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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

40 results

Time (local)	Label
2022-01-14 10:58:36	ga_ls9c_ard_3-2-1_106082_2022-01-14_final.stac-item
2022-02-02 09:46:17	ga_ls9c_ard_3-2-1_095071_2022-02-02_final.stac-item
2022-03-12 10:49:50	ga_ls9c_ard_3-2-1_105076_2022-03-12_final.stac-item
2022-04-25 11:13:05	ga_ls9c_ard_3-2-1_109073_2022-04-25_final.stac-item
2022-05-04 09:34:22	ga_ls9c_ard_3-2-1_092089_2022-05-04_final.stac-item
2022-05-04 11:09:39	ga_ls9c_ard_3-2-1_108080_2022-05-04_final.stac-item
2022-06-07 10:55:31	ga_ls9c_ard_3-2-1_106076_2022-06-07_final.stac-item
2022-06-15 10:06:33	ga_ls9c_ard_3-2-1_098077_2022-06-15_final.stac-item
2022-08-03 10:49:29	ga_ls9c_ard_3-2-1_105075_2022-08-03_final.stac-item
2022-08-25 11:53:26	ga_ls9c_ard_3-2-1_115080_2022-08-25_final.stac-item
2022-09-02 09:22:43	ga_ls9c_ard_3-2-1_091074_2022-09-01_final.stac-item
2022-09-02 09:26:18	ga_ls9c_ard_3-2-1_091083_2022-09-01_final.stac-item
2022-09-02 11:05:11	ga_ls9c_ard_3-2-1_107083_2022-09-02_final.stac-item
2022-09-11 10:56:14	ga_ls9c_ard_3-2-1_106076_2022-09-11_final.stac-item
2022-10-14 09:57:36	ga_ls9c_ard_3-2-1_097068_2022-10-14_final.stac-item
2022-11-01 09:52:25	ga_ls9c_ard_3-2-1_095086_2022-11-01_final.stac-item
2022-11-26 09:44:40	ga_ls9c_ard_3-2-1_094082_2022-11-26_final.stac-item
2023-01-05 10:33:43	ga_ls9c_ard_3-2-1_102081_2023-01-05_final.stac-item
2023-01-24 09:22:50	ga_ls9c_ard_3-2-1_091074_2023-01-23_final.stac-item
2023-02-01 10:15:59	ga_ls9c_ard_3-2-1_099083_2023-02-01_final.stac-item
2023-04-11 10:33:09	ga_ls9c_ard_3-2-1_102081_2023-04-11_final.stac-item
2023-05-24 10:13:24	ga_ls9c_ard_3-2-1_099079_2023-05-24_final.stac-item
2023-06-08 11:07:22	ga_ls9c_ard_3-2-1_108075_2023-06-08_final.stac-item
2023-06-12 09:06:54	ga_ls9c_ard_3-2-1_088083_2023-06-11_final.stac-item
2023-06-12 10:41:48	ga_ls9c_ard_3-2-1_104073_2023-06-12_final.stac-item
2023-07-10 09:27:26	ga_ls9c_ard_3-2-1_092072_2023-07-09_final.stac-item
2023-07-15 09:46:24	ga_ls9c_ard_3-2-1_095073_2023-07-15_final.stac-item
2023-07-20 10:06:56	ga_ls9c_ard_3-2-1_098078_2023-07-20_final.stac-item
2023-08-02 11:13:26	ga_ls9c_ard_3-2-1_109074_2023-08-02_final.stac-item
2023-11-06 09:33:48	ga_ls9c_ard_3-2-1_093071_2023-11-06_final.stac-item
2023-11-06 09:34:12	ga_ls9c_ard_3-2-1_093072_2023-11-06_final.stac-item
2023-11-08 09:22:39	ga_ls9c_ard_3-2-1_091074_2023-11-07_final.stac-item
2023-11-16 11:52:58	ga_ls9c_ard_3-2-1_115079_2023-11-16_final.stac-item
2023-12-15 09:40:08	ga_ls9c_ard_3-2-1_094071_2023-12-15_final.stac-item
2023-12-20 11:42:23	ga_ls9c_ard_3-2-1_113083_2023-12-20_final.stac-item
2024-01-03 11:53:28	ga_ls9c_ard_3-2-1_115080_2024-01-03_final.stac-item
2024-01-23 09:46:13	ga_ls9c_ard_3-2-1_095071_2024-01-23_final.stac-item
2024-02-07 09:06:39	ga_ls9c_ard_3-2-1_088080_2024-02-06_final.stac-item
2024-03-07 11:53:23	ga_ls9c_ard_3-2-1_115080_2024-03-07_final.stac-item
2024-05-16 09:34:20	ga_ls9c_ard_3-2-1_093074_2024-05-16_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