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
2015-04-16 09:28:15	ga_ls8c_ard_3-0-0_091090_2015-04-15_final
2015-04-16 09:28:39	ga_ls8c_ard_3-0-0_091091_2015-04-15_final
2015-04-23 09:34:24	ga_ls8c_ard_3-0-0_092090_2015-04-23_final
2015-05-18 09:27:54	ga_ls8c_ard_3-0-0_091090_2015-05-17_final
2015-05-20 09:15:33	ga_ls8c_ard_3-0-0_089090_2015-05-19_final
2015-05-25 09:34:07	ga_ls8c_ard_3-0-0_092090_2015-05-25_final
2015-06-03 09:28:01	ga_ls8c_ard_3-0-0_091090_2015-06-02_final
2015-06-03 09:28:25	ga_ls8c_ard_3-0-0_091091_2015-06-02_final
2015-06-10 09:34:17	ga_ls8c_ard_3-0-0_092090_2015-06-10_final
2015-06-12 09:21:57	ga_ls8c_ard_3-0-0_090090_2015-06-11_final
2015-06-12 09:22:21	ga_ls8c_ard_3-0-0_090091_2015-06-11_final
2015-06-19 09:28:10	ga_ls8c_ard_3-0-0_091090_2015-06-18_final
2015-06-19 09:28:34	ga_ls8c_ard_3-0-0_091091_2015-06-18_final
2015-06-21 09:15:49	ga_ls8c_ard_3-0-0_089090_2015-06-20_final
2015-06-26 09:34:22	ga_ls8c_ard_3-0-0_092090_2015-06-26_final
2015-06-28 09:22:03	ga_ls8c_ard_3-0-0_090090_2015-06-27_final
2015-06-28 09:22:27	ga_ls8c_ard_3-0-0_090091_2015-06-27_final
2015-07-14 09:22:14	ga_ls8c_ard_3-0-0_090090_2015-07-13_final
2015-07-14 09:22:37	ga_ls8c_ard_3-0-0_090091_2015-07-13_final
2015-07-21 09:28:27	ga_ls8c_ard_3-0-0_091090_2015-07-20_final
2015-07-21 09:28:51	ga_ls8c_ard_3-0-0_091091_2015-07-20_final
2015-07-28 09:34:39	ga_ls8c_ard_3-0-0_092090_2015-07-28_final
2015-07-30 09:22:18	ga_ls8c_ard_3-0-0_090090_2015-07-29_final
2015-07-30 09:22:42	ga_ls8c_ard_3-0-0_090091_2015-07-29_final
2015-08-06 09:28:29	ga_ls8c_ard_3-0-0_091090_2015-08-05_final
2015-08-06 09:28:53	ga_ls8c_ard_3-0-0_091091_2015-08-05_final
2015-08-08 09:16:09	ga_ls8c_ard_3-0-0_089090_2015-08-07_final
2015-08-15 09:22:24	ga_ls8c_ard_3-0-0_090090_2015-08-14_final
2015-08-15 09:22:48	ga_ls8c_ard_3-0-0_090091_2015-08-14_final
2016-12-23 09:22:55	ga_ls8c_ard_3-0-0_090090_2016-12-22_final
2016-12-23 09:23:19	ga_ls8c_ard_3-0-0_090091_2016-12-22_final
2016-12-30 09:29:06	ga_ls8c_ard_3-0-0_091090_2016-12-29_final
2016-12-30 09:29:30	ga_ls8c_ard_3-0-0_091091_2016-12-29_final
2017-01-31 09:28:55	ga_ls8c_ard_3-0-0_091090_2017-01-30_final
2017-01-31 09:29:19	ga_ls8c_ard_3-0-0_091091_2017-01-30_final
2017-02-09 09:22:39	ga_ls8c_ard_3-0-0_090090_2017-02-08_final
2017-02-09 09:23:03	ga_ls8c_ard_3-0-0_090091_2017-02-08_final
2017-02-23 09:34:57	ga_ls8c_ard_3-0-0_092090_2017-02-23_final
2017-02-25 09:22:34	ga_ls8c_ard_3-0-0_090090_2017-02-24_final
2017-02-25 09:22:58	ga_ls8c_ard_3-0-0_090091_2017-02-24_final
2017-03-13 09:22:50	ga_ls8c_ard_3-0-0_090091_2017-03-12_final
2017-03-22 09:16:09	ga_ls8c_ard_3-0-0_089090_2017-03-21_final
2017-06-26 09:16:16	ga_ls8c_ard_3-0-0_089090_2017-06-25_final
2018-02-12 09:22:31	ga_ls8c_ard_3-0-0_090090_2018-02-11_final
2018-02-12 09:22:55	ga_ls8c_ard_3-0-0_090091_2018-02-11_final
2018-02-19 09:29:03	ga_ls8c_ard_3-0-0_091091_2018-02-18_final
2018-02-21 09:16:16	ga_ls8c_ard_3-0-0_089090_2018-02-20_final
2018-02-26 09:34:47	ga_ls8c_ard_3-0-0_092090_2018-02-26_final
2018-02-28 09:22:24	ga_ls8c_ard_3-0-0_090090_2018-02-27_final
2018-02-28 09:22:48	ga_ls8c_ard_3-0-0_090091_2018-02-27_final
2018-03-07 09:28:55	ga_ls8c_ard_3-0-0_091091_2018-03-06_final
2018-03-09 09:16:08	ga_ls8c_ard_3-0-0_089090_2018-03-08_final
2018-03-16 09:22:39	ga_ls8c_ard_3-0-0_090091_2018-03-15_final
2018-03-25 09:16:00	ga_ls8c_ard_3-0-0_089090_2018-03-24_final
2018-04-01 09:22:08	ga_ls8c_ard_3-0-0_090090_2018-03-31_final
2018-04-01 09:22:32	ga_ls8c_ard_3-0-0_090091_2018-03-31_final
2018-04-08 09:28:39	ga_ls8c_ard_3-0-0_091091_2018-04-07_final
2018-04-17 09:22:23	ga_ls8c_ard_3-0-0_090091_2018-04-16_final
2018-05-03 09:22:14	ga_ls8c_ard_3-0-0_090091_2018-05-02_final
2018-05-10 09:27:56	ga_ls8c_ard_3-0-0_091090_2018-05-09_final
2018-05-10 09:28:20	ga_ls8c_ard_3-0-0_091091_2018-05-09_final
2018-05-12 09:15:33	ga_ls8c_ard_3-0-0_089090_2018-05-11_final
2018-05-19 09:22:03	ga_ls8c_ard_3-0-0_090091_2018-05-18_final
2019-01-23 09:16:19	ga_ls8c_ard_3-0-0_089090_2019-01-22_final
2019-01-28 09:34:50	ga_ls8c_ard_3-0-0_092090_2019-01-28_final
2019-02-06 09:28:38	ga_ls8c_ard_3-0-0_091090_2019-02-05_final
2019-02-06 09:29:02	ga_ls8c_ard_3-0-0_091091_2019-02-05_final
2019-02-08 09:16:16	ga_ls8c_ard_3-0-0_089090_2019-02-07_final
2019-02-13 09:34:48	ga_ls8c_ard_3-0-0_092090_2019-02-13_final
2019-02-15 09:22:26	ga_ls8c_ard_3-0-0_090090_2019-02-14_final
2019-02-15 09:22:50	ga_ls8c_ard_3-0-0_090091_2019-02-14_final
2019-02-22 09:28:35	ga_ls8c_ard_3-0-0_091090_2019-02-21_final
2019-02-22 09:28:59	ga_ls8c_ard_3-0-0_091091_2019-02-21_final
2019-02-24 09:16:13	ga_ls8c_ard_3-0-0_089090_2019-02-23_final
2019-03-01 09:34:44	ga_ls8c_ard_3-0-0_092090_2019-03-01_final
2019-03-03 09:22:22	ga_ls8c_ard_3-0-0_090090_2019-03-02_final
2019-03-03 09:22:45	ga_ls8c_ard_3-0-0_090091_2019-03-02_final
2019-03-10 09:28:30	ga_ls8c_ard_3-1-0_091090_2019-03-09_final
2019-03-10 09:28:54	ga_ls8c_ard_3-1-0_091091_2019-03-09_final
2019-03-17 09:34:38	ga_ls8c_ard_3-1-0_092090_2019-03-17_final
2019-03-19 09:22:40	ga_ls8c_ard_3-1-0_090091_2019-03-18_final
2019-03-26 09:28:26	ga_ls8c_ard_3-1-0_091090_2019-03-25_final
2019-03-26 09:28:50	ga_ls8c_ard_3-1-0_091091_2019-03-25_final
2019-03-28 09:16:04	ga_ls8c_ard_3-1-0_089090_2019-03-27_final
2019-04-04 09:22:13	ga_ls8c_ard_3-1-0_090090_2019-04-03_final
2019-04-04 09:22:37	ga_ls8c_ard_3-1-0_090091_2019-04-03_final
2019-04-11 09:28:45	ga_ls8c_ard_3-1-0_091091_2019-04-10_final
2019-04-20 09:22:31	ga_ls8c_ard_3-0-0_090091_2019-04-19_final
2019-04-29 09:15:55	ga_ls8c_ard_3-0-0_089090_2019-04-28_final
2019-05-06 09:22:09	ga_ls8c_ard_3-0-0_090090_2019-05-05_final
2019-05-06 09:22:33	ga_ls8c_ard_3-0-0_090091_2019-05-05_final
2019-05-13 09:28:25	ga_ls8c_ard_3-0-0_091090_2019-05-12_final
2019-05-13 09:28:49	ga_ls8c_ard_3-0-0_091091_2019-05-12_final
2019-05-15 09:16:05	ga_ls8c_ard_3-0-0_089090_2019-05-14_final
2019-05-22 09:22:20	ga_ls8c_ard_3-0-0_090090_2019-05-21_final
2019-05-22 09:22:44	ga_ls8c_ard_3-0-0_090091_2019-05-21_final
2019-05-31 09:16:14	ga_ls8c_ard_3-0-0_089090_2019-05-30_final
2019-06-05 09:34:48	ga_ls8c_ard_3-0-0_092090_2019-06-05_final
2019-06-07 09:22:28	ga_ls8c_ard_3-0-0_090090_2019-06-06_final
2019-06-07 09:22:52	ga_ls8c_ard_3-0-0_090091_2019-06-06_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