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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

62 results

Time (local)	Label
2013-06-12 10:23:18	ga_ls8c_ard_3-0-0_100082_2013-06-12_final
2013-08-29 10:35:18	ga_ls8c_ard_3-0-0_102081_2013-08-29_final
2014-04-08 10:42:33	ga_ls8c_ard_3-0-0_104073_2014-04-08_final
2014-06-11 10:45:18	ga_ls8c_ard_3-0-0_104081_2014-06-11_final
2014-07-31 10:33:13	ga_ls8c_ard_3-0-0_102081_2014-07-31_final
2014-08-17 11:14:11	ga_ls8c_ard_3-0-0_109075_2014-08-17_final
2014-11-12 11:24:08	ga_ls8c_ard_3-0-0_110084_2014-11-12_final
2014-12-02 10:54:58	ga_ls8c_ard_3-0-0_106073_2014-12-02_final
2015-01-20 09:57:09	ga_ls8c_ard_3-0-0_097068_2015-01-20_final
2015-02-08 10:31:33	ga_ls8c_ard_3-0-0_102077_2015-02-08_final
2015-03-06 09:27:35	ga_ls8c_ard_3-0-0_092072_2015-03-05_final
2015-04-23 09:25:13	ga_ls8c_ard_3-0-0_092067_2015-04-22_final
2015-08-18 09:45:44	ga_ls8c_ard_3-0-0_095071_2015-08-18_final
2015-10-10 10:09:45	ga_ls8c_ard_3-0-0_098084_2015-10-10_final
2015-11-02 11:53:19	ga_ls8c_ard_3-0-0_115080_2015-11-02_final
2016-05-27 09:28:18	ga_ls8c_ard_3-0-0_092074_2016-05-26_final
2016-06-26 09:43:13	ga_ls8c_ard_3-0-0_094080_2016-06-26_final
2016-08-20 11:30:11	ga_ls8c_ard_3-0-0_111084_2016-08-20_final
2017-04-22 10:03:32	ga_ls8c_ard_3-0-0_098070_2017-04-22_final
2017-05-18 10:45:29	ga_ls8c_ard_3-0-0_104082_2017-05-18_final
2017-07-15 09:39:39	ga_ls8c_ard_3-0-0_094071_2017-07-15_final
2017-08-27 11:05:27	ga_ls8c_ard_3-0-0_107084_2017-08-27_final
2017-10-25 10:46:19	ga_ls8c_ard_3-0-0_104082_2017-10-25_final
2017-11-15 09:22:20	ga_ls8c_ard_3-0-0_091073_2017-11-14_final
2017-11-27 11:24:15	ga_ls8c_ard_3-0-0_111069_2017-11-27_final
2018-01-31 10:29:57	ga_ls8c_ard_3-0-0_102073_2018-01-31_final
2018-04-04 09:46:37	ga_ls8c_ard_3-0-0_095074_2018-04-04_final
2018-06-20 09:16:03	ga_ls8c_ard_3-0-0_090076_2018-06-19_final
2018-06-22 09:06:30	ga_ls8c_ard_3-0-0_088083_2018-06-21_final
2018-08-30 09:22:01	ga_ls8c_ard_3-0-0_091074_2018-08-29_final
2018-09-08 09:16:41	ga_ls8c_ard_3-0-0_090076_2018-09-07_final
2018-09-15 09:28:05	ga_ls8c_ard_3-0-0_091089_2018-09-14_final
2018-11-13 09:07:28	ga_ls8c_ard_3-0-0_088083_2018-11-12_final
2018-12-10 10:26:34	ga_ls8c_ard_3-0-0_101080_2018-12-10_final
2018-12-25 11:17:47	ga_ls8c_ard_3-0-0_110069_2018-12-25_final
2019-01-28 09:27:39	ga_ls8c_ard_3-0-0_092072_2019-01-27_final
2019-03-04 11:35:19	ga_ls8c_ard_3-0-0_113067_2019-03-04_final
2019-03-19 09:16:41	ga_ls8c_ard_3-1-0_090076_2019-03-18_final
2019-04-29 09:11:07	ga_ls8c_ard_3-0-0_089078_2019-04-28_final
2019-08-14 10:33:47	ga_ls8c_ard_3-1-0_102082_2019-08-14_final
2019-09-11 09:17:21	ga_ls8c_ard_3-1-0_090076_2019-09-10_final
2020-01-16 11:53:22	ga_ls8c_ard_3-1-0_115080_2020-01-16_final
2020-09-28 11:51:54	ga_ls8c_ard_3-1-0_115076_2020-09-28_final
2020-10-08 10:50:08	ga_ls8c_ard_3-1-0_105076_2020-10-08_final
2021-07-17 11:28:00	ga_ls8c_ard_3-2-0_111079_2021-07-17_final
2021-08-13 09:28:48	ga_ls8c_ard_3-2-0_092074_2021-08-12_final
2021-10-25 09:26:54	ga_ls8c_ard_3-2-0_091084_2021-10-24_final
2022-02-05 11:08:04	ga_ls8c_ard_3-2-1_108075_2022-02-05_final
2022-02-07 09:17:37	ga_ls8c_ard_3-2-1_090077_2022-02-06_final
2022-02-11 10:33:22	ga_ls8c_ard_3-2-1_102081_2022-02-11_final
2022-08-18 10:56:07	ga_ls8c_ard_3-2-1_106075_2022-08-18_final
2022-08-21 11:26:13	ga_ls8c_ard_3-2-1_111073_2022-08-21_final
2022-08-24 10:22:38	ga_ls8c_ard_3-2-1_100084_2022-08-24_final
2022-11-25 09:47:21	ga_ls8c_ard_3-2-1_095073_2022-11-25_final
2023-01-04 10:36:16	ga_ls8c_ard_3-2-1_103072_2023-01-04_final
2023-04-20 09:33:33	ga_ls8c_ard_3-2-1_093072_2023-04-20_final
2023-05-07 11:57:35	ga_ls8c_ard_3-2-1_116077_2023-05-07_final
2023-08-08 11:27:08	ga_ls8c_ard_3-2-1_111077_2023-08-08_final
2023-09-05 10:13:29	ga_ls8c_ard_3-2-1_099078_2023-09-05_final
2023-12-02 09:22:40	ga_ls8c_ard_3-2-1_091074_2023-12-01_final
2024-01-02 10:19:49	ga_ls8c_ard_3-2-1_100078_2024-01-02_final
2024-03-19 09:52:10	ga_ls8c_ard_3-2-1_095087_2024-03-19_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