Search ga_ls9c_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

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

The raw CRS string as it appears in metadata:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

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. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

40 results

Time (local)	Label
2023-12-02 10:10:37	ga_ls9c_ard_3-2-1_099070_2023-12-02_final.stac-item
2023-12-02 10:11:01	ga_ls9c_ard_3-2-1_099071_2023-12-02_final.stac-item
2023-12-02 10:11:25	ga_ls9c_ard_3-2-1_099072_2023-12-02_final.stac-item
2023-12-02 10:11:49	ga_ls9c_ard_3-2-1_099073_2023-12-02_final.stac-item
2023-12-02 10:12:13	ga_ls9c_ard_3-2-1_099074_2023-12-02_final.stac-item
2023-12-02 10:12:37	ga_ls9c_ard_3-2-1_099075_2023-12-02_final.stac-item
2023-12-02 10:13:01	ga_ls9c_ard_3-2-1_099076_2023-12-02_final.stac-item
2023-12-02 10:13:25	ga_ls9c_ard_3-2-1_099077_2023-12-02_final.stac-item
2023-12-02 10:13:49	ga_ls9c_ard_3-2-1_099078_2023-12-02_final.stac-item
2023-12-02 10:14:13	ga_ls9c_ard_3-2-1_099079_2023-12-02_final.stac-item
2023-12-02 10:14:37	ga_ls9c_ard_3-2-1_099080_2023-12-02_final.stac-item
2023-12-02 10:15:01	ga_ls9c_ard_3-2-1_099081_2023-12-02_final.stac-item
2023-12-02 10:15:25	ga_ls9c_ard_3-2-1_099082_2023-12-02_final.stac-item
2023-12-02 10:15:49	ga_ls9c_ard_3-2-1_099083_2023-12-02_final.stac-item
2023-12-02 10:16:13	ga_ls9c_ard_3-2-1_099084_2023-12-02_final.stac-item
2023-12-02 10:16:36	ga_ls9c_ard_3-2-1_099085_2023-12-02_final.stac-item
2023-12-02 11:51:06	ga_ls9c_ard_3-2-1_115074_2023-12-02_final.stac-item
2023-12-02 11:51:30	ga_ls9c_ard_3-2-1_115075_2023-12-02_final.stac-item
2023-12-02 11:51:54	ga_ls9c_ard_3-2-1_115076_2023-12-02_final.stac-item
2023-12-02 11:52:18	ga_ls9c_ard_3-2-1_115077_2023-12-02_final.stac-item
2023-12-02 11:52:42	ga_ls9c_ard_3-2-1_115078_2023-12-02_final.stac-item
2023-12-02 11:53:06	ga_ls9c_ard_3-2-1_115079_2023-12-02_final.stac-item
2023-12-02 11:53:30	ga_ls9c_ard_3-2-1_115080_2023-12-02_final.stac-item
2023-12-03 09:16:35	ga_ls9c_ard_3-2-1_090074_2023-12-02_final.stac-item
2023-12-03 09:16:59	ga_ls9c_ard_3-2-1_090075_2023-12-02_final.stac-item
2023-12-03 09:17:23	ga_ls9c_ard_3-2-1_090076_2023-12-02_final.stac-item
2023-12-03 09:17:47	ga_ls9c_ard_3-2-1_090077_2023-12-02_final.stac-item
2023-12-03 09:18:11	ga_ls9c_ard_3-2-1_090078_2023-12-02_final.stac-item
2023-12-03 09:18:35	ga_ls9c_ard_3-2-1_090079_2023-12-02_final.stac-item
2023-12-03 09:18:59	ga_ls9c_ard_3-2-1_090080_2023-12-02_final.stac-item
2023-12-03 09:19:23	ga_ls9c_ard_3-2-1_090081_2023-12-02_final.stac-item
2023-12-03 09:19:47	ga_ls9c_ard_3-2-1_090082_2023-12-02_final.stac-item
2023-12-03 09:20:11	ga_ls9c_ard_3-2-1_090083_2023-12-02_final.stac-item
2023-12-03 09:20:35	ga_ls9c_ard_3-2-1_090084_2023-12-02_final.stac-item
2023-12-03 09:20:59	ga_ls9c_ard_3-2-1_090085_2023-12-02_final.stac-item
2023-12-03 09:21:22	ga_ls9c_ard_3-2-1_090086_2023-12-02_final.stac-item
2023-12-03 09:21:46	ga_ls9c_ard_3-2-1_090087_2023-12-02_final.stac-item
2023-12-03 09:22:10	ga_ls9c_ard_3-2-1_090088_2023-12-02_final.stac-item
2023-12-03 09:22:34	ga_ls9c_ard_3-2-1_090089_2023-12-02_final.stac-item
2023-12-03 09:22:58	ga_ls9c_ard_3-2-1_090090_2023-12-02_final.stac-item

Return to ga_ls9c_ard_3 whole collection overview

ga_ls9c_ard_3: Geoscience Australia Landsat 9 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years