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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

49 results

Time (local)	Label
2013-08-19 11:32:18	ga_ls8c_ard_3-0-0_112069_2013-08-19_final
2014-01-05 09:35:47	ga_ls8c_ard_3-0-0_093073_2014-01-05_final
2014-02-06 09:35:02	ga_ls8c_ard_3-0-0_093072_2014-02-06_final
2014-07-09 09:27:42	ga_ls8c_ard_3-0-0_092072_2014-07-08_final
2014-08-12 09:17:09	ga_ls8c_ard_3-0-0_090076_2014-08-11_final
2015-08-13 09:28:21	ga_ls8c_ard_3-0-0_092074_2015-08-12_final
2015-11-26 09:21:50	ga_ls8c_ard_3-0-0_091072_2015-11-25_final
2015-11-26 09:22:14	ga_ls8c_ard_3-0-0_091073_2015-11-25_final
2015-11-28 09:10:16	ga_ls8c_ard_3-0-0_089074_2015-11-27_final
2015-12-21 09:17:14	ga_ls8c_ard_3-0-0_090076_2015-12-20_final
2016-06-05 09:21:45	ga_ls8c_ard_3-0-0_091073_2016-06-04_final
2016-06-16 09:07:14	ga_ls8c_ard_3-0-0_088083_2016-06-15_final
2016-09-18 09:22:55	ga_ls8c_ard_3-0-0_090090_2016-09-17_final
2017-06-15 09:28:22	ga_ls8c_ard_3-0-0_092074_2017-06-14_final
2017-07-08 09:39:50	ga_ls8c_ard_3-0-0_093087_2017-07-08_final
2017-07-15 11:17:44	ga_ls8c_ard_3-0-0_110069_2017-07-15_final
2017-07-29 11:30:13	ga_ls8c_ard_3-0-0_112069_2017-07-29_final
2017-09-30 10:50:02	ga_ls8c_ard_3-0-0_105076_2017-09-30_final
2017-10-09 09:07:48	ga_ls8c_ard_3-0-0_088083_2017-10-08_final
2017-12-10 09:17:14	ga_ls8c_ard_3-0-0_090076_2017-12-09_final
2017-12-13 09:45:46	ga_ls8c_ard_3-0-0_095070_2017-12-13_final
2018-01-27 10:55:31	ga_ls8c_ard_3-0-0_106075_2018-01-27_final
2018-02-01 09:34:19	ga_ls8c_ard_3-0-0_093073_2018-02-01_final
2018-02-08 09:39:40	ga_ls8c_ard_3-0-0_094071_2018-02-08_final
2018-03-10 11:31:29	ga_ls8c_ard_3-0-0_112073_2018-03-10_final
2018-04-15 09:27:59	ga_ls8c_ard_3-0-0_092074_2018-04-14_final
2018-04-19 09:06:48	ga_ls8c_ard_3-0-0_088083_2018-04-18_final
2018-05-21 09:06:28	ga_ls8c_ard_3-0-0_088083_2018-05-20_final
2018-09-27 09:45:18	ga_ls8c_ard_3-0-0_095070_2018-09-27_final
2018-10-10 09:16:54	ga_ls8c_ard_3-0-0_090076_2018-10-09_final
2018-11-18 09:20:01	ga_ls8c_ard_3-0-0_091068_2018-11-17_final
2018-11-26 11:52:44	ga_ls8c_ard_3-0-0_115079_2018-11-26_final
2019-03-17 09:28:15	ga_ls8c_ard_3-1-0_092074_2019-03-16_final
2019-05-04 09:28:06	ga_ls8c_ard_3-0-0_092074_2019-05-03_final
2019-10-11 09:29:03	ga_ls8c_ard_3-1-0_092074_2019-10-10_final
2019-11-26 09:40:33	ga_ls8c_ard_3-1-0_094072_2019-11-26_final
2020-01-06 09:34:39	ga_ls8c_ard_3-1-0_093073_2020-01-06_final
2020-05-15 09:19:30	ga_ls8c_ard_3-1-0_091068_2020-05-14_final
2020-05-20 09:39:40	ga_ls8c_ard_3-1-0_094072_2020-05-20_final
2020-07-23 11:17:49	ga_ls8c_ard_3-1-0_110069_2020-07-23_final
2021-01-04 09:57:26	ga_ls8c_ard_3-2-0_097068_2021-01-04_final
2021-12-17 11:18:15	ga_ls8c_ard_3-2-1_110069_2021-12-17_final
2022-08-10 11:47:55	ga_ls8c_ard_3-2-1_114081_2022-08-10_final
2022-10-14 09:10:37	ga_ls8c_ard_3-2-1_089074_2022-10-13_final
2022-12-17 09:10:59	ga_ls8c_ard_3-2-1_089075_2022-12-16_final
2023-04-06 09:27:45	ga_ls8c_ard_3-2-1_091088_2023-04-05_final
2023-05-15 09:27:56	ga_ls8c_ard_3-2-1_092074_2023-05-14_final
2023-08-04 10:13:22	ga_ls8c_ard_3-2-1_099078_2023-08-04_final
2024-04-06 09:39:38	ga_ls8c_ard_3-2-1_093087_2024-04-06_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