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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

67 results

Time (local)	Label
2013-04-29 11:32:26	ga_ls8c_ard_3-0-0_112070_2013-04-29_final
2013-05-29 11:46:41	ga_ls8c_ard_3-0-0_114074_2013-05-29_final
2014-02-04 09:51:49	ga_ls8c_ard_3-0-0_095083_2014-02-04_final
2014-04-09 11:24:12	ga_ls8c_ard_3-0-0_111069_2014-04-09_final
2014-06-09 10:52:28	ga_ls8c_ard_3-0-0_106068_2014-06-09_final
2014-09-02 11:11:50	ga_ls8c_ard_3-0-0_109069_2014-09-02_final
2014-09-24 10:39:55	ga_ls8c_ard_3-0-0_103082_2014-09-24_final
2014-12-12 09:54:39	ga_ls8c_ard_3-0-0_096077_2014-12-12_final
2015-01-22 11:23:39	ga_ls8c_ard_3-0-0_111068_2015-01-22_final
2015-09-28 09:45:49	ga_ls8c_ard_3-0-0_094086_2015-09-28_final
2015-10-17 11:52:25	ga_ls8c_ard_3-0-0_115078_2015-10-17_final
2016-01-06 09:21:34	ga_ls8c_ard_3-0-0_090087_2016-01-05_final
2016-08-16 10:15:35	ga_ls8c_ard_3-0-0_099083_2016-08-16_final
2016-09-23 09:40:16	ga_ls8c_ard_3-0-0_093087_2016-09-23_final
2017-02-13 10:28:01	ga_ls8c_ard_3-0-0_102068_2017-02-13_final
2017-02-23 11:07:50	ga_ls8c_ard_3-0-0_108075_2017-02-23_final
2017-06-06 11:13:22	ga_ls8c_ard_3-0-0_109074_2017-06-06_final
2017-06-29 09:39:36	ga_ls8c_ard_3-0-0_094071_2017-06-29_final
2017-08-07 11:25:41	ga_ls8c_ard_3-0-0_111073_2017-08-07_final
2017-08-09 11:14:08	ga_ls8c_ard_3-0-0_109075_2017-08-09_final
2018-01-17 10:17:20	ga_ls8c_ard_3-0-0_100072_2018-01-17_final
2018-01-21 11:32:16	ga_ls8c_ard_3-0-0_112074_2018-01-21_final
2018-02-01 09:33:55	ga_ls8c_ard_3-0-0_093072_2018-02-01_final
2018-04-13 11:17:15	ga_ls8c_ard_3-0-0_110069_2018-04-13_final
2018-05-08 09:32:44	ga_ls8c_ard_3-0-0_093071_2018-05-08_final
2018-05-22 11:23:25	ga_ls8c_ard_3-0-0_111070_2018-05-22_final
2018-06-01 10:24:40	ga_ls8c_ard_3-0-0_101078_2018-06-01_final
2018-06-09 11:12:56	ga_ls8c_ard_3-0-0_109075_2018-06-09_final
2018-09-27 11:25:47	ga_ls8c_ard_3-0-0_111074_2018-09-27_final
2018-11-26 10:10:15	ga_ls8c_ard_3-0-0_099070_2018-11-26_final
2019-03-14 10:39:02	ga_ls8c_ard_3-1-0_103081_2019-03-14_final
2019-04-06 09:06:39	ga_ls8c_ard_3-1-0_088082_2019-04-05_final
2019-06-03 11:20:03	ga_ls8c_ard_3-0-0_110075_2019-06-03_final
2019-06-16 10:48:50	ga_ls8c_ard_3-1-0_105074_2019-06-16_final
2019-08-26 10:52:58	ga_ls8c_ard_3-1-0_106068_2019-08-26_final
2019-10-13 09:21:29	ga_ls8c_ard_3-1-0_090086_2019-10-12_final
2019-12-07 11:05:16	ga_ls8c_ard_3-1-0_107083_2019-12-07_final
2020-03-20 10:13:20	ga_ls8c_ard_3-1-0_099078_2020-03-20_final
2020-04-05 11:50:52	ga_ls8c_ard_3-1-0_115075_2020-04-05_final
2020-05-01 10:49:16	ga_ls8c_ard_3-1-0_105076_2020-05-01_final
2020-05-23 10:08:58	ga_ls8c_ard_3-1-0_099068_2020-05-23_final
2020-08-22 09:51:28	ga_ls8c_ard_3-1-0_096069_2020-08-22_final
2020-09-04 09:29:03	ga_ls8c_ard_3-1-0_091090_2020-09-03_final
2020-12-02 10:52:44	ga_ls8c_ard_3-1-0_106067_2020-12-02_final
2021-01-15 09:40:00	ga_ls8c_ard_3-2-0_094071_2021-01-15_final
2021-02-23 11:23:19	ga_ls8c_ard_3-2-0_111067_2021-02-23_final
2021-03-07 10:09:28	ga_ls8c_ard_3-2-0_099068_2021-03-07_final
2021-05-12 09:56:43	ga_ls8c_ard_3-2-0_097068_2021-05-12_final
2021-05-25 09:25:33	ga_ls8c_ard_3-2-0_092067_2021-05-24_final
2021-06-08 11:17:42	ga_ls8c_ard_3-2-0_110069_2021-06-08_final
2021-08-08 10:49:54	ga_ls8c_ard_3-2-0_105076_2021-08-08_final
2021-11-19 09:17:50	ga_ls8c_ard_3-2-0_090077_2021-11-18_final
2022-03-14 11:24:02	ga_ls8c_ard_3-2-1_111069_2022-03-14_final
2022-03-21 09:57:14	ga_ls8c_ard_3-2-1_096084_2022-03-21_final
2022-04-03 09:21:49	ga_ls8c_ard_3-2-1_091073_2022-04-02_final
2022-06-02 11:24:30	ga_ls8c_ard_3-2-1_111070_2022-06-02_final
2022-07-17 09:22:07	ga_ls8c_ard_3-2-1_090088_2022-07-16_final
2022-08-09 11:03:27	ga_ls8c_ard_3-2-1_107078_2022-08-09_final
2022-11-25 09:52:33	ga_ls8c_ard_3-2-1_095086_2022-11-25_final
2022-12-31 11:00:35	ga_ls8c_ard_3-2-1_107071_2022-12-31_final
2023-02-19 09:11:55	ga_ls8c_ard_3-2-1_089078_2023-02-18_final
2023-03-07 09:10:31	ga_ls8c_ard_3-2-1_089075_2023-03-06_final
2023-05-26 10:49:07	ga_ls8c_ard_3-2-1_105076_2023-05-26_final
2023-09-14 10:09:47	ga_ls8c_ard_3-2-1_098084_2023-09-14_final
2023-12-14 11:26:16	ga_ls8c_ard_3-2-1_111074_2023-12-14_final
2024-01-01 11:13:51	ga_ls8c_ard_3-2-1_109074_2024-01-01_final
2024-02-05 10:09:50	ga_ls8c_ard_3-2-1_098084_2024-02-05_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