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Cloud cover percentage [0, 100] from:

Cloud cover percentage [0, 100] to (exclusive):

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Time when dataset was created (processed) From

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Coordinate reference system field:

How much data is in the scene from:

How much data is in the scene to (exclusive):

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Derived product version number:

The ground sample distance from:

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Sun azimuth from:

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Sun elevation from:

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File format (GeoTiff, NetCDF):

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Label:

Latitude range from:

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Longitude range from:

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Full metadata document:

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ID of a metadata type:

Platform code:

Product family code:

African regional area:

Spatial reference code from the provider. For Landsat region_code is a scene path row '{:03d}{:03d}.format(path,row)'. For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Landsat root mean square error from:

Landsat root mean square error to (exclusive):

Landsat root mean square error in X from:

Landsat root mean square error in X to (exclusive):

Landsat root mean square error in Y from:

Landsat root mean square error in Y to (exclusive):

The satellite orbit state, either ascending or descending:

The satellite relative orbit from:

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Acquisition time range From

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34 results

Time (local)	Label
2014-12-15 16:51:33	wofs_ls_165053_2014-12-15.stac-item
2015-04-11 18:42:40	wofs_ls_184039_2015-04-11.stac-item
2015-11-20 19:36:40	wofs_ls_193033_2015-11-20.stac-item
2016-01-17 17:14:40	wofs_ls_167080_2016-01-17.stac-item
2016-01-20 17:42:22	wofs_ls_172072_2016-01-20.stac-item
2016-03-17 17:37:07	wofs_ls_171075_2016-03-17.stac-item
2016-04-03 18:19:49	wofs_ls_178074_2016-04-03.stac-item
2016-04-08 18:35:32	wofs_ls_181067_2016-04-08.stac-item
2016-10-23 18:01:34	wofs_ls_175073_2016-10-23.stac-item
2016-12-04 20:04:22	wofs_ls_197040_2016-12-04.stac-item
2018-02-27 19:56:58	wofs_ls_195054_2018-02-27.stac-item
2019-06-12 17:43:53	wofs_ls_173061_2019-06-12.stac-item
2020-06-18 20:26:27	wofs_ls_201035_2020-06-18.stac-item
2020-07-18 17:31:36	wofs_ls_171061_2020-07-18.stac-item
2020-12-23 19:21:41	wofs_ls_189057_2020-12-23.stac-item
2021-01-13 16:28:19	wofs_ls_160072_2021-01-13.stac-item
2021-05-15 17:01:36	wofs_ls_166064_2021-05-15.stac-item
2021-06-28 17:21:50	wofs_ls_170052_2021-06-28.stac-item
2021-11-18 16:37:01	wofs_ls_161075_2021-11-18.stac-item
2021-12-18 18:34:39	wofs_ls_181063_2021-12-18.stac-item
2022-02-04 17:52:19	wofs_ls_173081_2022-02-04.stac-item
2022-02-14 18:19:22	wofs_ls_179056_2022-02-14.stac-item
2022-03-29 16:28:52	wofs_ls_160074_2022-03-29.stac-item
2022-06-22 18:20:34	wofs_ls_179060_2022-06-22.stac-item
2022-07-21 16:14:05	wofs_ls_158068_2022-07-21.stac-item
2022-10-21 19:05:48	wofs_ls_186063_2022-10-21.stac-item
2022-11-07 16:26:58	wofs_ls_161052_2022-11-07.stac-item
2022-11-16 17:17:38	wofs_ls_168071_2022-11-16.stac-item
2022-12-29 18:32:22	wofs_ls_181057_2022-12-29.stac-item
2023-03-18 20:10:32	wofs_ls_198041_2023-03-18.stac-item
2023-06-11 16:31:41	wofs_ls_161067_2023-06-11.stac-item
2023-08-20 20:42:55	wofs_ls_203045_2023-08-20.stac-item
2024-04-20 20:15:45	wofs_ls_199039_2024-04-20.stac-item
2024-05-23 18:30:24	wofs_ls_182040_2024-05-23.stac-item

Return to wofs_ls whole collection overview

wofs_ls: Historic Flood Mapping Water Observations from Space

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