Search ndvi_anomaly whole collection

Cloud cover percentage [0, 100] from:

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

Landsat collection category, such as T1 or T2:

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):

ID of a dataset type:

Derived product version number:

The ground sample distance from:

The ground sample distance to (exclusive):

Sun azimuth from:

Sun azimuth to (exclusive):

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:

Metadata type name of dataset:

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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55 results

Time (local)	Label
2022-09-01 09:30:00	ndvi_anomaly_x223y094_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x223y095_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x223y087_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x224y087_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x224y088_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x225y055_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x225y051_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x224y076_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x225y048_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x225y060_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x224y084_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x225y047_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x226y056_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x226y053_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x226y089_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x226y090_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x226y055_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x226y049_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x226y050_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x227y050_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x226y048_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x226y085_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x227y053_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x225y088_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x227y049_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x226y086_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x227y055_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x228y058_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x228y047_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x228y084_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x227y091_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x227y090_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x228y046_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x228y053_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x228y085_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x228y081_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x227y056_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x229y053_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x229y086_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x229y056_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x230y084_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x229y055_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x229y087_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x230y054_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x231y058_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x231y057_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x231y060_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x231y054_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x230y055_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x229y054_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x230y052_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x230y092_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x231y059_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x231y092_2022-09--P1M.stac-item
2022-09-01 09:30:00	ndvi_anomaly_x231y091_2022-09--P1M.stac-item

Return to ndvi_anomaly whole collection overview

ndvi_anomaly: Monthly NDVI Anomalies produced by Digital Earth Africa.

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