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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
2013-06-13 09:27:16	ga_ls8c_ard_3-0-0_091081_2013-06-12_final
2013-10-20 11:48:27	ga_ls8c_ard_3-0-0_114079_2013-10-20_final
2014-11-07 09:21:55	ga_ls8c_ard_3-0-0_091072_2014-11-06_final
2015-06-11 10:09:35	ga_ls8c_ard_3-0-0_099070_2015-06-11_final
2015-07-22 10:09:19	ga_ls8c_ard_3-0-0_098084_2015-07-22_final
2015-08-04 09:33:16	ga_ls8c_ard_3-0-0_093071_2015-08-04_final
2015-08-11 09:45:05	ga_ls8c_ard_3-0-0_094085_2015-08-11_final
2015-11-10 11:04:16	ga_ls8c_ard_3-0-0_107081_2015-11-10_final
2015-11-14 10:37:57	ga_ls8c_ard_3-0-0_103077_2015-11-14_final
2016-04-22 10:38:58	ga_ls8c_ard_3-0-0_103081_2016-04-22_final
2016-05-06 09:15:43	ga_ls8c_ard_3-0-0_089089_2016-05-05_final
2016-07-31 11:51:13	ga_ls8c_ard_3-0-0_115075_2016-07-31_final
2016-08-20 11:30:11	ga_ls8c_ard_3-0-0_111084_2016-08-20_final
2016-12-08 11:38:45	ga_ls8c_ard_3-0-0_113074_2016-12-08_final
2016-12-24 09:57:48	ga_ls8c_ard_3-0-0_097069_2016-12-24_final
2017-01-31 11:03:25	ga_ls8c_ard_3-0-0_107079_2017-01-31_final
2017-04-01 11:24:04	ga_ls8c_ard_3-0-0_111070_2017-04-01_final
2017-12-03 09:10:40	ga_ls8c_ard_3-0-0_089075_2017-12-02_final
2018-01-09 11:07:15	ga_ls8c_ard_3-0-0_108073_2018-01-09_final
2018-06-19 11:50:08	ga_ls8c_ard_3-0-0_115075_2018-06-19_final
2018-07-09 09:45:55	ga_ls8c_ard_3-0-0_095073_2018-07-09_final
2018-09-08 09:22:17	ga_ls8c_ard_3-0-0_090090_2018-09-07_final
2018-11-25 09:25:48	ga_ls8c_ard_3-0-0_092067_2018-11-24_final
2019-03-06 11:27:20	ga_ls8c_ard_3-0-0_111078_2019-03-06_final
2019-03-23 10:28:03	ga_ls8c_ard_3-1-0_102069_2019-03-23_final
2019-04-08 10:33:10	ga_ls8c_ard_3-1-0_102082_2019-04-08_final
2019-04-20 09:21:19	ga_ls8c_ard_3-0-0_090088_2019-04-19_final
2019-05-25 09:45:16	ga_ls8c_ard_3-0-0_095070_2019-05-25_final
2019-07-13 10:28:48	ga_ls8c_ard_3-1-0_102070_2019-07-13_final
2019-08-24 11:07:19	ga_ls8c_ard_3-1-0_108073_2019-08-24_final
2019-10-12 10:14:18	ga_ls8c_ard_3-1-0_099079_2019-10-12_final
2019-10-23 09:57:46	ga_ls8c_ard_3-1-0_096084_2019-10-23_final
2019-11-23 10:49:43	ga_ls8c_ard_3-1-0_105075_2019-11-23_final
2020-09-05 10:02:44	ga_ls8c_ard_3-2-1_098066_2020-09-05_final
2020-11-16 10:53:53	ga_ls8c_ard_3-1-0_106070_2020-11-16_final
2021-05-28 09:56:53	ga_ls8c_ard_3-2-0_097068_2021-05-28_final
2021-08-03 10:28:08	ga_ls8c_ard_3-2-0_102068_2021-08-03_final
2021-10-17 11:53:14	ga_ls8c_ard_3-2-0_115079_2021-10-17_final
2022-02-26 11:26:07	ga_ls8c_ard_3-2-1_111074_2022-02-26_final
2022-03-03 10:03:46	ga_ls8c_ard_3-2-1_098069_2022-03-03_final
2022-05-24 11:36:12	ga_ls8c_ard_3-2-1_112084_2022-05-24_final
2022-06-09 09:57:53	ga_ls8c_ard_3-2-1_096085_2022-06-09_final
2022-08-02 10:56:01	ga_ls8c_ard_3-2-1_106075_2022-08-02_final
2022-10-18 10:25:14	ga_ls8c_ard_3-2-1_101075_2022-10-18_final
2023-03-10 11:20:17	ga_ls8c_ard_3-2-1_110075_2023-03-10_final
2023-04-13 09:32:13	ga_ls8c_ard_3-2-1_092084_2023-04-13_final
2023-07-19 11:50:54	ga_ls8c_ard_3-2-1_115075_2023-07-19_final
2023-12-30 11:24:15	ga_ls8c_ard_3-2-1_111069_2023-12-30_final
2024-03-03 11:25:38	ga_ls8c_ard_3-2-1_111073_2024-03-03_final
2024-03-18 10:42:13	ga_ls8c_ard_3-2-1_104073_2024-03-18_final
2024-04-14 10:27:25	ga_ls8c_ard_3-2-1_101083_2024-04-14_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