Search ga_ls8c_ard_3 whole collection

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

First 100 results (query limit)

Time (local)	Label
2013-05-21 09:24:19	ga_ls8c_ard_3-0-0_090089_2013-05-20_final
2013-06-22 09:24:12	ga_ls8c_ard_3-0-0_090089_2013-06-21_final
2013-07-08 09:24:16	ga_ls8c_ard_3-0-0_090089_2013-07-07_final
2014-04-06 09:22:27	ga_ls8c_ard_3-0-0_090089_2014-04-05_final
2014-06-05 11:19:57	ga_ls8c_ard_3-0-0_110075_2014-06-05_final
2014-06-18 09:12:14	ga_ls8c_ard_3-0-0_089080_2014-06-17_final
2014-07-23 11:20:11	ga_ls8c_ard_3-0-0_110075_2014-07-23_final
2015-01-19 09:22:17	ga_ls8c_ard_3-0-0_090089_2015-01-18_final
2015-03-20 11:19:53	ga_ls8c_ard_3-0-0_110075_2015-03-20_final
2015-06-12 09:21:33	ga_ls8c_ard_3-0-0_090089_2015-06-11_final
2015-09-12 11:20:12	ga_ls8c_ard_3-0-0_110075_2015-09-12_final
2015-09-30 09:35:04	ga_ls8c_ard_3-0-0_092090_2015-09-30_final
2015-10-31 10:25:59	ga_ls8c_ard_3-0-0_101078_2015-10-31_final
2015-12-01 11:20:27	ga_ls8c_ard_3-0-0_110075_2015-12-01_final
2016-02-05 09:35:05	ga_ls8c_ard_3-0-0_092090_2016-02-05_final
2016-02-20 10:25:46	ga_ls8c_ard_3-0-0_101078_2016-02-20_final
2016-03-06 11:20:11	ga_ls8c_ard_3-0-0_110075_2016-03-06_final
2016-03-08 09:34:55	ga_ls8c_ard_3-0-0_092090_2016-03-08_final
2016-05-11 09:34:36	ga_ls8c_ard_3-0-0_092090_2016-05-11_final
2016-06-12 09:34:44	ga_ls8c_ard_3-0-0_092090_2016-06-12_final
2016-06-14 09:21:59	ga_ls8c_ard_3-0-0_090089_2016-06-13_final
2016-06-30 09:22:07	ga_ls8c_ard_3-0-0_090089_2016-06-29_final
2016-07-30 09:35:04	ga_ls8c_ard_3-0-0_092090_2016-07-30_final
2016-10-18 09:35:23	ga_ls8c_ard_3-0-0_092090_2016-10-18_final
2016-11-19 09:35:23	ga_ls8c_ard_3-0-0_092090_2016-11-19_final
2016-12-21 09:35:17	ga_ls8c_ard_3-0-0_092090_2016-12-21_final
2017-01-06 09:35:15	ga_ls8c_ard_3-0-0_092090_2017-01-06_final
2017-02-07 09:35:02	ga_ls8c_ard_3-0-0_092090_2017-02-07_final
2017-03-11 09:34:49	ga_ls8c_ard_3-0-0_092090_2017-03-11_final
2017-03-13 09:22:02	ga_ls8c_ard_3-0-0_090089_2017-03-12_final
2017-06-15 09:34:45	ga_ls8c_ard_3-0-0_092090_2017-06-15_final
2017-07-17 09:34:53	ga_ls8c_ard_3-0-0_092090_2017-07-17_final
2017-08-02 09:35:01	ga_ls8c_ard_3-0-0_092090_2017-08-02_final
2017-08-18 09:35:06	ga_ls8c_ard_3-0-0_092090_2017-08-18_final
2017-09-05 09:22:24	ga_ls8c_ard_3-0-0_090089_2017-09-04_final
2017-10-21 09:35:21	ga_ls8c_ard_3-0-0_092090_2017-10-21_final
2017-11-05 10:26:10	ga_ls8c_ard_3-0-0_101078_2017-11-05_final
2017-11-13 11:11:35	ga_ls8c_ard_3-0-0_109068_2017-11-13_final
2017-12-07 10:26:01	ga_ls8c_ard_3-0-0_101078_2017-12-07_final
2017-12-31 11:11:29	ga_ls8c_ard_3-0-0_109068_2017-12-31_final
2018-01-09 09:35:09	ga_ls8c_ard_3-0-0_092090_2018-01-09_final
2018-02-12 09:22:07	ga_ls8c_ard_3-0-0_090089_2018-02-11_final
2018-03-30 09:34:31	ga_ls8c_ard_3-0-0_092090_2018-03-30_final
2018-04-30 10:25:03	ga_ls8c_ard_3-0-0_101078_2018-04-30_final
2018-05-01 09:34:13	ga_ls8c_ard_3-0-0_092090_2018-05-01_final
2018-05-19 09:21:15	ga_ls8c_ard_3-0-0_090089_2018-05-18_final
2018-08-07 10:56:08	ga_ls8c_ard_3-0-0_106078_2018-08-07_final
2018-08-12 11:10:44	ga_ls8c_ard_3-0-0_109068_2018-08-12_final
2018-12-11 09:34:56	ga_ls8c_ard_3-0-0_092090_2018-12-11_final
2019-01-02 10:28:20	ga_ls8c_ard_3-0-0_102069_2019-01-02_final
2019-01-05 11:02:50	ga_ls8c_ard_3-0-0_107078_2019-01-05_final
2019-01-08 09:55:14	ga_ls8c_ard_3-0-0_096079_2019-01-08_final
2019-01-12 11:08:35	ga_ls8c_ard_3-0-0_108077_2019-01-12_final
2019-01-15 11:41:05	ga_ls8c_ard_3-0-0_113081_2019-01-15_final
2019-01-17 09:51:49	ga_ls8c_ard_3-0-0_095086_2019-01-17_final
2019-01-17 11:25:07	ga_ls8c_ard_3-0-0_111072_2019-01-17_final
2019-01-24 09:55:10	ga_ls8c_ard_3-0-0_096079_2019-01-24_final
2019-01-26 11:21:41	ga_ls8c_ard_3-0-0_110079_2019-01-26_final
2019-01-27 10:25:40	ga_ls8c_ard_3-0-0_101078_2019-01-27_final
2019-01-28 09:31:14	ga_ls8c_ard_3-0-0_092081_2019-01-28_final
2019-01-28 09:34:50	ga_ls8c_ard_3-0-0_092090_2019-01-28_final
2019-01-31 10:02:07	ga_ls8c_ard_3-0-0_097081_2019-01-31_final
2019-02-02 09:51:45	ga_ls8c_ard_3-0-0_095086_2019-02-02_final
2019-02-06 11:04:43	ga_ls8c_ard_3-0-0_107083_2019-02-06_final
2019-02-11 09:45:34	ga_ls8c_ard_3-0-0_094086_2019-02-11_final
2019-02-12 10:25:38	ga_ls8c_ard_3-0-0_101078_2019-02-12_final
2019-02-13 09:31:12	ga_ls8c_ard_3-0-0_092081_2019-02-13_final
2019-02-15 09:22:02	ga_ls8c_ard_3-0-0_090089_2019-02-14_final
2019-02-18 09:51:43	ga_ls8c_ard_3-0-0_095086_2019-02-18_final
2019-02-18 11:25:01	ga_ls8c_ard_3-0-0_111072_2019-02-18_final
2019-03-01 09:32:44	ga_ls8c_ard_3-0-0_092085_2019-03-01_final
2019-03-01 09:34:44	ga_ls8c_ard_3-0-0_092090_2019-03-01_final
2019-03-02 10:12:48	ga_ls8c_ard_3-0-0_099077_2019-03-02_final
2019-03-06 11:24:56	ga_ls8c_ard_3-0-0_111072_2019-03-06_final
2019-04-22 10:40:38	ga_ls8c_ard_3-0-0_104070_2019-04-22_final
2019-04-23 09:51:24	ga_ls8c_ard_3-0-0_095086_2019-04-23_final
2019-04-23 11:24:41	ga_ls8c_ard_3-0-0_111072_2019-04-23_final
2019-04-25 11:12:43	ga_ls8c_ard_3-0-0_109073_2019-04-25_final
2019-04-27 11:00:45	ga_ls8c_ard_3-0-0_107074_2019-04-27_final
2019-04-30 09:54:47	ga_ls8c_ard_3-0-0_096079_2019-04-30_final
2019-05-02 09:45:14	ga_ls8c_ard_3-0-0_094086_2019-05-02_final
2019-05-03 10:25:19	ga_ls8c_ard_3-0-0_101078_2019-05-03_final
2019-05-04 09:30:54	ga_ls8c_ard_3-0-0_092081_2019-05-04_final
2019-05-04 09:32:30	ga_ls8c_ard_3-0-0_092085_2019-05-04_final
2019-05-05 11:52:15	ga_ls8c_ard_3-0-0_115079_2019-05-05_final
2019-05-09 09:43:55	ga_ls8c_ard_3-0-0_095067_2019-05-09_final
2019-05-18 11:19:54	ga_ls8c_ard_3-0-0_110075_2019-05-18_final
2019-05-18 11:21:30	ga_ls8c_ard_3-0-0_110079_2019-05-18_final
2019-05-20 09:32:40	ga_ls8c_ard_3-0-0_092085_2019-05-20_final
2019-05-21 10:15:57	ga_ls8c_ard_3-0-0_099085_2019-05-21_final
2019-05-21 11:52:26	ga_ls8c_ard_3-0-0_115079_2019-05-21_final
2019-05-25 09:51:39	ga_ls8c_ard_3-0-0_095086_2019-05-25_final
2019-05-26 10:28:09	ga_ls8c_ard_3-0-0_102069_2019-05-26_final
2019-05-27 11:15:48	ga_ls8c_ard_3-0-0_109080_2019-05-27_final
2019-06-01 11:32:47	ga_ls8c_ard_3-0-0_112076_2019-06-01_final
2019-06-03 09:45:33	ga_ls8c_ard_3-0-0_094086_2019-06-03_final
2019-06-05 09:31:13	ga_ls8c_ard_3-0-0_092081_2019-06-05_final
2019-06-05 09:32:49	ga_ls8c_ard_3-0-0_092085_2019-06-05_final
2019-06-08 10:02:08	ga_ls8c_ard_3-0-0_097081_2019-06-08_final
2019-06-08 11:41:25	ga_ls8c_ard_3-0-0_113082_2019-06-08_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