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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

52 results

Time (local)	Label
2021-11-05 11:12:53	ga_ls9c_ard_3-2-1_109070_2021-11-05_final.stac-item
2021-11-12 10:56:13	ga_ls9c_ard_3-2-1_106069_2021-11-12_final.stac-item
2022-01-19 11:12:47	ga_ls9c_ard_3-2-1_109071_2022-01-19_final.stac-item
2022-01-21 09:22:45	ga_ls9c_ard_3-2-1_091074_2022-01-20_final.stac-item
2022-02-11 09:46:27	ga_ls9c_ard_3-2-1_094087_2022-02-11_final.stac-item
2022-02-11 11:18:09	ga_ls9c_ard_3-2-1_110069_2022-02-11_final.stac-item
2022-03-02 11:52:49	ga_ls9c_ard_3-2-1_115079_2022-03-02_final.stac-item
2022-04-06 09:07:04	ga_ls9c_ard_3-2-1_088082_2022-04-05_final.stac-item
2022-04-07 09:50:43	ga_ls9c_ard_3-2-1_095083_2022-04-07_final.stac-item
2022-04-16 11:20:08	ga_ls9c_ard_3-2-1_110075_2022-04-16_final.stac-item
2022-04-24 10:27:49	ga_ls9c_ard_3-2-1_102068_2022-04-24_final.stac-item
2022-06-07 09:22:13	ga_ls9c_ard_3-2-1_090090_2022-06-06_final.stac-item
2022-06-22 10:13:19	ga_ls9c_ard_3-2-1_099078_2022-06-22_final.stac-item
2022-06-28 09:39:31	ga_ls9c_ard_3-2-1_093086_2022-06-28_final.stac-item
2022-07-12 11:24:18	ga_ls9c_ard_3-2-1_111070_2022-07-12_final.stac-item
2022-07-25 09:22:15	ga_ls9c_ard_3-2-1_090089_2022-07-24_final.stac-item
2022-08-06 09:39:57	ga_ls9c_ard_3-2-1_094071_2022-08-06_final.stac-item
2022-08-08 09:34:23	ga_ls9c_ard_3-2-1_092088_2022-08-08_final.stac-item
2022-08-27 10:04:11	ga_ls9c_ard_3-2-1_097085_2022-08-27_final.stac-item
2022-09-20 10:52:55	ga_ls9c_ard_3-2-1_105083_2022-09-20_final.stac-item
2022-09-24 10:25:02	ga_ls9c_ard_3-2-1_101075_2022-09-24_final.stac-item
2022-10-21 10:04:36	ga_ls9c_ard_3-2-1_098070_2022-10-21_final.stac-item
2022-11-22 10:06:12	ga_ls9c_ard_3-2-1_098074_2022-11-22_final.stac-item
2022-12-15 10:11:10	ga_ls9c_ard_3-2-1_099071_2022-12-15_final.stac-item
2022-12-21 09:39:39	ga_ls9c_ard_3-2-1_093085_2022-12-21_final.stac-item
2022-12-22 10:18:06	ga_ls9c_ard_3-2-1_100073_2022-12-22_final.stac-item
2023-01-14 10:27:52	ga_ls9c_ard_3-2-1_101082_2023-01-14_final.stac-item
2023-02-01 10:13:59	ga_ls9c_ard_3-2-1_099078_2023-02-01_final.stac-item
2023-02-10 10:04:15	ga_ls9c_ard_3-2-1_098069_2023-02-10_final.stac-item
2023-02-14 09:41:30	ga_ls9c_ard_3-2-1_094074_2023-02-14_final.stac-item
2023-03-06 10:58:59	ga_ls9c_ard_3-2-1_106083_2023-03-06_final.stac-item
2023-03-20 09:27:59	ga_ls9c_ard_3-2-1_092072_2023-03-19_final.stac-item
2023-05-25 10:55:27	ga_ls9c_ard_3-2-1_106076_2023-05-25_final.stac-item
2023-06-09 10:12:32	ga_ls9c_ard_3-2-1_099077_2023-06-09_final.stac-item
2023-07-19 09:26:05	ga_ls9c_ard_3-2-1_091084_2023-07-18_final.stac-item
2023-08-24 10:39:18	ga_ls9c_ard_3-2-1_103081_2023-08-24_final.stac-item
2023-08-27 09:28:34	ga_ls9c_ard_3-2-1_092074_2023-08-26_final.stac-item
2023-08-29 09:22:13	ga_ls9c_ard_3-2-1_090089_2023-08-28_final.stac-item
2023-09-05 09:22:04	ga_ls9c_ard_3-2-1_091073_2023-09-04_final.stac-item
2023-10-14 09:28:05	ga_ls9c_ard_3-2-1_092072_2023-10-13_final.stac-item
2023-12-03 09:20:59	ga_ls9c_ard_3-2-1_090085_2023-12-02_final.stac-item
2023-12-05 10:46:16	ga_ls9c_ard_3-2-1_104082_2023-12-05_final.stac-item
2023-12-28 10:49:20	ga_ls9c_ard_3-2-1_105074_2023-12-28_final.stac-item
2024-03-02 09:57:56	ga_ls9c_ard_3-2-1_096085_2024-03-02_final.stac-item
2024-03-15 09:27:50	ga_ls9c_ard_3-2-1_091087_2024-03-14_final.stac-item
2024-03-18 11:32:25	ga_ls9c_ard_3-2-1_112074_2024-03-18_final.stac-item
2024-03-23 10:09:15	ga_ls9c_ard_3-2-1_099067_2024-03-23_final.stac-item
2024-03-25 09:58:03	ga_ls9c_ard_3-2-1_097070_2024-03-25_final.stac-item
2024-03-26 10:46:05	ga_ls9c_ard_3-2-1_104082_2024-03-26_final.stac-item
2024-03-27 09:52:26	ga_ls9c_ard_3-2-1_095087_2024-03-27_final.stac-item
2024-04-08 10:13:06	ga_ls9c_ard_3-2-1_099077_2024-04-08_final.stac-item
2024-04-08 10:13:54	ga_ls9c_ard_3-2-1_099079_2024-04-08_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