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
2017-09-04 10:13:14	ga_ls8c_ard_3-0-0_099077_2017-09-04_final
2017-09-04 10:13:38	ga_ls8c_ard_3-0-0_099078_2017-09-04_final
2017-09-04 11:52:07	ga_ls8c_ard_3-0-0_115077_2017-09-04_final
2017-09-04 11:52:31	ga_ls8c_ard_3-0-0_115078_2017-09-04_final
2017-09-05 09:18:00	ga_ls8c_ard_3-0-0_090078_2017-09-04_final
2017-09-05 10:56:53	ga_ls8c_ard_3-0-0_106078_2017-09-05_final
2017-09-06 10:00:52	ga_ls8c_ard_3-0-0_097077_2017-09-06_final
2017-09-06 10:01:16	ga_ls8c_ard_3-0-0_097078_2017-09-06_final
2017-09-06 11:40:09	ga_ls8c_ard_3-0-0_113078_2017-09-06_final
2017-09-07 10:44:32	ga_ls8c_ard_3-0-0_104078_2017-09-07_final
2017-09-08 09:48:31	ga_ls8c_ard_3-0-0_095077_2017-09-08_final
2017-09-08 09:48:55	ga_ls8c_ard_3-0-0_095078_2017-09-08_final
2017-09-08 11:27:48	ga_ls8c_ard_3-0-0_111078_2017-09-08_final
2017-10-25 10:44:43	ga_ls8c_ard_3-0-0_104078_2017-10-25_final
2017-10-26 09:49:06	ga_ls8c_ard_3-0-0_095078_2017-10-26_final
2017-10-26 11:27:59	ga_ls8c_ard_3-0-0_111078_2017-10-26_final
2017-10-27 10:31:58	ga_ls8c_ard_3-0-0_102077_2017-10-27_final
2017-10-27 10:32:22	ga_ls8c_ard_3-0-0_102078_2017-10-27_final
2017-11-10 10:44:41	ga_ls8c_ard_3-0-0_104078_2017-11-10_final
2017-11-11 09:48:40	ga_ls8c_ard_3-0-0_095077_2017-11-11_final
2017-11-11 09:49:04	ga_ls8c_ard_3-0-0_095078_2017-11-11_final
2017-11-11 11:27:57	ga_ls8c_ard_3-0-0_111078_2017-11-11_final
2017-11-12 10:32:19	ga_ls8c_ard_3-0-0_102078_2017-11-12_final
2017-11-26 10:44:36	ga_ls8c_ard_3-0-0_104078_2017-11-26_final
2017-11-27 09:48:58	ga_ls8c_ard_3-0-0_095078_2017-11-27_final
2017-11-27 11:27:51	ga_ls8c_ard_3-0-0_111078_2017-11-27_final
2017-11-28 10:31:49	ga_ls8c_ard_3-0-0_102077_2017-11-28_final
2017-11-28 10:32:13	ga_ls8c_ard_3-0-0_102078_2017-11-28_final
2017-12-12 10:44:34	ga_ls8c_ard_3-0-0_104078_2017-12-12_final
2017-12-13 09:48:34	ga_ls8c_ard_3-0-0_095077_2017-12-13_final
2017-12-13 09:48:57	ga_ls8c_ard_3-0-0_095078_2017-12-13_final
2017-12-13 11:27:27	ga_ls8c_ard_3-0-0_111077_2017-12-13_final
2017-12-13 11:27:51	ga_ls8c_ard_3-0-0_111078_2017-12-13_final
2017-12-14 10:32:14	ga_ls8c_ard_3-0-0_102078_2017-12-14_final
2018-01-29 10:43:56	ga_ls8c_ard_3-1-0_104077_2018-01-29_final
2018-01-29 10:44:20	ga_ls8c_ard_3-0-0_104078_2018-01-29_final
2018-01-30 09:48:42	ga_ls8c_ard_3-0-0_095078_2018-01-30_final
2018-01-30 11:27:35	ga_ls8c_ard_3-0-0_111078_2018-01-30_final
2018-01-31 10:31:57	ga_ls8c_ard_3-0-0_102078_2018-01-31_final
2022-01-22 10:56:58	ga_ls8c_ard_3-2-1_106078_2022-01-22_final
2022-01-23 10:00:56	ga_ls8c_ard_3-2-1_097077_2022-01-23_final
2022-01-23 10:01:20	ga_ls8c_ard_3-2-1_097078_2022-01-23_final
2022-01-23 11:40:13	ga_ls8c_ard_3-2-1_113078_2022-01-23_final
2022-01-24 10:44:35	ga_ls8c_ard_3-2-1_104078_2022-01-24_final
2022-01-25 09:48:57	ga_ls8c_ard_3-2-1_095078_2022-01-25_final
2022-01-25 11:27:50	ga_ls8c_ard_3-2-1_111078_2022-01-25_final
2022-03-21 11:33:44	ga_ls8c_ard_3-2-1_112078_2022-03-21_final
2022-03-22 10:38:05	ga_ls8c_ard_3-2-1_103078_2022-03-22_final
2022-03-23 09:42:27	ga_ls8c_ard_3-2-1_094078_2022-03-23_final
2022-03-23 11:21:20	ga_ls8c_ard_3-2-1_110078_2022-03-23_final
2022-03-24 10:25:42	ga_ls8c_ard_3-2-1_101078_2022-03-24_final
2022-03-25 09:30:04	ga_ls8c_ard_3-2-1_092078_2022-03-25_final
2022-03-25 11:08:57	ga_ls8c_ard_3-2-1_108078_2022-03-25_final
2022-03-26 10:13:19	ga_ls8c_ard_3-2-1_099078_2022-03-26_final
2022-03-26 11:52:12	ga_ls8c_ard_3-2-1_115078_2022-03-26_final
2022-03-27 09:17:41	ga_ls8c_ard_3-2-1_090078_2022-03-26_final
2022-03-27 10:56:34	ga_ls8c_ard_3-2-1_106078_2022-03-27_final
2022-03-28 10:00:55	ga_ls8c_ard_3-2-1_097078_2022-03-28_final
2022-03-28 11:39:48	ga_ls8c_ard_3-2-1_113078_2022-03-28_final
2022-03-31 10:31:48	ga_ls8c_ard_3-2-1_102078_2022-03-31_final
2022-04-01 09:36:10	ga_ls8c_ard_3-2-1_093078_2022-04-01_final
2022-04-01 11:15:03	ga_ls8c_ard_3-2-1_109078_2022-04-01_final
2022-04-02 10:19:26	ga_ls8c_ard_3-2-1_100078_2022-04-02_final
2022-04-02 11:58:19	ga_ls8c_ard_3-2-1_116078_2022-04-02_final
2022-04-03 09:23:49	ga_ls8c_ard_3-2-1_091078_2022-04-02_final
2022-04-03 11:02:42	ga_ls8c_ard_3-2-1_107078_2022-04-03_final
2022-04-04 10:07:05	ga_ls8c_ard_3-2-1_098078_2022-04-04_final
2022-04-04 11:45:58	ga_ls8c_ard_3-2-1_114078_2022-04-04_final
2022-04-05 09:11:29	ga_ls8c_ard_3-2-1_089078_2022-04-04_final
2022-04-05 10:50:22	ga_ls8c_ard_3-2-1_105078_2022-04-05_final
2022-04-06 09:54:45	ga_ls8c_ard_3-2-1_096078_2022-04-06_final
2022-04-06 11:33:38	ga_ls8c_ard_3-2-1_112078_2022-04-06_final
2022-06-10 10:37:57	ga_ls8c_ard_3-2-1_103077_2022-06-10_final
2022-06-18 11:27:29	ga_ls8c_ard_3-2-1_111077_2022-06-18_final
2022-06-18 11:27:53	ga_ls8c_ard_3-2-1_111078_2022-06-18_final
2022-06-19 10:32:16	ga_ls8c_ard_3-2-1_102078_2022-06-19_final
2022-06-20 09:36:39	ga_ls8c_ard_3-2-1_093078_2022-06-20_final
2023-02-12 10:44:43	ga_ls8c_ard_3-2-1_104078_2023-02-12_final
2023-02-13 09:49:05	ga_ls8c_ard_3-2-1_095078_2023-02-13_final
2023-02-13 11:27:58	ga_ls8c_ard_3-2-1_111078_2023-02-13_final
2023-02-14 10:31:56	ga_ls8c_ard_3-2-1_102077_2023-02-14_final
2023-02-14 10:32:20	ga_ls8c_ard_3-2-1_102078_2023-02-14_final
2023-02-15 09:36:42	ga_ls8c_ard_3-2-1_093078_2023-02-15_final
2023-02-15 11:15:35	ga_ls8c_ard_3-2-1_109078_2023-02-15_final
2023-02-16 10:19:57	ga_ls8c_ard_3-2-1_100078_2023-02-16_final
2023-02-16 11:58:50	ga_ls8c_ard_3-2-1_116078_2023-02-16_final
2023-02-17 09:24:19	ga_ls8c_ard_3-2-1_091078_2023-02-16_final
2023-02-17 11:03:12	ga_ls8c_ard_3-2-1_107078_2023-02-17_final
2023-02-18 10:07:33	ga_ls8c_ard_3-2-1_098078_2023-02-18_final
2023-02-18 11:46:26	ga_ls8c_ard_3-2-1_114078_2023-02-18_final
2023-02-19 09:11:31	ga_ls8c_ard_3-2-1_089077_2023-02-18_final
2023-02-19 09:11:55	ga_ls8c_ard_3-2-1_089078_2023-02-18_final
2023-02-19 10:50:48	ga_ls8c_ard_3-2-1_105078_2023-02-19_final
2023-02-24 11:09:13	ga_ls8c_ard_3-2-1_108078_2023-02-24_final
2023-02-25 10:13:34	ga_ls8c_ard_3-2-1_099078_2023-02-25_final
2023-02-25 11:52:27	ga_ls8c_ard_3-2-1_115078_2023-02-25_final
2023-02-26 09:17:57	ga_ls8c_ard_3-2-1_090078_2023-02-25_final
2023-02-26 10:56:50	ga_ls8c_ard_3-2-1_106078_2023-02-26_final
2023-02-27 10:01:13	ga_ls8c_ard_3-2-1_097078_2023-02-27_final
2023-02-27 11:40:06	ga_ls8c_ard_3-2-1_113078_2023-02-27_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