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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

59 results

Time (local)	Label
2013-10-25 10:24:27	ga_ls8c_ard_3-0-0_101070_2013-10-25_final
2014-04-03 10:26:05	ga_ls8c_ard_3-0-0_101078_2014-04-03_final
2014-06-16 09:28:35	ga_ls8c_ard_3-0-0_091090_2014-06-15_final
2014-07-21 11:30:09	ga_ls8c_ard_3-0-0_112069_2014-07-21_final
2014-11-10 09:58:24	ga_ls8c_ard_3-0-0_096086_2014-11-10_final
2015-01-02 10:09:57	ga_ls8c_ard_3-0-0_099069_2015-01-02_final
2015-04-12 09:43:47	ga_ls8c_ard_3-0-0_095067_2015-04-12_final
2015-05-04 09:14:53	ga_ls8c_ard_3-0-0_089088_2015-05-03_final
2015-06-15 09:45:17	ga_ls8c_ard_3-0-0_095071_2015-06-15_final
2015-06-18 11:57:05	ga_ls8c_ard_3-0-0_116076_2015-06-18_final
2015-06-19 09:28:10	ga_ls8c_ard_3-0-0_091090_2015-06-18_final
2015-07-07 09:15:11	ga_ls8c_ard_3-0-0_089088_2015-07-06_final
2015-07-23 10:49:24	ga_ls8c_ard_3-0-0_105076_2015-07-23_final
2015-07-24 11:31:52	ga_ls8c_ard_3-0-0_112074_2015-07-24_final
2016-11-24 09:44:45	ga_ls8c_ard_3-0-0_095067_2016-11-24_final
2017-05-18 10:44:41	ga_ls8c_ard_3-0-0_104080_2017-05-18_final
2017-09-24 09:44:36	ga_ls8c_ard_3-0-0_095067_2017-09-24_final
2017-09-30 09:16:20	ga_ls8c_ard_3-0-0_089089_2017-09-29_final
2018-02-06 11:29:20	ga_ls8c_ard_3-0-0_112067_2018-02-06_final
2018-04-14 10:22:01	ga_ls8c_ard_3-0-0_101070_2018-04-14_final
2018-06-10 11:56:13	ga_ls8c_ard_3-0-0_116075_2018-06-10_final
2018-08-12 09:39:50	ga_ls8c_ard_3-0-0_093088_2018-08-12_final
2018-09-14 11:57:00	ga_ls8c_ard_3-0-0_116075_2018-09-14_final
2018-09-14 11:57:24	ga_ls8c_ard_3-0-0_116076_2018-09-14_final
2018-11-14 09:44:21	ga_ls8c_ard_3-0-0_095067_2018-11-14_final
2018-11-26 10:10:15	ga_ls8c_ard_3-0-0_099070_2018-11-26_final
2018-11-30 08:10:38	ga_ls8c_ard_3-2-1_079080_2018-11-29_final
2018-12-12 10:09:48	ga_ls8c_ard_3-0-0_099069_2018-12-12_final
2019-01-17 09:44:14	ga_ls8c_ard_3-0-0_095067_2019-01-17_final
2019-04-30 11:29:17	ga_ls8c_ard_3-0-0_112068_2019-04-30_final
2019-06-21 09:34:30	ga_ls8c_ard_3-1-0_092089_2019-06-21_final
2019-07-30 09:40:28	ga_ls8c_ard_3-1-0_093088_2019-07-30_final
2020-02-07 11:14:59	ga_ls8c_ard_3-1-0_109077_2020-02-07_final
2020-05-24 09:18:56	ga_ls8c_ard_3-1-0_090082_2020-05-23_final
2020-05-30 11:56:52	ga_ls8c_ard_3-1-0_116075_2020-05-30_final
2020-07-10 10:16:09	ga_ls8c_ard_3-1-0_099085_2020-07-10_final
2020-09-19 11:57:39	ga_ls8c_ard_3-1-0_116075_2020-09-19_final
2020-09-19 11:58:03	ga_ls8c_ard_3-1-0_116076_2020-09-19_final
2020-11-10 11:31:45	ga_ls8c_ard_3-1-0_112072_2020-11-10_final
2020-11-16 10:59:04	ga_ls8c_ard_3-1-0_106083_2020-11-16_final
2020-12-14 09:40:34	ga_ls8c_ard_3-1-0_094072_2020-12-14_final
2020-12-18 10:53:32	ga_ls8c_ard_3-2-0_106069_2020-12-18_final
2021-01-18 10:13:40	ga_ls8c_ard_3-2-0_099078_2021-01-18_final
2021-01-22 11:25:02	ga_ls8c_ard_3-2-0_111071_2021-01-22_final
2021-02-13 10:47:06	ga_ls8c_ard_3-2-0_105069_2021-02-13_final
2021-05-05 11:29:22	ga_ls8c_ard_3-2-0_112068_2021-05-05_final
2021-06-26 09:28:32	ga_ls8c_ard_3-2-0_092074_2021-06-25_final
2021-07-26 09:45:49	ga_ls8c_ard_3-2-0_094086_2021-07-26_final
2021-08-29 09:28:52	ga_ls8c_ard_3-2-0_092074_2021-08-28_final
2021-09-16 09:16:59	ga_ls8c_ard_3-2-0_090075_2021-09-15_final
2021-09-23 09:28:22	ga_ls8c_ard_3-2-0_091088_2021-09-22_final
2021-11-26 09:22:26	ga_ls8c_ard_3-2-0_091073_2021-11-25_final
2021-12-22 09:57:29	ga_ls8c_ard_3-2-1_097068_2021-12-22_final
2022-01-21 10:10:55	ga_ls8c_ard_3-2-1_099071_2022-01-21_final
2022-04-19 11:05:11	ga_ls8c_ard_3-2-1_107084_2022-04-19_final
2022-05-20 11:58:32	ga_ls8c_ard_3-2-1_116078_2022-05-20_final
2022-07-23 11:58:54	ga_ls8c_ard_3-2-1_116078_2022-07-23_final
2023-01-20 10:39:45	ga_ls8c_ard_3-2-1_103081_2023-01-20_final
2023-02-02 10:10:31	ga_ls8c_ard_3-2-1_098085_2023-02-02_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