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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
2013-03-31 09:31:51	ga_ls8c_ard_3-0-0_092074_2013-03-31_final
2013-04-19 09:22:54	ga_ls8c_ard_3-0-0_090086_2013-04-18_final
2013-05-29 10:11:23	ga_ls8c_ard_3-0-0_098083_2013-05-29_final
2014-09-06 10:49:56	ga_ls8c_ard_3-0-0_105076_2014-09-06_final
2014-12-17 10:13:14	ga_ls8c_ard_3-0-0_099077_2014-12-17_final
2015-04-19 09:49:58	ga_ls8c_ard_3-0-0_096067_2015-04-19_final
2015-08-14 10:16:01	ga_ls8c_ard_3-0-0_099085_2015-08-14_final
2015-10-12 09:50:36	ga_ls8c_ard_3-0-0_096067_2015-10-12_final
2015-12-26 09:33:47	ga_ls8c_ard_3-0-0_093071_2015-12-26_final
2015-12-31 11:30:23	ga_ls8c_ard_3-0-0_112069_2015-12-31_final
2016-02-03 11:17:09	ga_ls8c_ard_3-0-0_110067_2016-02-03_final
2016-04-30 09:44:00	ga_ls8c_ard_3-0-0_095067_2016-04-30_final
2016-05-17 10:32:49	ga_ls8c_ard_3-0-0_102081_2016-05-17_final
2016-12-15 10:07:37	ga_ls8c_ard_3-0-0_098078_2016-12-15_final
2017-03-13 09:21:14	ga_ls8c_ard_3-0-0_090087_2017-03-12_final
2017-06-04 09:46:02	ga_ls8c_ard_3-0-0_095072_2017-06-04_final
2017-06-10 09:13:47	ga_ls8c_ard_3-0-0_089084_2017-06-09_final
2017-07-13 09:51:12	ga_ls8c_ard_3-0-0_096069_2017-07-13_final
2017-09-10 09:32:10	ga_ls8c_ard_3-0-0_093067_2017-09-10_final
2018-01-09 11:08:03	ga_ls8c_ard_3-0-0_108075_2018-01-09_final
2018-04-04 09:46:37	ga_ls8c_ard_3-0-0_095074_2018-04-04_final
2018-05-02 10:12:41	ga_ls8c_ard_3-0-0_099078_2018-05-02_final
2018-10-16 10:21:32	ga_ls8c_ard_3-0-0_100083_2018-10-16_final
2018-12-04 09:27:58	ga_ls8c_ard_3-0-0_091088_2018-12-03_final
2018-12-05 11:41:44	ga_ls8c_ard_3-0-0_114067_2018-12-05_final
2018-12-12 10:09:48	ga_ls8c_ard_3-0-0_099069_2018-12-12_final
2018-12-29 10:53:04	ga_ls8c_ard_3-0-0_106069_2018-12-29_final
2019-01-08 09:50:27	ga_ls8c_ard_3-0-0_096067_2019-01-08_final
2019-01-13 10:10:10	ga_ls8c_ard_3-0-0_099070_2019-01-13_final
2019-03-29 11:31:01	ga_ls8c_ard_3-1-0_112072_2019-03-29_final
2020-01-20 11:24:15	ga_ls8c_ard_3-1-0_111069_2020-01-20_final
2020-02-29 10:39:24	ga_ls8c_ard_3-1-0_103081_2020-02-29_final
2020-04-19 10:27:03	ga_ls8c_ard_3-1-0_101082_2020-04-19_final
2020-10-11 09:46:09	ga_ls8c_ard_3-1-0_094086_2020-10-11_final
2020-12-17 10:09:28	ga_ls8c_ard_3-2-0_099067_2020-12-17_final
2020-12-21 09:44:44	ga_ls8c_ard_3-2-0_095067_2020-12-21_final
2021-02-27 11:01:46	ga_ls8c_ard_3-2-0_107075_2021-02-27_final
2021-04-08 10:09:16	ga_ls8c_ard_3-2-0_099068_2021-04-08_final
2021-05-06 10:38:55	ga_ls8c_ard_3-2-0_103081_2021-05-06_final
2021-06-17 09:33:29	ga_ls8c_ard_3-2-0_093071_2021-06-17_final
2021-07-20 11:57:44	ga_ls8c_ard_3-2-0_116076_2021-07-20_final
2021-08-25 11:31:39	ga_ls8c_ard_3-2-0_112072_2021-08-25_final
2022-01-25 11:23:51	ga_ls8c_ard_3-2-1_111068_2022-01-25_final
2022-03-05 11:31:28	ga_ls8c_ard_3-2-1_112072_2022-03-05_final
2022-03-10 10:10:18	ga_ls8c_ard_3-2-1_099070_2022-03-10_final
2022-03-18 09:22:47	ga_ls8c_ard_3-2-1_091075_2022-03-17_final
2022-06-20 09:34:39	ga_ls8c_ard_3-2-1_093073_2022-06-20_final
2022-09-06 11:24:15	ga_ls8c_ard_3-2-1_111068_2022-09-06_final
2022-10-01 11:22:56	ga_ls8c_ard_3-2-1_110080_2022-10-01_final
2022-11-13 11:05:56	ga_ls8c_ard_3-2-1_107084_2022-11-13_final
2023-02-10 09:17:26	ga_ls8c_ard_3-2-1_090076_2023-02-09_final
2023-03-21 09:22:46	ga_ls8c_ard_3-2-1_091075_2023-03-20_final
2023-07-10 10:21:47	ga_ls8c_ard_3-2-1_100084_2023-07-10_final
2023-08-26 11:13:43	ga_ls8c_ard_3-2-1_109074_2023-08-26_final
2023-11-14 09:34:37	ga_ls8c_ard_3-2-1_093073_2023-11-14_final
2023-11-18 09:16:44	ga_ls8c_ard_3-2-1_089090_2023-11-17_final
2024-01-28 09:17:07	ga_ls8c_ard_3-2-1_090076_2024-01-27_final
2024-03-19 11:23:52	ga_ls8c_ard_3-2-1_111069_2024-03-19_final
2024-03-19 11:24:16	ga_ls8c_ard_3-2-1_111070_2024-03-19_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years