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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
2015-05-17 11:57:36	ga_ls8c_ard_3-0-0_116078_2015-05-17_final
2015-06-18 11:57:53	ga_ls8c_ard_3-0-0_116078_2015-06-18_final
2015-07-04 11:58:01	ga_ls8c_ard_3-0-0_116078_2015-07-04_final
2015-07-20 11:58:10	ga_ls8c_ard_3-0-0_116078_2015-07-20_final
2016-05-03 11:58:13	ga_ls8c_ard_3-0-0_116078_2016-05-03_final
2016-05-19 11:58:10	ga_ls8c_ard_3-0-0_116078_2016-05-19_final
2017-06-07 11:58:14	ga_ls8c_ard_3-0-0_116078_2017-06-07_final
2017-10-13 11:58:52	ga_ls8c_ard_3-0-0_116078_2017-10-13_final
2017-10-29 11:58:53	ga_ls8c_ard_3-0-0_116078_2017-10-29_final
2018-10-16 11:58:26	ga_ls8c_ard_3-0-0_116078_2018-10-16_final
2018-11-01 11:58:30	ga_ls8c_ard_3-0-0_116078_2018-11-01_final
2019-04-26 11:57:58	ga_ls8c_ard_3-0-0_116078_2019-04-26_final
2019-05-12 11:58:07	ga_ls8c_ard_3-0-0_116078_2019-05-12_final
2019-05-28 11:58:17	ga_ls8c_ard_3-0-0_116078_2019-05-28_final
2019-06-13 11:58:24	ga_ls8c_ard_3-1-0_116078_2019-06-13_final
2019-06-29 11:58:29	ga_ls8c_ard_3-1-0_116078_2019-06-29_final
2020-05-14 11:58:00	ga_ls8c_ard_3-1-0_116078_2020-05-14_final
2020-07-01 11:58:22	ga_ls8c_ard_3-1-0_116078_2020-07-01_final
2021-05-17 11:58:11	ga_ls8c_ard_3-2-0_116078_2021-05-17_final
2021-06-02 11:58:20	ga_ls8c_ard_3-2-0_116078_2021-06-02_final
2021-06-18 11:58:26	ga_ls8c_ard_3-2-0_116078_2021-06-18_final
2021-07-04 11:58:29	ga_ls8c_ard_3-2-0_116078_2021-07-04_final
2021-10-08 11:58:59	ga_ls8c_ard_3-2-0_116078_2021-10-08_final
2021-10-24 11:59:01	ga_ls8c_ard_3-2-0_116078_2021-10-24_final
2022-04-18 11:58:25	ga_ls8c_ard_3-2-1_116078_2022-04-18_final
2022-05-04 11:58:25	ga_ls8c_ard_3-2-1_116078_2022-05-04_final
2022-05-20 11:58:32	ga_ls8c_ard_3-2-1_116078_2022-05-20_final
2022-06-05 11:58:38	ga_ls8c_ard_3-2-1_116078_2022-06-05_final
2022-06-21 11:58:48	ga_ls8c_ard_3-2-1_116078_2022-06-21_final
2022-07-07 11:58:50	ga_ls8c_ard_3-2-1_116078_2022-07-07_final
2022-07-23 11:58:54	ga_ls8c_ard_3-2-1_116078_2022-07-23_final
2022-08-08 11:59:04	ga_ls8c_ard_3-2-1_116078_2022-08-08_final
2022-08-24 11:59:07	ga_ls8c_ard_3-2-1_116078_2022-08-24_final
2022-09-09 11:59:10	ga_ls8c_ard_3-2-1_116078_2022-09-09_final
2022-09-25 11:59:14	ga_ls8c_ard_3-2-1_116078_2022-09-25_final
2022-10-27 11:59:13	ga_ls8c_ard_3-2-1_116078_2022-10-27_final
2022-11-12 11:59:10	ga_ls8c_ard_3-2-1_116078_2022-11-12_final
2023-01-31 11:58:58	ga_ls8c_ard_3-2-1_116078_2023-01-31_final
2023-02-16 11:58:50	ga_ls8c_ard_3-2-1_116078_2023-02-16_final
2023-05-23 11:57:53	ga_ls8c_ard_3-2-1_116078_2023-05-23_final
2023-06-08 11:57:59	ga_ls8c_ard_3-2-1_116078_2023-06-08_final
2023-07-10 11:58:16	ga_ls8c_ard_3-2-1_116078_2023-07-10_final
2023-07-26 11:58:22	ga_ls8c_ard_3-2-1_116078_2023-07-26_final
2023-08-27 11:58:35	ga_ls8c_ard_3-2-1_116078_2023-08-27_final
2023-09-28 11:58:42	ga_ls8c_ard_3-2-1_116078_2023-09-28_final
2023-10-14 11:58:45	ga_ls8c_ard_3-2-1_116078_2023-10-14_final
2023-10-14 11:58:45	ga_ls8c_ard_3-2-1_116078_2023-10-14_nrt
2023-10-30 11:58:48	ga_ls8c_ard_3-2-1_116078_2023-10-30_final
2023-12-17 11:58:47	ga_ls8c_ard_3-2-1_116078_2023-12-17_final
2024-02-03 11:58:40	ga_ls8c_ard_3-2-1_116078_2024-02-03_final
2024-02-19 11:58:39	ga_ls8c_ard_3-2-1_116078_2024-02-19_final

Return to ga_ls8c_ard_3 whole collection overview

ga_ls8c_ard_3: Geoscience Australia Landsat 8 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