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

Time when dataset was created (processed) to (exclusive)

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):

Dataset UUID:

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Instrument name:

Label:

Latitude range from:

Latitude range to (exclusive):

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:

The satellite relative orbit to (exclusive):

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

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50 results

Time (local)	Label
2022-10-01 09:30:00	ndvi_anomaly_x219y099_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x221y076_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x221y095_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x221y077_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x221y083_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x221y082_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x222y093_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x222y092_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x223y086_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x223y079_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x223y078_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x226y047_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x225y089_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x224y084_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x224y082_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x225y079_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x225y090_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x224y083_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x225y080_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x224y081_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x227y087_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x227y086_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x226y048_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x226y086_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x226y059_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x226y085_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x226y060_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x229y056_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x228y053_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x228y084_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x229y086_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x229y055_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x228y052_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x228y045_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x228y085_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x231y057_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x231y090_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x232y091_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x230y051_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x231y054_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x230y061_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x230y085_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x229y091_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x230y050_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x231y058_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x230y084_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x232y089_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x230y092_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x232y090_2022-10--P1M.stac-item
2022-10-01 09:30:00	ndvi_anomaly_x231y092_2022-10--P1M.stac-item

Return to ndvi_anomaly whole collection overview

ndvi_anomaly: Monthly NDVI Anomalies produced by Digital Earth Africa.

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