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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

62 results

Time (local)	Label
2014-01-31 11:52:17	ga_ls8c_ard_3-0-0_115075_2014-01-31_final
2014-02-17 09:19:55	ga_ls8c_ard_3-0-0_090081_2014-02-16_final
2014-03-30 09:12:21	ga_ls8c_ard_3-0-0_089079_2014-03-29_final
2014-03-30 09:16:20	ga_ls8c_ard_3-0-0_089089_2014-03-29_final
2014-12-05 11:29:51	ga_ls8c_ard_3-0-0_111083_2014-12-05_final
2015-01-05 10:40:28	ga_ls8c_ard_3-0-0_104068_2015-01-05_final
2015-04-15 10:18:41	ga_ls8c_ard_3-0-0_100077_2015-04-15_final
2015-07-31 11:40:27	ga_ls8c_ard_3-0-0_113080_2015-07-31_final
2015-12-21 09:20:26	ga_ls8c_ard_3-0-0_090084_2015-12-20_final
2016-02-17 11:30:35	ga_ls8c_ard_3-0-0_112070_2016-02-17_final
2016-05-09 11:19:28	ga_ls8c_ard_3-0-0_110074_2016-05-09_final
2016-10-22 10:40:47	ga_ls8c_ard_3-0-0_104068_2016-10-22_final
2017-01-07 10:09:43	ga_ls8c_ard_3-0-0_099068_2017-01-07_final
2017-03-05 10:03:34	ga_ls8c_ard_3-0-0_098069_2017-03-05_final
2017-07-02 11:52:11	ga_ls8c_ard_3-0-0_115078_2017-07-02_final
2017-12-02 10:09:53	ga_ls8c_ard_3-0-0_098084_2017-12-02_final
2018-01-02 11:01:31	ga_ls8c_ard_3-0-0_107074_2018-01-02_final
2018-01-19 10:07:21	ga_ls8c_ard_3-0-0_098078_2018-01-19_final
2018-02-19 09:21:52	ga_ls8c_ard_3-0-0_091073_2018-02-18_final
2018-02-27 10:13:38	ga_ls8c_ard_3-0-0_099079_2018-02-27_final
2018-05-18 10:14:30	ga_ls8c_ard_3-0-0_099083_2018-05-18_final
2018-11-14 11:25:13	ga_ls8c_ard_3-0-0_111072_2018-11-14_final
2019-02-01 09:06:30	ga_ls8c_ard_3-1-0_088081_2019-01-31_final
2019-02-08 10:48:46	ga_ls8c_ard_3-0-0_105074_2019-02-08_final
2019-04-16 09:40:29	ga_ls8c_ard_3-1-0_094074_2019-04-16_final
2019-04-20 09:17:19	ga_ls8c_ard_3-0-0_090078_2019-04-19_final
2019-05-09 11:23:36	ga_ls8c_ard_3-0-0_111069_2019-05-09_final
2019-05-27 11:13:49	ga_ls8c_ard_3-0-0_109075_2019-05-27_final
2019-09-27 09:21:02	ga_ls8c_ard_3-1-0_090085_2019-09-26_final
2019-10-14 11:41:38	ga_ls8c_ard_3-1-0_113081_2019-10-14_final
2020-01-20 11:25:50	ga_ls8c_ard_3-1-0_111073_2020-01-20_final
2020-02-19 09:57:59	ga_ls8c_ard_3-1-0_097070_2020-02-19_final
2020-03-28 09:23:25	ga_ls8c_ard_3-1-0_091077_2020-03-27_final
2020-07-08 10:27:18	ga_ls8c_ard_3-1-0_101082_2020-07-08_final
2020-08-01 11:13:40	ga_ls8c_ard_3-1-0_109074_2020-08-01_final
2020-08-29 09:57:18	ga_ls8c_ard_3-1-0_097068_2020-08-29_final
2020-11-01 11:42:45	ga_ls8c_ard_3-1-0_113084_2020-11-01_final
2020-11-28 11:20:15	ga_ls8c_ard_3-1-0_110074_2020-11-28_final
2021-04-25 09:21:30	ga_ls8c_ard_3-2-0_090088_2021-04-24_final
2021-05-23 09:39:29	ga_ls8c_ard_3-2-0_094071_2021-05-23_final
2021-09-07 09:22:20	ga_ls8c_ard_3-2-0_091073_2021-09-06_final
2021-09-15 11:53:05	ga_ls8c_ard_3-2-0_115079_2021-09-15_final
2021-10-30 11:19:56	ga_ls8c_ard_3-2-0_110073_2021-10-30_final
2022-02-16 10:52:40	ga_ls8c_ard_3-2-1_105083_2022-02-16_final
2022-02-23 10:53:13	ga_ls8c_ard_3-2-1_106069_2022-02-23_final
2022-04-06 09:57:33	ga_ls8c_ard_3-2-1_096085_2022-04-06_final
2022-04-21 09:16:19	ga_ls8c_ard_3-2-1_089090_2022-04-20_final
2022-06-04 11:13:46	ga_ls8c_ard_3-2-1_109074_2022-06-04_final
2023-01-12 11:25:39	ga_ls8c_ard_3-2-1_111072_2023-01-12_final
2023-02-10 09:17:26	ga_ls8c_ard_3-2-1_090076_2023-02-09_final
2023-02-24 11:06:01	ga_ls8c_ard_3-2-1_108070_2023-02-24_final
2023-02-25 10:13:34	ga_ls8c_ard_3-2-1_099078_2023-02-25_final
2023-03-20 11:58:29	ga_ls8c_ard_3-2-1_116078_2023-03-20_final
2023-04-02 11:23:51	ga_ls8c_ard_3-2-1_111069_2023-04-02_final
2023-05-02 09:56:38	ga_ls8c_ard_3-2-1_097068_2023-05-02_final
2023-06-25 09:28:23	ga_ls8c_ard_3-2-1_091090_2023-06-24_final
2023-12-10 10:13:15	ga_ls8c_ard_3-2-1_099077_2023-12-10_final
2024-01-05 09:11:47	ga_ls8c_ard_3-2-1_089078_2024-01-04_final
2024-01-31 11:25:44	ga_ls8c_ard_3-2-1_111073_2024-01-31_final
2024-02-14 09:58:03	ga_ls8c_ard_3-2-1_097070_2024-02-14_final
2024-02-23 11:31:31	ga_ls8c_ard_3-2-1_112072_2024-02-23_final
2024-03-26 11:31:30	ga_ls8c_ard_3-2-1_112073_2024-03-26_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years