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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

46 results

Time (local)	Label
2013-06-12 10:23:18	ga_ls8c_ard_3-0-0_100082_2013-06-12_final
2014-01-25 09:17:38	ga_ls8c_ard_3-0-0_089090_2014-01-24_final
2014-10-25 11:32:29	ga_ls8c_ard_3-0-0_112074_2014-10-25_final
2015-01-25 10:16:51	ga_ls8c_ard_3-0-0_100071_2015-01-25_final
2015-10-05 09:44:26	ga_ls8c_ard_3-0-0_095067_2015-10-05_final
2016-03-13 09:45:51	ga_ls8c_ard_3-0-0_095071_2016-03-13_final
2016-05-20 11:02:57	ga_ls8c_ard_3-0-0_107079_2016-05-20_final
2016-08-07 10:19:44	ga_ls8c_ard_3-0-0_100078_2016-08-07_final
2016-10-14 09:58:30	ga_ls8c_ard_3-0-0_096086_2016-10-14_final
2016-10-29 09:10:28	ga_ls8c_ard_3-0-0_089074_2016-10-28_final
2016-10-30 11:30:37	ga_ls8c_ard_3-0-0_112069_2016-10-30_final
2017-05-12 11:22:05	ga_ls8c_ard_3-0-0_110081_2017-05-12_final
2017-05-30 09:27:27	ga_ls8c_ard_3-0-0_092072_2017-05-29_final
2017-06-01 10:52:00	ga_ls8c_ard_3-0-0_106067_2017-06-01_final
2017-12-29 09:52:34	ga_ls8c_ard_3-0-0_095087_2017-12-29_final
2018-02-02 10:19:10	ga_ls8c_ard_3-0-0_100077_2018-02-02_final
2018-02-15 11:23:06	ga_ls8c_ard_3-0-0_111067_2018-02-15_final
2018-03-19 09:45:57	ga_ls8c_ard_3-0-0_095072_2018-03-19_final
2018-08-30 11:04:30	ga_ls8c_ard_3-0-0_107083_2018-08-30_final
2018-11-25 09:29:23	ga_ls8c_ard_3-0-0_092076_2018-11-24_final
2019-01-19 09:33:52	ga_ls8c_ard_3-0-0_093072_2019-01-19_final
2019-03-06 09:44:04	ga_ls8c_ard_3-0-0_095067_2019-03-06_final
2019-08-15 11:17:03	ga_ls8c_ard_3-1-0_109082_2019-08-15_final
2019-08-29 09:44:36	ga_ls8c_ard_3-1-0_095067_2019-08-29_final
2019-12-04 10:33:34	ga_ls8c_ard_3-1-0_102081_2019-12-04_final
2020-06-03 09:57:41	ga_ls8c_ard_3-1-0_096086_2020-06-03_final
2020-06-08 10:09:30	ga_ls8c_ard_3-1-0_099069_2020-06-08_final
2020-07-11 10:52:14	ga_ls8c_ard_3-1-0_106067_2020-07-11_final
2021-03-01 10:46:36	ga_ls8c_ard_3-2-0_105068_2021-03-01_final
2021-04-24 10:09:33	ga_ls8c_ard_3-2-0_099069_2021-04-24_final
2021-07-05 11:02:52	ga_ls8c_ard_3-2-0_107078_2021-07-05_final
2021-11-11 10:07:43	ga_ls8c_ard_3-2-0_098078_2021-11-11_final
2021-11-15 09:40:34	ga_ls8c_ard_3-2-0_094072_2021-11-15_final
2022-01-20 09:28:51	ga_ls8c_ard_3-2-1_092074_2022-01-19_final
2022-01-27 09:36:11	ga_ls8c_ard_3-2-1_093077_2022-01-27_final
2022-07-07 10:17:09	ga_ls8c_ard_3-2-1_100071_2022-07-07_final
2022-09-20 11:42:17	ga_ls8c_ard_3-2-1_113082_2022-09-20_final
2022-10-03 11:11:46	ga_ls8c_ard_3-2-1_108083_2022-10-03_final
2022-10-12 11:05:28	ga_ls8c_ard_3-2-1_107083_2022-10-12_final
2022-10-18 10:25:14	ga_ls8c_ard_3-2-1_101075_2022-10-18_final
2023-01-24 10:09:53	ga_ls8c_ard_3-2-1_099068_2023-01-24_final
2023-02-02 10:10:07	ga_ls8c_ard_3-2-1_098084_2023-02-02_final
2023-03-06 10:09:45	ga_ls8c_ard_3-2-1_098084_2023-03-06_final
2023-04-12 10:22:39	ga_ls8c_ard_3-2-1_101071_2023-04-12_final
2023-05-04 11:23:32	ga_ls8c_ard_3-2-1_111069_2023-05-04_final
2023-10-20 09:39:58	ga_ls8c_ard_3-2-1_094071_2023-10-20_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