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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

39 results

Time (local)	Label
2021-11-08 09:55:27	ga_ls9c_ard_3-2-1_097070_2021-11-08_final.stac-item
2021-12-29 10:55:52	ga_ls9c_ard_3-2-1_106075_2021-12-29_final.stac-item
2022-03-08 11:12:33	ga_ls9c_ard_3-2-1_109071_2022-03-08_final.stac-item
2022-03-31 11:17:51	ga_ls9c_ard_3-2-1_110069_2022-03-31_final.stac-item
2022-04-29 09:15:51	ga_ls9c_ard_3-2-1_089089_2022-04-28_final.stac-item
2022-05-03 10:25:36	ga_ls9c_ard_3-2-1_101078_2022-05-03_final.stac-item
2022-06-14 09:28:04	ga_ls9c_ard_3-2-1_091089_2022-06-13_final.stac-item
2022-08-15 09:39:02	ga_ls9c_ard_3-2-1_093084_2022-08-15_final.stac-item
2022-09-07 09:40:03	ga_ls9c_ard_3-2-1_094071_2022-09-07_final.stac-item
2022-09-10 10:10:10	ga_ls9c_ard_3-2-1_099069_2022-09-10_final.stac-item
2022-10-02 11:17:41	ga_ls9c_ard_3-2-1_109083_2022-10-02_final.stac-item
2022-10-11 11:07:33	ga_ls9c_ard_3-2-1_108073_2022-10-11_final.stac-item
2022-11-10 09:41:05	ga_ls9c_ard_3-2-1_094073_2022-11-10_final.stac-item
2022-12-03 11:24:54	ga_ls9c_ard_3-2-1_111070_2022-12-03_final.stac-item
2022-12-14 09:29:07	ga_ls9c_ard_3-2-1_092074_2022-12-13_final.stac-item
2023-02-03 09:59:15	ga_ls9c_ard_3-2-1_097072_2023-02-03_final.stac-item
2023-03-21 10:11:14	ga_ls9c_ard_3-2-1_099072_2023-03-21_final.stac-item
2023-03-25 11:24:33	ga_ls9c_ard_3-2-1_111070_2023-03-25_final.stac-item
2023-03-27 11:12:32	ga_ls9c_ard_3-2-1_109071_2023-03-27_final.stac-item
2023-05-12 11:24:08	ga_ls9c_ard_3-2-1_111070_2023-05-12_final.stac-item
2023-06-02 10:06:48	ga_ls9c_ard_3-2-1_098078_2023-06-02_final.stac-item
2023-07-21 09:11:43	ga_ls9c_ard_3-2-1_089079_2023-07-20_final.stac-item
2023-07-31 11:23:47	ga_ls9c_ard_3-2-1_111069_2023-07-31_final.stac-item
2023-08-03 10:16:38	ga_ls9c_ard_3-2-1_100071_2023-08-03_final.stac-item
2023-08-06 09:11:04	ga_ls9c_ard_3-2-1_089077_2023-08-05_final.stac-item
2023-08-29 09:20:37	ga_ls9c_ard_3-2-1_090085_2023-08-28_final.stac-item
2023-09-14 10:55:39	ga_ls9c_ard_3-2-1_106075_2023-09-14_final.stac-item
2023-10-10 09:58:20	ga_ls9c_ard_3-2-1_096086_2023-10-10_final.stac-item
2023-10-25 10:49:38	ga_ls9c_ard_3-2-1_105075_2023-10-25_final.stac-item
2023-11-17 09:17:17	ga_ls9c_ard_3-2-1_090076_2023-11-16_final.stac-item
2024-01-16 11:18:59	ga_ls9c_ard_3-2-1_110071_2024-01-16_final.stac-item
2024-01-23 11:24:42	ga_ls9c_ard_3-2-1_111070_2024-01-23_final.stac-item
2024-01-29 10:49:16	ga_ls9c_ard_3-2-1_105074_2024-01-29_final.stac-item
2024-02-08 09:47:07	ga_ls9c_ard_3-2-1_095073_2024-02-08_final.stac-item
2024-02-08 11:26:00	ga_ls9c_ard_3-2-1_111073_2024-02-08_final.stac-item
2024-02-12 11:00:27	ga_ls9c_ard_3-2-1_107071_2024-02-12_final.stac-item
2024-02-13 10:04:01	ga_ls9c_ard_3-2-1_098069_2024-02-13_final.stac-item
2024-03-01 09:11:28	ga_ls9c_ard_3-2-1_089077_2024-02-29_final.stac-item
2024-03-24 09:17:12	ga_ls9c_ard_3-2-1_090076_2024-03-23_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