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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

38 results

Time (local)	Label
2021-11-07 10:54:57	ga_ls9c_ard_3-2-1_106072_2021-11-07_final.stac-item
2022-01-21 09:22:45	ga_ls9c_ard_3-2-1_091074_2022-01-20_final.stac-item
2022-04-03 10:09:04	ga_ls9c_ard_3-2-1_099067_2022-04-03_final.stac-item
2022-06-15 10:02:34	ga_ls9c_ard_3-2-1_098067_2022-06-15_final.stac-item
2022-06-29 10:19:35	ga_ls9c_ard_3-2-1_100078_2022-06-29_final.stac-item
2022-07-09 09:21:20	ga_ls9c_ard_3-2-1_090087_2022-07-08_final.stac-item
2022-07-30 09:34:29	ga_ls9c_ard_3-2-1_093073_2022-07-30_final.stac-item
2022-08-09 10:09:17	ga_ls9c_ard_3-2-1_099067_2022-08-09_final.stac-item
2022-08-20 11:31:41	ga_ls9c_ard_3-2-1_112072_2022-08-20_final.stac-item
2022-09-19 10:03:16	ga_ls9c_ard_3-2-1_098067_2022-09-19_final.stac-item
2022-10-12 11:53:37	ga_ls9c_ard_3-2-1_115080_2022-10-12_final.stac-item
2022-10-28 11:53:39	ga_ls9c_ard_3-2-1_115080_2022-10-28_final.stac-item
2022-11-02 10:33:40	ga_ls9c_ard_3-2-1_102081_2022-11-02_final.stac-item
2022-12-23 09:26:04	ga_ls9c_ard_3-2-1_091082_2022-12-22_final.stac-item
2022-12-23 09:26:28	ga_ls9c_ard_3-2-1_091083_2022-12-22_final.stac-item
2023-03-14 10:03:06	ga_ls9c_ard_3-2-1_098067_2023-03-14_final.stac-item
2023-04-23 12:31:07	ga_ls9c_ard_3-2-1_122067_2023-04-23_final.stac-item
2023-04-30 09:21:25	ga_ls9c_ard_3-2-1_091072_2023-04-29_final.stac-item
2023-06-25 10:08:27	ga_ls9c_ard_3-2-1_099067_2023-06-25_final.stac-item
2023-07-31 09:51:40	ga_ls9c_ard_3-2-1_095086_2023-07-31_final.stac-item
2023-07-31 11:24:10	ga_ls9c_ard_3-2-1_111070_2023-07-31_final.stac-item
2023-08-07 11:31:14	ga_ls9c_ard_3-2-1_112072_2023-08-07_final.stac-item
2023-08-18 09:34:12	ga_ls9c_ard_3-2-1_093073_2023-08-18_final.stac-item
2023-09-03 11:13:41	ga_ls9c_ard_3-2-1_109074_2023-09-03_final.stac-item
2023-10-07 09:28:59	ga_ls9c_ard_3-2-1_091090_2023-10-06_final.stac-item
2023-10-15 11:53:26	ga_ls9c_ard_3-2-1_115080_2023-10-15_final.stac-item
2023-11-11 11:31:39	ga_ls9c_ard_3-2-1_112072_2023-11-11_final.stac-item
2023-11-19 09:07:45	ga_ls9c_ard_3-2-1_088083_2023-11-18_final.stac-item
2023-11-23 10:19:35	ga_ls9c_ard_3-2-1_100077_2023-11-23_final.stac-item
2023-11-24 09:22:46	ga_ls9c_ard_3-2-1_091074_2023-11-23_final.stac-item
2024-01-10 11:57:39	ga_ls9c_ard_3-2-1_116075_2024-01-10_final.stac-item
2024-01-10 11:58:03	ga_ls9c_ard_3-2-1_116076_2024-01-10_final.stac-item
2024-01-21 09:57:01	ga_ls9c_ard_3-2-1_097067_2024-01-21_final.stac-item
2024-02-28 12:37:36	ga_ls9c_ard_3-2-1_123067_2024-02-28_final.stac-item
2024-03-01 09:16:40	ga_ls9c_ard_3-2-1_089090_2024-02-29_final.stac-item
2024-03-03 10:35:13	ga_ls9c_ard_3-2-1_103070_2024-03-03_final.stac-item
2024-03-14 11:57:56	ga_ls9c_ard_3-2-1_116076_2024-03-14_final.stac-item
2024-04-02 09:10:32	ga_ls9c_ard_3-2-1_089075_2024-04-01_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