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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
2013-10-24 11:18:53	ga_ls8c_ard_3-0-0_110067_2013-10-24_final
2014-07-21 09:57:15	ga_ls8c_ard_3-0-0_096084_2014-07-21_final
2014-11-10 11:32:06	ga_ls8c_ard_3-0-0_112073_2014-11-10_final
2014-12-21 09:46:56	ga_ls8c_ard_3-0-0_095073_2014-12-21_final
2015-02-08 10:28:22	ga_ls8c_ard_3-0-0_102069_2015-02-08_final
2015-02-16 11:16:55	ga_ls8c_ard_3-0-0_110067_2015-02-16_final
2015-02-25 09:33:27	ga_ls8c_ard_3-0-0_093071_2015-02-25_final
2015-04-22 10:22:03	ga_ls8c_ard_3-0-0_101070_2015-04-22_final
2015-07-03 11:13:32	ga_ls8c_ard_3-0-0_109075_2015-07-03_final
2015-12-21 10:54:56	ga_ls8c_ard_3-0-0_106073_2015-12-21_final
2016-03-29 11:23:47	ga_ls8c_ard_3-0-0_111069_2016-03-29_final
2016-05-07 09:55:46	ga_ls8c_ard_3-0-0_096081_2016-05-07_final
2016-06-21 09:22:14	ga_ls8c_ard_3-0-0_091074_2016-06-20_final
2016-09-05 09:52:12	ga_ls8c_ard_3-0-0_095086_2016-09-05_final
2017-02-21 11:17:01	ga_ls8c_ard_3-0-0_110067_2017-02-21_final
2017-07-17 11:07:47	ga_ls8c_ard_3-0-0_108075_2017-07-17_final
2017-08-12 11:46:39	ga_ls8c_ard_3-0-0_114079_2017-08-12_final
2017-11-01 09:16:00	ga_ls8c_ard_3-0-0_089088_2017-10-31_final
2017-12-19 09:11:30	ga_ls8c_ard_3-0-0_089077_2017-12-18_final
2018-05-24 11:12:37	ga_ls8c_ard_3-0-0_109074_2018-05-24_final
2018-07-18 09:37:25	ga_ls8c_ard_3-0-0_094067_2018-07-18_final
2018-08-29 11:58:07	ga_ls8c_ard_3-0-0_116078_2018-08-29_final
2019-06-12 11:14:20	ga_ls8c_ard_3-1-0_109076_2019-06-12_final
2019-07-14 11:13:40	ga_ls8c_ard_3-1-0_109074_2019-07-14_final
2019-08-15 11:16:39	ga_ls8c_ard_3-1-0_109081_2019-08-15_final
2019-09-23 11:17:26	ga_ls8c_ard_3-1-0_110067_2019-09-23_final
2019-10-20 11:02:33	ga_ls8c_ard_3-1-0_107076_2019-10-20_final
2019-11-10 09:38:36	ga_ls8c_ard_3-1-0_094067_2019-11-10_final
2019-11-22 11:42:09	ga_ls8c_ard_3-1-0_114067_2019-11-22_final
2020-01-13 11:17:18	ga_ls8c_ard_3-1-0_110067_2020-01-13_final
2020-08-08 09:38:12	ga_ls8c_ard_3-1-0_094067_2020-08-08_final
2020-12-01 10:16:40	ga_ls8c_ard_3-1-0_099085_2020-12-01_final
2021-03-11 11:24:47	ga_ls8c_ard_3-2-0_111071_2021-03-11_final
2021-03-20 09:39:38	ga_ls8c_ard_3-2-0_094071_2021-03-20_final
2021-04-09 09:21:13	ga_ls8c_ard_3-2-0_090087_2021-04-08_final
2021-06-09 10:27:17	ga_ls8c_ard_3-2-0_101082_2021-06-09_final
2021-10-16 11:08:22	ga_ls8c_ard_3-2-0_108075_2021-10-16_final
2022-02-15 10:03:01	ga_ls8c_ard_3-2-1_098067_2022-02-15_final
2022-03-10 10:09:06	ga_ls8c_ard_3-2-1_099067_2022-03-10_final
2022-03-19 10:02:26	ga_ls8c_ard_3-2-1_098066_2022-03-19_final
2022-04-15 11:24:20	ga_ls8c_ard_3-2-1_111070_2022-04-15_final
2022-05-28 09:34:58	ga_ls8c_ard_3-2-1_092090_2022-05-28_final
2022-07-25 10:03:18	ga_ls8c_ard_3-2-1_098067_2022-07-25_final
2022-08-11 09:14:13	ga_ls8c_ard_3-2-1_089083_2022-08-10_final
2022-12-08 10:58:55	ga_ls8c_ard_3-2-1_106082_2022-12-08_final
2023-02-20 09:53:33	ga_ls8c_ard_3-2-1_096074_2023-02-20_final
2023-03-13 10:09:54	ga_ls8c_ard_3-2-1_099069_2023-03-13_final
2023-09-30 10:03:04	ga_ls8c_ard_3-2-1_098067_2023-09-30_final
2023-10-17 09:10:40	ga_ls8c_ard_3-2-1_089075_2023-10-16_final
2023-10-29 11:17:56	ga_ls8c_ard_3-2-1_109084_2023-10-29_final
2024-04-24 09:22:20	ga_ls8c_ard_3-2-1_091075_2024-04-23_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years