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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

59 results

Time (local)	Label
2014-03-24 11:23:38	ga_ls8c_ard_3-0-0_111067_2014-03-24_final
2014-06-28 09:51:19	ga_ls8c_ard_3-0-0_095085_2014-06-28_final
2014-10-14 10:11:21	ga_ls8c_ard_3-0-0_099072_2014-10-14_final
2014-10-16 09:57:48	ga_ls8c_ard_3-0-0_097069_2014-10-16_final
2014-10-24 10:49:37	ga_ls8c_ard_3-0-0_105075_2014-10-24_final
2015-01-10 11:00:37	ga_ls8c_ard_3-0-0_107072_2015-01-10_final
2015-02-03 10:10:40	ga_ls8c_ard_3-0-0_099071_2015-02-03_final
2015-07-23 09:11:42	ga_ls8c_ard_3-0-0_089079_2015-07-22_final
2015-12-22 09:58:06	ga_ls8c_ard_3-0-0_097070_2015-12-22_final
2016-02-10 11:25:41	ga_ls8c_ard_3-0-0_111073_2016-02-10_final
2016-06-15 09:57:16	ga_ls8c_ard_3-0-0_097069_2016-06-15_final
2016-08-25 10:04:17	ga_ls8c_ard_3-0-0_098070_2016-08-25_final
2016-10-20 10:55:08	ga_ls8c_ard_3-0-0_106073_2016-10-20_final
2016-10-25 11:13:41	ga_ls8c_ard_3-0-0_109073_2016-10-25_final
2017-01-13 11:15:05	ga_ls8c_ard_3-0-0_109077_2017-01-13_final
2017-04-07 10:46:32	ga_ls8c_ard_3-0-0_105069_2017-04-07_final
2017-04-08 11:30:11	ga_ls8c_ard_3-0-0_112070_2017-04-08_final
2017-08-19 11:51:16	ga_ls8c_ard_3-0-0_115075_2017-08-19_final
2017-10-06 10:14:11	ga_ls8c_ard_3-0-0_099079_2017-10-06_final
2017-10-11 10:29:09	ga_ls8c_ard_3-0-0_102070_2017-10-11_final
2017-10-28 11:13:14	ga_ls8c_ard_3-0-0_109072_2017-10-28_final
2018-01-04 09:13:27	ga_ls8c_ard_3-0-0_089082_2018-01-03_final
2018-05-07 10:27:58	ga_ls8c_ard_3-0-0_102070_2018-05-07_final
2018-07-21 10:09:08	ga_ls8c_ard_3-0-0_099069_2018-07-21_final
2018-08-14 11:04:23	ga_ls8c_ard_3-0-0_107083_2018-08-14_final
2018-09-13 11:17:20	ga_ls8c_ard_3-0-0_109084_2018-09-13_final
2018-11-03 10:07:15	ga_ls8c_ard_3-0-0_098078_2018-11-03_final
2018-11-20 09:12:51	ga_ls8c_ard_3-0-0_089081_2018-11-19_final
2019-01-05 09:26:44	ga_ls8c_ard_3-0-0_091085_2019-01-04_final
2019-02-27 11:17:36	ga_ls8c_ard_3-0-0_110069_2019-02-27_final
2019-05-05 11:50:40	ga_ls8c_ard_3-0-0_115075_2019-05-05_final
2019-05-18 09:39:49	ga_ls8c_ard_3-0-0_094072_2019-05-18_final
2019-09-11 10:53:02	ga_ls8c_ard_3-1-0_106068_2019-09-11_final
2019-09-19 11:47:19	ga_ls8c_ard_3-1-0_114080_2019-09-19_final
2019-11-19 09:32:23	ga_ls8c_ard_3-1-0_093067_2019-11-19_final
2019-11-25 10:36:10	ga_ls8c_ard_3-1-0_103072_2019-11-25_final
2020-02-11 10:47:03	ga_ls8c_ard_3-1-0_105069_2020-02-11_final
2020-07-11 09:21:20	ga_ls8c_ard_3-1-0_090087_2020-07-10_final
2020-08-15 09:44:25	ga_ls8c_ard_3-1-0_095067_2020-08-15_final
2020-09-07 11:32:52	ga_ls8c_ard_3-1-0_112075_2020-09-07_final
2020-11-23 11:05:17	ga_ls8c_ard_3-1-0_107083_2020-11-23_final
2021-05-14 11:23:40	ga_ls8c_ard_3-2-0_111069_2021-05-14_final
2022-02-22 10:14:21	ga_ls8c_ard_3-2-1_099080_2022-02-22_final
2022-03-14 09:51:56	ga_ls8c_ard_3-2-1_095086_2022-03-14_final
2022-03-30 09:51:44	ga_ls8c_ard_3-2-1_095086_2022-03-30_final
2022-06-06 09:27:44	ga_ls8c_ard_3-2-1_091087_2022-06-05_final
2022-07-08 09:28:19	ga_ls8c_ard_3-2-1_091088_2022-07-07_final
2022-07-09 10:07:35	ga_ls8c_ard_3-2-1_098078_2022-07-09_final
2022-09-14 10:40:04	ga_ls8c_ard_3-2-1_103081_2022-09-14_final
2022-10-17 11:18:27	ga_ls8c_ard_3-2-1_110069_2022-10-17_final
2023-01-02 09:13:44	ga_ls8c_ard_3-2-1_089082_2023-01-01_final
2023-03-29 11:51:25	ga_ls8c_ard_3-2-1_115076_2023-03-29_final
2023-05-19 10:45:17	ga_ls8c_ard_3-2-1_104082_2023-05-19_final
2023-05-23 10:18:12	ga_ls8c_ard_3-2-1_100076_2023-05-23_final
2023-06-25 09:28:23	ga_ls8c_ard_3-2-1_091090_2023-06-24_final
2023-07-19 11:50:54	ga_ls8c_ard_3-2-1_115075_2023-07-19_final
2023-08-12 11:01:14	ga_ls8c_ard_3-2-1_107074_2023-08-12_final
2023-10-17 09:10:40	ga_ls8c_ard_3-2-1_089075_2023-10-16_final
2024-04-20 09:45:52	ga_ls8c_ard_3-2-1_095072_2024-04-20_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