Download this notebook from github.

Open multiples datasetsΒΆ

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

[1]:

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

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

[2]:

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

Can't open an multi-dataset. Use `xsar.Sentinel1Meta('/tmp/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.SentinelMeta to get the available subdatasets list.

[3]:

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

[3]:
Multi (24) dataset
SENTINEL1_DS:S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:
ipf 2.7
platform SENTINEL-1A
swath WV
product SLC
pols VV
start_date 2016-05-10 10:16:03.843410
stop_date 2016-05-10 10:21:43.669704
subdatasets list of 24 subdatasets

Note that the abose wv_slc_meta object is a multi dataset

Subdatasets list is available with xsar.Sentinel1Meta.subdatasets property

[4]:

wv_slc_meta.subdatasets

[4]:

['SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_001',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_002',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_003',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_004',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_005',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_006',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_007',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_008',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_009',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_010',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_011',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_012',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_013',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_014',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_015',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_016',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_017',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_018',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_019',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_020',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_021',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_022',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_023',
 'SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_024']

A subdataset can be directly be opened by xsar.open_dataset

[5]:


wv_slc_ds1 = xr.open_dataset(wv_slc_meta.subdatasets[0])
wv_slc_ds1

[5]:

<xarray.Dataset>
Dimensions:         (atrack: 4923, pol: 1, xtrack: 5681)
Coordinates:
  * pol             (pol) object 'VV'
  * atrack          (atrack) float64 0.5 1.5 2.5 ... 4.922e+03 4.922e+03
  * xtrack          (xtrack) float64 0.5 1.5 2.5 ... 5.678e+03 5.68e+03 5.68e+03
Data variables: (12/14)
    digital_number  (pol, atrack, xtrack) complex128 ...
    time            (atrack) datetime64[ns] 2016-05-10T10:16:03.843409920 ......
    longitude       (atrack, xtrack) float32 ...
    latitude        (atrack, xtrack) float32 ...
    land_mask       (atrack, xtrack) int8 ...
    ground_heading  (atrack, xtrack) float32 ...
    ...              ...
    sigma0_raw      (pol, atrack, xtrack) float64 ...
    nesz            (pol, atrack, xtrack) float64 ...
    gamma0_raw      (pol, atrack, xtrack) float64 ...
    negz            (pol, atrack, xtrack) float64 ...
    sigma0          (pol, atrack, xtrack) float64 ...
    gamma0          (pol, atrack, xtrack) float64 ...
Attributes: (12/15)
    ipf:               2.7
    platform:          SENTINEL-1A
    swath:             WV
    product:           SLC
    pols:              VV
    name:              SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T101603_201...
    ...                ...
    coverage:          20km * 20km (atrack * xtrack )
    pixel_atrack_m:    4.127512286013487
    pixel_xtrack_m:    3.6571523143890947
    orbit_pass:        Descending
    platform_heading:  -166.3012322109123
    Conventions:       CF-1.7

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

[6]:

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

[6]:
Single dataset
SENTINEL1_DS:S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_001
ipf 2.7
platform SENTINEL-1A
swath WV
product SLC
pols VV
orbit_pass Descending
pixel size 4.1 * 3.7 meters (atrack * xtrack)
coverage 20km * 20km (atrack * xtrack )
start_date 2016-05-10 10:16:03.843410
stop_date 2016-05-10 10:16:06.826137
dsid WV_001

And use this wv_slc_meta1 object with xsar.open_dataset

[7]:

wv_slc_ds1 = xr.open_dataset(wv_slc_meta1)

Getting all xsar.Sentinel1Meta objects from a list of pathΒΆ

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.

[8]:

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

[8]:
name ipf platform swath product pols meta
path dsid
/tmp/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE WV_001 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_002 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_003 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_004 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_005 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_006 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_007 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_008 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_009 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_010 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_011 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_012 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_013 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_014 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_015 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_016 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_017 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_018 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_019 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_020 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_021 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_022 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_023 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
WV_024 SENTINEL1_DS:/tmp/S1A_WV_SLC__1SSV_20160510T10... 2.7 SENTINEL-1A WV SLC VV single Sentinel1Meta object
/tmp/S1A_IW_SLC__1SDV_20170907T102951_20170907T103021_018268_01EB76_Z010.SAFE IW1 SENTINEL1_DS:/tmp/S1A_IW_SLC__1SDV_20170907T10... 2.84 SENTINEL-1A IW SLC VV VH single Sentinel1Meta object
IW2 SENTINEL1_DS:/tmp/S1A_IW_SLC__1SDV_20170907T10... 2.84 SENTINEL-1A IW SLC VV VH single Sentinel1Meta object
IW3 SENTINEL1_DS:/tmp/S1A_IW_SLC__1SDV_20170907T10... 2.84 SENTINEL-1A IW SLC VV VH single Sentinel1Meta 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 β€˜meta’ column name, who refer to the xsar.Sentinel1Meta objet itself.

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

[9]:

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'])


[9]:

[10]:

gdf_info.iloc[0]['meta']

[10]:
Single dataset
SENTINEL1_DS:S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE:WV_001
ipf 2.7
platform SENTINEL-1A
swath WV
product SLC
pols VV
orbit_pass Descending
pixel size 4.1 * 3.7 meters (atrack * xtrack)
coverage 20km * 20km (atrack * xtrack )
start_date 2016-05-10 10:16:03.843410
stop_date 2016-05-10 10:16:06.826137
dsid WV_001