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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

45 results

Time (local)	Label
2021-11-12 09:22:44	ga_ls9c_ard_3-2-1_091082_2021-11-11_final.stac-item
2021-11-24 10:44:46	ga_ls9c_ard_3-2-1_104075_2021-11-24_final.stac-item
2022-01-01 09:52:40	ga_ls9c_ard_3-2-1_095087_2022-01-01_final.stac-item
2022-02-09 09:52:26	ga_ls9c_ard_3-2-1_096071_2022-02-09_final.stac-item
2022-03-23 10:29:14	ga_ls9c_ard_3-2-1_102071_2022-03-23_final.stac-item
2022-04-11 09:27:58	ga_ls9c_ard_3-2-1_091088_2022-04-10_final.stac-item
2022-05-08 10:42:06	ga_ls9c_ard_3-2-1_104073_2022-05-08_final.stac-item
2022-05-08 10:45:42	ga_ls9c_ard_3-2-1_104082_2022-05-08_final.stac-item
2022-05-29 09:22:24	ga_ls9c_ard_3-2-1_091075_2022-05-28_final.stac-item
2022-06-22 10:13:43	ga_ls9c_ard_3-2-1_099079_2022-06-22_final.stac-item
2022-06-30 09:25:33	ga_ls9c_ard_3-2-1_091082_2022-06-29_final.stac-item
2022-08-31 09:40:16	ga_ls9c_ard_3-2-1_093087_2022-08-31_final.stac-item
2022-10-12 10:11:32	ga_ls9c_ard_3-2-1_099072_2022-10-12_final.stac-item
2022-10-19 10:21:45	ga_ls9c_ard_3-2-1_100082_2022-10-19_final.stac-item
2022-11-08 11:35:06	ga_ls9c_ard_3-2-1_112080_2022-11-08_final.stac-item
2022-11-28 09:33:53	ga_ls9c_ard_3-2-1_092086_2022-11-28_final.stac-item
2022-12-28 09:44:38	ga_ls9c_ard_3-2-1_094082_2022-12-28_final.stac-item
2023-02-01 10:10:48	ga_ls9c_ard_3-2-1_099070_2023-02-01_final.stac-item
2023-03-05 10:10:09	ga_ls9c_ard_3-2-1_099069_2023-03-05_final.stac-item
2023-03-29 09:22:50	ga_ls9c_ard_3-2-1_091075_2023-03-28_final.stac-item
2023-04-26 09:51:00	ga_ls9c_ard_3-2-1_095084_2023-04-26_final.stac-item
2023-05-08 11:52:27	ga_ls9c_ard_3-2-1_115079_2023-05-08_final.stac-item
2023-05-12 11:25:20	ga_ls9c_ard_3-2-1_111073_2023-05-12_final.stac-item
2023-05-25 10:52:16	ga_ls9c_ard_3-2-1_106068_2023-05-25_final.stac-item
2023-06-03 09:10:47	ga_ls9c_ard_3-2-1_089077_2023-06-02_final.stac-item
2023-07-21 10:51:48	ga_ls9c_ard_3-2-1_105082_2023-07-21_final.stac-item
2023-07-27 10:10:20	ga_ls9c_ard_3-2-1_099071_2023-07-27_final.stac-item
2023-08-06 10:49:09	ga_ls9c_ard_3-2-1_105075_2023-08-06_final.stac-item
2023-08-13 10:58:09	ga_ls9c_ard_3-2-1_106082_2023-08-13_final.stac-item
2023-08-15 10:45:47	ga_ls9c_ard_3-2-1_104082_2023-08-15_final.stac-item
2023-09-02 10:28:01	ga_ls9c_ard_3-2-1_102068_2023-09-02_final.stac-item
2023-10-12 11:19:42	ga_ls9c_ard_3-2-1_110073_2023-10-12_final.stac-item
2023-10-31 10:15:17	ga_ls9c_ard_3-2-1_099082_2023-10-31_final.stac-item
2023-11-16 11:52:58	ga_ls9c_ard_3-2-1_115079_2023-11-16_final.stac-item
2023-11-18 11:38:39	ga_ls9c_ard_3-2-1_113074_2023-11-18_final.stac-item
2023-11-25 10:09:38	ga_ls9c_ard_3-2-1_098083_2023-11-25_final.stac-item
2023-12-28 09:16:26	ga_ls9c_ard_3-2-1_089089_2023-12-27_final.stac-item
2024-01-02 11:05:50	ga_ls9c_ard_3-2-1_108069_2024-01-02_final.stac-item
2024-01-03 10:10:11	ga_ls9c_ard_3-2-1_099069_2024-01-03_final.stac-item
2024-01-04 10:55:50	ga_ls9c_ard_3-2-1_106075_2024-01-04_final.stac-item
2024-01-23 09:47:01	ga_ls9c_ard_3-2-1_095073_2024-01-23_final.stac-item
2024-02-28 10:59:54	ga_ls9c_ard_3-2-1_107070_2024-02-28_final.stac-item
2024-05-03 10:04:08	ga_ls9c_ard_3-2-1_098071_2024-05-03_final.stac-item
2024-05-07 09:45:49	ga_ls9c_ard_3-2-1_094087_2024-05-07_final.stac-item
2024-05-14 11:24:02	ga_ls9c_ard_3-2-1_111070_2024-05-14_nrt.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