_018268_01EB76_Z010.SAFE.zip
  warnings.warn("Downloading %s" % file_url)
/home1/datahome/agrouaze/sources/git/xsar/src/xsar/xsar.py:214: UserWarning: Unzipping /home1/scratch/agrouaze/xsardatasync/xsardata/S1A_IW_SLC__1SDV_20170907T102951_20170907T103021_018268_01EB76_Z010.SAFE
  warnings.warn("Unzipping %s" % os.path.join(res_path, fname))

multidataset
multidataset

		name	ipf	platform	swath	product	pols	meta
path	dsid
/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE	WV_001	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_002	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_003	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_004	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_005	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_006	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_007	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_008	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_009	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_010	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_011	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_012	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_013	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_014	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_015	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_016	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_017	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_018	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_019	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_020	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_021	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_022	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_023	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
	WV_024	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.7	SENTINEL-1A	WV	SLC	VV	<Sentinel1Meta single object>
/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_IW_SLC__1SDV_20170907T102951_20170907T103021_018268_01EB76_Z010.SAFE	IW1	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.84	SENTINEL-1A	IW	SLC	VV VH	<Sentinel1Meta single object>
	IW2	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.84	SENTINEL-1A	IW	SLC	VV VH	<Sentinel1Meta single object>
	IW3	SENTINEL1_DS:/home1/scratch/agrouaze/xsardatas...	2.84	SENTINEL-1A	IW	SLC	VV VH	<Sentinel1Meta single object>

By default, xsar.product_info only return a minimal set of columns.

Columns list can be given by the columns= keyword.

Columns name can be any attributes from xsar.Sentinel1Meta, with the addition of the ‘meta’ column name, who refer to the xsar.Sentinel1Meta objet itself.

If the columns list include ‘geometry’, the result will by a geopandas.GeoDataframe, who can be displayed whith holoviews.

gdf_info = xsar.product_info(
    [
        xsar.get_test_file('S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE'),
        xsar.get_test_file('S1A_IW_SLC__1SDV_20170907T102951_20170907T103021_018268_01EB76_Z010.SAFE')

    ],
    columns=[ 'safe', 'dsid', 'meta', 'geometry' ]
)

# 'meta' column is dropped for display
gv.feature.land * gv.Polygons(gdf_info.drop(['meta'], axis=1)).opts(tools=['hover'])

multidataset
multidataset

gdf_info.iloc[0]['meta']

<Sentinel1Meta single object>