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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
2013-10-15 09:48:40	ga_ls8c_ard_3-0-0_095073_2013-10-15_final
2014-05-04 11:19:59	ga_ls8c_ard_3-0-0_110075_2014-05-04_final
2014-09-08 10:39:58	ga_ls8c_ard_3-0-0_103082_2014-09-08_final
2015-03-22 09:33:48	ga_ls8c_ard_3-0-0_092088_2015-03-22_final
2015-05-05 11:28:38	ga_ls8c_ard_3-0-0_112067_2015-05-05_final
2015-05-09 09:33:20	ga_ls8c_ard_3-0-0_092088_2015-05-09_final
2015-07-26 09:39:50	ga_ls8c_ard_3-0-0_094072_2015-07-26_final
2015-10-21 11:25:44	ga_ls8c_ard_3-0-0_111073_2015-10-21_final
2016-01-18 11:18:00	ga_ls8c_ard_3-0-0_110069_2016-01-18_final
2016-03-25 11:52:56	ga_ls8c_ard_3-0-0_115080_2016-03-25_final
2016-04-10 10:12:44	ga_ls8c_ard_3-0-0_099077_2016-04-10_final
2016-06-05 11:03:26	ga_ls8c_ard_3-0-0_107080_2016-06-05_final
2016-06-27 10:27:17	ga_ls8c_ard_3-0-0_101082_2016-06-27_final
2016-09-18 09:22:55	ga_ls8c_ard_3-0-0_090090_2016-09-17_final
2016-12-11 10:33:33	ga_ls8c_ard_3-0-0_102081_2016-12-11_final
2016-12-28 09:32:17	ga_ls8c_ard_3-0-0_093067_2016-12-28_final
2017-01-23 10:13:14	ga_ls8c_ard_3-0-0_099077_2017-01-23_final
2017-02-14 11:12:28	ga_ls8c_ard_3-0-0_109071_2017-02-14_final
2017-04-18 10:28:18	ga_ls8c_ard_3-0-0_102070_2017-04-18_final
2017-06-20 09:46:32	ga_ls8c_ard_3-0-0_095073_2017-06-20_final
2017-06-23 10:19:27	ga_ls8c_ard_3-0-0_100078_2017-06-23_final
2017-07-08 09:39:26	ga_ls8c_ard_3-0-0_093086_2017-07-08_final
2017-09-08 11:24:12	ga_ls8c_ard_3-0-0_111069_2017-09-08_final
2017-11-19 10:39:40	ga_ls8c_ard_3-0-0_103081_2017-11-19_final
2017-12-13 09:52:33	ga_ls8c_ard_3-0-0_095087_2017-12-13_final
2018-01-23 09:39:48	ga_ls8c_ard_3-0-0_094071_2018-01-23_final
2018-03-30 11:07:00	ga_ls8c_ard_3-0-0_108074_2018-03-30_final
2018-04-18 09:56:03	ga_ls8c_ard_3-0-0_097067_2018-04-18_final
2018-07-12 10:18:51	ga_ls8c_ard_3-0-0_100078_2018-07-12_final
2018-09-11 11:25:17	ga_ls8c_ard_3-0-0_111073_2018-09-11_final
2018-09-24 10:52:28	ga_ls8c_ard_3-0-0_106068_2018-09-24_final
2018-12-12 11:52:17	ga_ls8c_ard_3-0-0_115078_2018-12-12_final
2019-03-26 09:19:39	ga_ls8c_ard_3-1-0_091068_2019-03-25_final
2019-07-13 10:28:01	ga_ls8c_ard_3-1-0_102068_2019-07-13_final
2019-07-24 10:13:31	ga_ls8c_ard_3-1-0_099078_2019-07-24_final
2020-03-06 11:35:35	ga_ls8c_ard_3-1-0_113067_2020-03-06_final
2020-05-24 09:16:33	ga_ls8c_ard_3-1-0_090076_2020-05-23_final
2020-06-19 11:29:09	ga_ls8c_ard_3-1-0_112067_2020-06-19_final
2020-07-06 10:39:15	ga_ls8c_ard_3-1-0_103081_2020-07-06_final
2021-01-05 10:46:16	ga_ls8c_ard_3-2-0_104082_2021-01-05_final
2021-03-02 09:50:34	ga_ls8c_ard_3-2-0_096067_2021-03-02_final
2021-08-28 10:27:41	ga_ls8c_ard_3-2-0_101082_2021-08-28_final
2022-04-09 10:27:17	ga_ls8c_ard_3-2-1_101082_2022-04-09_final
2022-07-17 09:22:07	ga_ls8c_ard_3-2-1_090088_2022-07-16_final
2023-02-25 10:11:11	ga_ls8c_ard_3-2-1_099072_2023-02-25_final
2023-06-05 09:46:10	ga_ls8c_ard_3-2-1_095073_2023-06-05_final
2023-06-17 10:08:12	ga_ls8c_ard_3-2-1_099066_2023-06-17_final
2023-06-23 09:39:06	ga_ls8c_ard_3-2-1_093086_2023-06-23_final
2023-08-02 10:25:20	ga_ls8c_ard_3-2-1_101077_2023-08-02_final
2023-10-06 11:07:39	ga_ls8c_ard_3-2-1_108074_2023-10-06_final
2024-04-12 10:39:24	ga_ls8c_ard_3-2-1_103082_2024-04-12_nrt

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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years