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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
2013-08-12 09:46:25	ga_ls8c_ard_3-0-0_095067_2013-08-12_final
2014-02-26 10:49:42	ga_ls8c_ard_3-0-0_105074_2014-02-26_final
2014-12-09 09:21:48	ga_ls8c_ard_3-0-0_091072_2014-12-08_final
2014-12-21 09:44:32	ga_ls8c_ard_3-0-0_095067_2014-12-21_final
2015-03-12 10:32:52	ga_ls8c_ard_3-0-0_102081_2015-03-12_final
2015-07-20 10:19:16	ga_ls8c_ard_3-0-0_100078_2015-07-20_final
2015-12-01 09:40:22	ga_ls8c_ard_3-0-0_094072_2015-12-01_final
2015-12-11 10:17:01	ga_ls8c_ard_3-0-0_100071_2015-12-11_final
2016-06-09 10:39:07	ga_ls8c_ard_3-0-0_103081_2016-06-09_final
2016-08-31 09:28:50	ga_ls8c_ard_3-0-0_092074_2016-08-30_final
2016-09-29 10:40:04	ga_ls8c_ard_3-0-0_103082_2016-09-29_final
2016-10-22 10:40:47	ga_ls8c_ard_3-0-0_104068_2016-10-22_final
2016-11-10 09:34:22	ga_ls8c_ard_3-0-0_093072_2016-11-10_final
2016-12-14 09:22:22	ga_ls8c_ard_3-0-0_091073_2016-12-13_final
2017-07-09 10:19:30	ga_ls8c_ard_3-0-0_100078_2017-07-09_final
2017-12-04 11:32:25	ga_ls8c_ard_3-0-0_112074_2017-12-04_final
2018-01-13 10:46:05	ga_ls8c_ard_3-0-0_104082_2018-01-13_final
2018-02-06 11:32:07	ga_ls8c_ard_3-0-0_112074_2018-02-06_final
2018-06-18 09:27:35	ga_ls8c_ard_3-0-0_092074_2018-06-17_final
2018-08-17 09:50:02	ga_ls8c_ard_3-0-0_096067_2018-08-17_final
2019-01-13 10:13:22	ga_ls8c_ard_3-0-0_099078_2019-01-13_final
2019-02-02 09:44:11	ga_ls8c_ard_3-0-0_095067_2019-02-02_final
2019-04-07 09:45:07	ga_ls8c_ard_3-1-0_095070_2019-04-07_final
2019-04-23 11:25:29	ga_ls8c_ard_3-0-0_111074_2019-04-23_final
2019-06-03 11:20:03	ga_ls8c_ard_3-0-0_110075_2019-06-03_final
2019-12-03 09:44:44	ga_ls8c_ard_3-1-0_095067_2019-12-03_final
2020-03-20 10:10:32	ga_ls8c_ard_3-1-0_099071_2020-03-20_final
2020-06-12 11:24:06	ga_ls8c_ard_3-1-0_111070_2020-06-12_final
2020-10-24 09:10:51	ga_ls8c_ard_3-1-0_089075_2020-10-23_final
2020-11-20 10:28:23	ga_ls8c_ard_3-1-0_102068_2020-11-20_final
2021-03-11 11:23:11	ga_ls8c_ard_3-2-0_111067_2021-03-11_final
2021-07-01 09:44:18	ga_ls8c_ard_3-2-0_095067_2021-07-01_final
2022-02-10 11:24:36	ga_ls8c_ard_3-2-1_111070_2022-02-10_final
2022-04-19 10:59:36	ga_ls8c_ard_3-2-1_107070_2022-04-19_final
2022-09-23 10:33:54	ga_ls8c_ard_3-2-1_102081_2022-09-23_final
2022-09-23 10:34:18	ga_ls8c_ard_3-2-1_102082_2022-09-23_final
2022-11-25 09:52:33	ga_ls8c_ard_3-2-1_095086_2022-11-25_final
2022-12-23 10:10:42	ga_ls8c_ard_3-2-1_099070_2022-12-23_final
2023-02-06 09:40:12	ga_ls8c_ard_3-2-1_094071_2023-02-06_final
2023-02-25 11:51:15	ga_ls8c_ard_3-2-1_115075_2023-02-25_final
2023-03-06 10:02:34	ga_ls8c_ard_3-2-1_098066_2023-03-06_final
2023-03-07 09:10:31	ga_ls8c_ard_3-2-1_089075_2023-03-06_final
2023-04-30 11:51:53	ga_ls8c_ard_3-2-1_115078_2023-04-30_final
2023-07-04 09:16:20	ga_ls8c_ard_3-2-1_090075_2023-07-03_final
2023-07-19 10:13:37	ga_ls8c_ard_3-2-1_099079_2023-07-19_final
2023-11-29 10:33:29	ga_ls8c_ard_3-2-1_102081_2023-11-29_final
2023-12-05 11:36:23	ga_ls8c_ard_3-2-1_112084_2023-12-05_final
2023-12-26 10:13:43	ga_ls8c_ard_3-2-1_099078_2023-12-26_final
2024-02-13 10:54:04	ga_ls8c_ard_3-2-1_106071_2024-02-13_final
2024-03-24 10:02:38	ga_ls8c_ard_3-2-1_098067_2024-03-24_final
2024-04-08 09:21:17	ga_ls8c_ard_3-2-1_091072_2024-04-07_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