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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
2021-11-10 09:37:06	ga_ls9c_ard_3-2-1_094071_2021-11-10_final.stac-item
2021-11-17 09:22:28	ga_ls9c_ard_3-2-1_091075_2021-11-16_final.stac-item
2022-01-01 09:47:05	ga_ls9c_ard_3-2-1_095073_2022-01-01_final.stac-item
2022-02-06 09:23:08	ga_ls9c_ard_3-2-1_091075_2022-02-05_final.stac-item
2022-02-15 10:52:59	ga_ls9c_ard_3-2-1_106068_2022-02-15_final.stac-item
2022-03-11 10:03:47	ga_ls9c_ard_3-2-1_098069_2022-03-11_final.stac-item
2022-03-22 11:24:04	ga_ls9c_ard_3-2-1_111069_2022-03-22_final.stac-item
2022-05-15 10:48:36	ga_ls9c_ard_3-2-1_105074_2022-05-15_final.stac-item
2022-07-12 09:51:48	ga_ls9c_ard_3-2-1_095086_2022-07-12_final.stac-item
2022-08-06 09:39:57	ga_ls9c_ard_3-2-1_094071_2022-08-06_final.stac-item
2022-08-18 10:09:57	ga_ls9c_ard_3-2-1_098084_2022-08-18_final.stac-item
2022-08-20 11:32:29	ga_ls9c_ard_3-2-1_112074_2022-08-20_final.stac-item
2022-09-23 11:20:39	ga_ls9c_ard_3-2-1_110075_2022-09-23_final.stac-item
2022-10-19 10:19:21	ga_ls9c_ard_3-2-1_100076_2022-10-19_final.stac-item
2022-11-07 10:49:50	ga_ls9c_ard_3-2-1_105075_2022-11-07_nrt.stac-item
2022-11-08 11:32:43	ga_ls9c_ard_3-2-1_112074_2022-11-08_final.stac-item
2022-11-13 10:11:12	ga_ls9c_ard_3-2-1_099071_2022-11-13_final.stac-item
2022-12-12 11:18:22	ga_ls9c_ard_3-2-1_110069_2022-12-12_final.stac-item
2022-12-27 10:36:16	ga_ls9c_ard_3-2-1_103072_2022-12-27_final.stac-item
2023-01-17 10:54:20	ga_ls9c_ard_3-2-1_106071_2023-01-17_final.stac-item
2023-01-20 11:25:34	ga_ls9c_ard_3-2-1_111072_2023-01-20_final.stac-item
2023-01-23 10:22:25	ga_ls9c_ard_3-2-1_100084_2023-01-23_final.stac-item
2023-01-25 10:04:31	ga_ls9c_ard_3-2-1_098070_2023-01-25_final.stac-item
2023-03-03 10:23:20	ga_ls9c_ard_3-2-1_101071_2023-03-03_final.stac-item
2023-03-27 09:34:03	ga_ls9c_ard_3-2-1_093072_2023-03-27_final.stac-item
2023-04-06 10:09:52	ga_ls9c_ard_3-2-1_099069_2023-04-06_final.stac-item
2023-04-10 11:25:36	ga_ls9c_ard_3-2-1_111073_2023-04-10_final.stac-item
2023-04-26 09:45:48	ga_ls9c_ard_3-2-1_095071_2023-04-26_final.stac-item
2023-04-29 10:21:27	ga_ls9c_ard_3-2-1_100083_2023-04-29_final.stac-item
2023-05-12 11:24:08	ga_ls9c_ard_3-2-1_111070_2023-05-12_final.stac-item
2023-06-17 09:28:11	ga_ls9c_ard_3-2-1_091090_2023-06-16_final.stac-item
2023-07-04 10:08:51	ga_ls9c_ard_3-2-1_098083_2023-07-04_final.stac-item
2023-07-12 10:57:10	ga_ls9c_ard_3-2-1_106080_2023-07-12_final.stac-item
2023-07-21 09:11:19	ga_ls9c_ard_3-2-1_089078_2023-07-20_final.stac-item
2023-07-27 10:08:21	ga_ls9c_ard_3-2-1_099066_2023-07-27_final.stac-item
2023-07-31 09:45:41	ga_ls9c_ard_3-2-1_095071_2023-07-31_final.stac-item
2023-08-04 09:22:37	ga_ls9c_ard_3-2-1_091075_2023-08-03_final.stac-item
2023-08-28 10:13:50	ga_ls9c_ard_3-2-1_099079_2023-08-28_final.stac-item
2023-10-03 11:24:10	ga_ls9c_ard_3-2-1_111069_2023-10-03_final.stac-item
2023-10-30 11:07:43	ga_ls9c_ard_3-2-1_108074_2023-10-30_final.stac-item
2023-11-03 10:42:32	ga_ls9c_ard_3-2-1_104073_2023-11-03_final.stac-item
2023-11-15 11:11:42	ga_ls9c_ard_3-2-1_108084_2023-11-15_final.stac-item
2023-12-02 10:14:13	ga_ls9c_ard_3-2-1_099079_2023-12-02_final.stac-item
2024-01-16 11:18:59	ga_ls9c_ard_3-2-1_110071_2024-01-16_final.stac-item
2024-01-29 09:12:23	ga_ls9c_ard_3-2-1_089079_2024-01-28_final.stac-item
2024-02-21 10:52:54	ga_ls9c_ard_3-2-1_106068_2024-02-21_final.stac-item
2024-02-25 10:28:10	ga_ls9c_ard_3-2-1_102068_2024-02-25_final.stac-item
2024-02-28 09:22:13	ga_ls9c_ard_3-2-1_091073_2024-02-27_final.stac-item
2024-03-01 09:13:28	ga_ls9c_ard_3-2-1_089082_2024-02-29_final.stac-item
2024-03-01 10:49:57	ga_ls9c_ard_3-2-1_105076_2024-03-01_final.stac-item
2024-04-08 10:09:54	ga_ls9c_ard_3-2-1_099069_2024-04-08_interim.stac-item
2024-04-13 10:33:35	ga_ls9c_ard_3-2-1_102082_2024-04-13_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