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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
2013-07-25 11:44:01	ga_ls8c_ard_3-0-0_113083_2013-07-25_final
2013-11-18 11:15:47	ga_ls8c_ard_3-0-0_109075_2013-11-18_final
2014-08-03 09:22:04	ga_ls8c_ard_3-0-0_091073_2014-08-02_final
2014-12-19 09:59:41	ga_ls8c_ard_3-0-0_097074_2014-12-19_final
2015-01-03 09:22:43	ga_ls8c_ard_3-0-0_090090_2015-01-02_final
2015-08-18 11:29:25	ga_ls8c_ard_3-0-0_111083_2015-08-18_final
2015-08-27 11:17:42	ga_ls8c_ard_3-0-0_110069_2015-08-27_final
2016-02-12 09:32:01	ga_ls8c_ard_3-0-0_093067_2016-02-12_final
2016-03-19 10:46:24	ga_ls8c_ard_3-0-0_105068_2016-03-19_final
2016-03-30 10:32:56	ga_ls8c_ard_3-0-0_102081_2016-03-30_final
2016-04-28 09:57:31	ga_ls8c_ard_3-0-0_097070_2016-04-28_final
2016-06-06 11:45:54	ga_ls8c_ard_3-0-0_114078_2016-06-06_final
2016-07-24 10:07:20	ga_ls8c_ard_3-0-0_098078_2016-07-24_final
2016-09-12 11:32:06	ga_ls8c_ard_3-0-0_112073_2016-09-12_final
2016-10-10 10:19:12	ga_ls8c_ard_3-0-0_100076_2016-10-10_final
2017-01-08 10:52:59	ga_ls8c_ard_3-0-0_106068_2017-01-08_final
2017-05-31 10:08:43	ga_ls8c_ard_3-0-0_099067_2017-05-31_final
2017-06-04 11:22:55	ga_ls8c_ard_3-0-0_111067_2017-06-04_final
2017-08-24 10:28:57	ga_ls8c_ard_3-0-0_102070_2017-08-24_final
2017-12-20 11:30:52	ga_ls8c_ard_3-0-0_112070_2017-12-20_final
2018-01-01 10:21:51	ga_ls8c_ard_3-0-0_100083_2018-01-01_final
2018-01-04 10:46:45	ga_ls8c_ard_3-0-0_105068_2018-01-04_final
2018-02-21 09:09:53	ga_ls8c_ard_3-0-0_089074_2018-02-20_final
2018-08-31 11:46:10	ga_ls8c_ard_3-0-0_114079_2018-08-31_final
2018-09-26 09:06:26	ga_ls8c_ard_3-1-0_088081_2018-09-25_final
2018-10-26 09:22:11	ga_ls8c_ard_3-0-0_090089_2018-10-25_final
2018-12-22 09:13:35	ga_ls8c_ard_3-0-0_089083_2018-12-21_final
2019-10-02 11:18:04	ga_ls8c_ard_3-1-0_109084_2019-10-02_final
2019-12-14 09:29:45	ga_ls8c_ard_3-2-0_092076_2019-12-13_final
2020-05-23 10:13:22	ga_ls8c_ard_3-1-0_099079_2020-05-23_final
2020-05-26 09:06:35	ga_ls8c_ard_3-1-0_088082_2020-05-25_final
2020-06-08 10:09:06	ga_ls8c_ard_3-1-0_099068_2020-06-08_final
2020-07-25 11:07:52	ga_ls8c_ard_3-1-0_108075_2020-07-25_final
2020-08-30 09:06:28	ga_ls8c_ard_3-1-0_088080_2020-08-29_final
2021-11-27 10:04:30	ga_ls8c_ard_3-2-0_098070_2021-11-27_final
2022-02-21 11:07:34	ga_ls8c_ard_3-2-1_108074_2022-02-21_final
2022-03-12 10:01:07	ga_ls8c_ard_3-2-1_097078_2022-03-12_final
2022-03-30 09:52:08	ga_ls8c_ard_3-2-1_095087_2022-03-30_final
2022-04-12 09:17:19	ga_ls8c_ard_3-2-1_090077_2022-04-11_final
2022-06-27 11:18:09	ga_ls8c_ard_3-2-1_110069_2022-06-27_final
2022-08-01 10:10:21	ga_ls8c_ard_3-2-1_099069_2022-08-01_final
2022-12-13 11:15:02	ga_ls8c_ard_3-2-1_109076_2022-12-13_final
2023-01-12 11:24:27	ga_ls8c_ard_3-2-1_111069_2023-01-12_final
2023-02-25 11:51:15	ga_ls8c_ard_3-2-1_115075_2023-02-25_final
2023-05-06 09:38:39	ga_ls8c_ard_3-2-1_093085_2023-05-06_final
2023-07-02 11:05:34	ga_ls8c_ard_3-2-1_108070_2023-07-02_final
2023-12-10 10:10:03	ga_ls8c_ard_3-2-1_099069_2023-12-10_final
2023-12-21 11:32:29	ga_ls8c_ard_3-2-1_112074_2023-12-21_final
2024-02-12 10:08:50	ga_ls8c_ard_3-2-1_099066_2024-02-12_final
2024-03-19 11:23:52	ga_ls8c_ard_3-2-1_111069_2024-03-19_final
2024-03-30 11:07:33	ga_ls8c_ard_3-2-1_108075_2024-03-30_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