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

43 results

Time (local)	Label
2023-10-08 10:04:40	ga_ls9c_ard_3-2-1_098071_2023-10-08_final.stac-item
2023-10-08 10:05:04	ga_ls9c_ard_3-2-1_098072_2023-10-08_final.stac-item
2023-10-08 10:09:04	ga_ls9c_ard_3-2-1_098082_2023-10-08_final.stac-item
2023-10-08 11:45:33	ga_ls9c_ard_3-2-1_114076_2023-10-08_final.stac-item
2023-10-09 09:10:15	ga_ls9c_ard_3-2-1_089074_2023-10-08_final.stac-item
2023-10-09 09:11:51	ga_ls9c_ard_3-2-1_089078_2023-10-08_final.stac-item
2023-10-09 09:13:03	ga_ls9c_ard_3-2-1_089081_2023-10-08_final.stac-item
2023-10-09 09:13:51	ga_ls9c_ard_3-2-1_089083_2023-10-08_final.stac-item
2023-10-09 09:15:03	ga_ls9c_ard_3-2-1_089086_2023-10-08_final.stac-item
2023-10-09 09:16:15	ga_ls9c_ard_3-2-1_089089_2023-10-08_final.stac-item
2023-10-09 10:49:32	ga_ls9c_ard_3-2-1_105075_2023-10-09_final.stac-item
2023-10-09 10:49:56	ga_ls9c_ard_3-2-1_105076_2023-10-09_final.stac-item
2023-10-09 10:50:20	ga_ls9c_ard_3-2-1_105077_2023-10-09_final.stac-item
2023-10-10 09:51:57	ga_ls9c_ard_3-2-1_096070_2023-10-10_final.stac-item
2023-10-10 09:52:21	ga_ls9c_ard_3-2-1_096071_2023-10-10_final.stac-item
2023-10-10 09:52:45	ga_ls9c_ard_3-2-1_096072_2023-10-10_final.stac-item
2023-10-10 09:53:08	ga_ls9c_ard_3-2-1_096073_2023-10-10_final.stac-item
2023-10-10 09:53:32	ga_ls9c_ard_3-2-1_096074_2023-10-10_final.stac-item
2023-10-10 09:53:56	ga_ls9c_ard_3-2-1_096075_2023-10-10_final.stac-item
2023-10-10 09:54:20	ga_ls9c_ard_3-2-1_096076_2023-10-10_final.stac-item
2023-10-10 09:54:44	ga_ls9c_ard_3-2-1_096077_2023-10-10_final.stac-item
2023-10-10 09:55:08	ga_ls9c_ard_3-2-1_096078_2023-10-10_final.stac-item
2023-10-10 09:55:32	ga_ls9c_ard_3-2-1_096079_2023-10-10_final.stac-item
2023-10-10 09:55:56	ga_ls9c_ard_3-2-1_096080_2023-10-10_final.stac-item
2023-10-10 09:56:20	ga_ls9c_ard_3-2-1_096081_2023-10-10_final.stac-item
2023-10-10 09:56:44	ga_ls9c_ard_3-2-1_096082_2023-10-10_final.stac-item
2023-10-10 09:57:08	ga_ls9c_ard_3-2-1_096083_2023-10-10_final.stac-item
2023-10-10 09:57:32	ga_ls9c_ard_3-2-1_096084_2023-10-10_final.stac-item
2023-10-10 09:57:56	ga_ls9c_ard_3-2-1_096085_2023-10-10_final.stac-item
2023-10-10 09:58:20	ga_ls9c_ard_3-2-1_096086_2023-10-10_final.stac-item
2023-10-10 11:31:38	ga_ls9c_ard_3-2-1_112072_2023-10-10_final.stac-item
2023-10-10 11:32:02	ga_ls9c_ard_3-2-1_112073_2023-10-10_final.stac-item
2023-10-10 11:32:26	ga_ls9c_ard_3-2-1_112074_2023-10-10_final.stac-item
2023-10-10 11:32:49	ga_ls9c_ard_3-2-1_112075_2023-10-10_final.stac-item
2023-10-10 11:33:13	ga_ls9c_ard_3-2-1_112076_2023-10-10_final.stac-item
2023-10-10 11:33:37	ga_ls9c_ard_3-2-1_112077_2023-10-10_final.stac-item
2023-10-10 11:34:01	ga_ls9c_ard_3-2-1_112078_2023-10-10_final.stac-item
2023-10-10 11:34:25	ga_ls9c_ard_3-2-1_112079_2023-10-10_final.stac-item
2023-10-10 11:34:49	ga_ls9c_ard_3-2-1_112080_2023-10-10_final.stac-item
2023-10-10 11:35:13	ga_ls9c_ard_3-2-1_112081_2023-10-10_final.stac-item
2023-10-10 11:35:37	ga_ls9c_ard_3-2-1_112082_2023-10-10_final.stac-item
2023-10-10 11:36:01	ga_ls9c_ard_3-2-1_112083_2023-10-10_final.stac-item
2023-10-10 11:36:25	ga_ls9c_ard_3-2-1_112084_2023-10-10_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