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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

51 results

Time (local)	Label
2021-11-10 11:18:09	ga_ls9c_ard_3-2-1_110077_2021-11-10_final.stac-item
2021-11-12 10:58:37	ga_ls9c_ard_3-2-1_106075_2021-11-12_final.stac-item
2022-03-10 09:21:43	ga_ls9c_ard_3-2-1_091072_2022-03-09_final.stac-item
2022-03-19 10:55:11	ga_ls9c_ard_3-2-1_106074_2022-03-19_final.stac-item
2022-04-04 10:53:32	ga_ls9c_ard_3-2-1_106070_2022-04-04_final.stac-item
2022-04-12 10:03:14	ga_ls9c_ard_3-2-1_098068_2022-04-12_final.stac-item
2022-04-25 11:17:28	ga_ls9c_ard_3-2-1_109084_2022-04-25_final.stac-item
2022-06-23 10:53:01	ga_ls9c_ard_3-2-1_106069_2022-06-23_final.stac-item
2022-07-01 10:03:37	ga_ls9c_ard_3-2-1_098069_2022-07-01_final.stac-item
2022-07-25 09:17:28	ga_ls9c_ard_3-2-1_090077_2022-07-24_final.stac-item
2022-08-10 09:17:39	ga_ls9c_ard_3-2-1_090077_2022-08-09_final.stac-item
2022-09-05 09:55:12	ga_ls9c_ard_3-2-1_096078_2022-09-05_final.stac-item
2022-09-18 11:01:41	ga_ls9c_ard_3-2-1_107074_2022-09-18_final.stac-item
2022-09-28 11:38:48	ga_ls9c_ard_3-2-1_113074_2022-09-28_final.stac-item
2022-10-11 11:07:57	ga_ls9c_ard_3-2-1_108074_2022-10-11_final.stac-item
2022-10-17 10:32:06	ga_ls9c_ard_3-2-1_102077_2022-10-17_final.stac-item
2022-10-23 09:55:50	ga_ls9c_ard_3-2-1_096079_2022-10-23_final.stac-item
2022-12-08 10:05:23	ga_ls9c_ard_3-2-1_098072_2022-12-08_final.stac-item
2023-01-08 09:24:08	ga_ls9c_ard_3-2-1_091077_2023-01-07_final.stac-item
2023-01-08 09:26:55	ga_ls9c_ard_3-2-1_091084_2023-01-07_final.stac-item
2023-01-17 10:54:44	ga_ls9c_ard_3-2-1_106072_2023-01-17_final.stac-item
2023-03-18 09:39:58	ga_ls9c_ard_3-2-1_094071_2023-03-18_final.stac-item
2023-03-24 10:40:30	ga_ls9c_ard_3-2-1_104068_2023-03-24_final.stac-item
2023-03-27 11:13:44	ga_ls9c_ard_3-2-1_109074_2023-03-27_final.stac-item
2023-06-04 09:57:38	ga_ls9c_ard_3-2-1_096086_2023-06-04_final.stac-item
2023-06-08 11:09:46	ga_ls9c_ard_3-2-1_108081_2023-06-08_final.stac-item
2023-06-10 09:22:05	ga_ls9c_ard_3-2-1_090090_2023-06-09_final.stac-item
2023-06-18 11:45:57	ga_ls9c_ard_3-2-1_114079_2023-06-18_final.stac-item
2023-06-22 11:18:26	ga_ls9c_ard_3-2-1_110072_2023-06-22_final.stac-item
2023-06-24 09:27:59	ga_ls9c_ard_3-2-1_092074_2023-06-23_final.stac-item
2023-06-26 10:54:07	ga_ls9c_ard_3-2-1_106073_2023-06-26_final.stac-item
2023-07-31 09:52:04	ga_ls9c_ard_3-2-1_095087_2023-07-31_final.stac-item
2023-08-01 10:28:34	ga_ls9c_ard_3-2-1_102070_2023-08-01_final.stac-item
2023-08-06 10:49:09	ga_ls9c_ard_3-2-1_105075_2023-08-06_final.stac-item
2023-08-11 11:06:55	ga_ls9c_ard_3-2-1_108073_2023-08-11_final.stac-item
2023-08-18 09:39:47	ga_ls9c_ard_3-2-1_093087_2023-08-18_final.stac-item
2023-08-25 09:45:17	ga_ls9c_ard_3-2-1_094085_2023-08-25_final.stac-item
2023-09-05 11:04:56	ga_ls9c_ard_3-2-1_107083_2023-09-05_final.stac-item
2023-09-19 09:40:07	ga_ls9c_ard_3-2-1_093087_2023-09-19_final.stac-item
2023-09-30 10:55:13	ga_ls9c_ard_3-2-1_106074_2023-09-30_final.stac-item
2023-10-12 09:45:12	ga_ls9c_ard_3-2-1_094084_2023-10-12_final.stac-item
2023-10-29 10:23:17	ga_ls9c_ard_3-2-1_101071_2023-10-29_final.stac-item
2023-11-06 09:39:47	ga_ls9c_ard_3-2-1_093086_2023-11-06_final.stac-item
2023-11-18 09:57:46	ga_ls9c_ard_3-2-1_097069_2023-11-18_final.stac-item
2024-01-28 10:10:23	ga_ls9c_ard_3-2-1_098085_2024-01-28_final.stac-item
2024-02-03 09:33:21	ga_ls9c_ard_3-2-1_092085_2024-02-03_final.stac-item
2024-02-14 10:48:52	ga_ls9c_ard_3-2-1_105073_2024-02-14_final.stac-item
2024-03-13 09:33:48	ga_ls9c_ard_3-2-1_093071_2024-03-13_final.stac-item
2024-03-17 10:48:46	ga_ls9c_ard_3-2-1_105073_2024-03-17_final.stac-item
2024-03-24 09:21:12	ga_ls9c_ard_3-2-1_090086_2024-03-23_final.stac-item
2024-03-24 10:57:41	ga_ls9c_ard_3-2-1_106080_2024-03-24_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years