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
2015-04-30 09:35:41	ga_ls8c_ard_3-0-0_093078_2015-04-30_final
2015-04-30 11:14:34	ga_ls8c_ard_3-0-0_109078_2015-04-30_final
2015-05-01 10:18:32	ga_ls8c_ard_3-0-0_100077_2015-05-01_final
2015-05-01 10:18:56	ga_ls8c_ard_3-0-0_100078_2015-05-01_final
2015-05-14 09:47:48	ga_ls8c_ard_3-0-0_095078_2015-05-14_final
2015-05-14 11:26:41	ga_ls8c_ard_3-0-0_111078_2015-05-14_final
2015-05-15 10:30:40	ga_ls8c_ard_3-0-0_102077_2015-05-15_final
2015-05-15 10:31:04	ga_ls8c_ard_3-0-0_102078_2015-05-15_final
2015-05-16 09:35:03	ga_ls8c_ard_3-0-0_093077_2015-05-16_final
2015-05-16 09:35:27	ga_ls8c_ard_3-0-0_093078_2015-05-16_final
2015-05-16 11:13:56	ga_ls8c_ard_3-0-0_109077_2015-05-16_final
2015-05-16 11:14:20	ga_ls8c_ard_3-0-0_109078_2015-05-16_final
2015-05-17 10:18:19	ga_ls8c_ard_3-0-0_100077_2015-05-17_final
2015-05-17 10:18:43	ga_ls8c_ard_3-0-0_100078_2015-05-17_final
2015-05-17 11:57:12	ga_ls8c_ard_3-0-0_116077_2015-05-17_final
2015-05-17 11:57:36	ga_ls8c_ard_3-0-0_116078_2015-05-17_final
2015-07-26 09:41:49	ga_ls8c_ard_3-0-0_094077_2015-07-26_final
2015-07-26 09:42:13	ga_ls8c_ard_3-0-0_094078_2015-07-26_final
2015-07-26 11:20:42	ga_ls8c_ard_3-0-0_110077_2015-07-26_final
2015-07-26 11:21:06	ga_ls8c_ard_3-0-0_110078_2015-07-26_final
2015-07-27 10:25:05	ga_ls8c_ard_3-0-0_101077_2015-07-27_final
2015-07-27 10:25:29	ga_ls8c_ard_3-0-0_101078_2015-07-27_final
2015-08-04 09:35:40	ga_ls8c_ard_3-0-0_093077_2015-08-04_final
2015-08-04 11:14:33	ga_ls8c_ard_3-0-0_109077_2015-08-04_final
2015-08-04 11:14:57	ga_ls8c_ard_3-0-0_109078_2015-08-04_final
2015-08-05 10:18:55	ga_ls8c_ard_3-0-0_100077_2015-08-05_final
2015-08-05 10:19:19	ga_ls8c_ard_3-0-0_100078_2015-08-05_final
2015-08-05 11:57:48	ga_ls8c_ard_3-0-0_116077_2015-08-05_final
2015-08-05 11:58:12	ga_ls8c_ard_3-0-0_116078_2015-08-05_final
2018-09-16 10:06:34	ga_ls8c_ard_3-0-0_098077_2018-09-16_final
2018-09-16 10:06:58	ga_ls8c_ard_3-0-0_098078_2018-09-16_final
2018-09-16 11:45:27	ga_ls8c_ard_3-0-0_114077_2018-09-16_final
2018-09-16 11:45:51	ga_ls8c_ard_3-0-0_114078_2018-09-16_final
2018-09-17 09:10:57	ga_ls8c_ard_3-0-0_089077_2018-09-16_final
2018-09-17 09:11:21	ga_ls8c_ard_3-0-0_089078_2018-09-16_final
2018-09-17 10:49:50	ga_ls8c_ard_3-0-0_105077_2018-09-17_final
2018-09-17 10:50:14	ga_ls8c_ard_3-0-0_105078_2018-09-17_final
2018-10-04 09:54:20	ga_ls8c_ard_3-0-0_096077_2018-10-04_final
2018-10-04 09:54:44	ga_ls8c_ard_3-0-0_096078_2018-10-04_final
2018-10-04 11:33:13	ga_ls8c_ard_3-0-0_112077_2018-10-04_final
2018-10-04 11:33:37	ga_ls8c_ard_3-0-0_112078_2018-10-04_final
2018-10-05 10:37:37	ga_ls8c_ard_3-0-0_103077_2018-10-05_final
2018-10-05 10:38:00	ga_ls8c_ard_3-0-0_103078_2018-10-05_final
2018-10-06 09:42:00	ga_ls8c_ard_3-0-0_094077_2018-10-06_final
2018-10-06 09:42:24	ga_ls8c_ard_3-0-0_094078_2018-10-06_final
2018-10-06 11:20:53	ga_ls8c_ard_3-0-0_110077_2018-10-06_final
2018-10-06 11:21:17	ga_ls8c_ard_3-0-0_110078_2018-10-06_final
2018-10-07 10:25:16	ga_ls8c_ard_3-0-0_101077_2018-10-07_final
2018-10-07 10:25:40	ga_ls8c_ard_3-0-0_101078_2018-10-07_final
2018-12-23 09:54:27	ga_ls8c_ard_3-0-0_096077_2018-12-23_final
2018-12-23 09:54:51	ga_ls8c_ard_3-0-0_096078_2018-12-23_final
2018-12-23 11:33:20	ga_ls8c_ard_3-0-0_112077_2018-12-23_final
2018-12-23 11:33:44	ga_ls8c_ard_3-0-0_112078_2018-12-23_final
2018-12-24 10:37:43	ga_ls8c_ard_3-0-0_103077_2018-12-24_final
2018-12-24 10:38:07	ga_ls8c_ard_3-0-0_103078_2018-12-24_final
2018-12-25 09:42:06	ga_ls8c_ard_3-0-0_094077_2018-12-25_final
2018-12-25 09:42:30	ga_ls8c_ard_3-0-0_094078_2018-12-25_final
2018-12-25 11:20:59	ga_ls8c_ard_3-0-0_110077_2018-12-25_final
2018-12-25 11:21:23	ga_ls8c_ard_3-0-0_110078_2018-12-25_final
2018-12-26 10:25:21	ga_ls8c_ard_3-0-0_101077_2018-12-26_final
2018-12-26 10:25:45	ga_ls8c_ard_3-0-0_101078_2018-12-26_final
2019-01-06 10:06:48	ga_ls8c_ard_3-0-0_098077_2019-01-06_final
2019-01-06 10:07:12	ga_ls8c_ard_3-0-0_098078_2019-01-06_final
2019-01-06 11:45:41	ga_ls8c_ard_3-0-0_114077_2019-01-06_final
2019-01-06 11:46:05	ga_ls8c_ard_3-0-0_114078_2019-01-06_final
2019-01-07 09:11:11	ga_ls8c_ard_3-0-0_089077_2019-01-06_final
2019-01-07 09:11:35	ga_ls8c_ard_3-0-0_089078_2019-01-06_final
2019-01-07 10:50:28	ga_ls8c_ard_3-0-0_105078_2019-01-07_final
2023-03-02 10:32:07	ga_ls8c_ard_3-2-1_102078_2023-03-02_final
2023-03-04 10:19:20	ga_ls8c_ard_3-2-1_100077_2023-03-04_final
2023-03-04 10:19:44	ga_ls8c_ard_3-2-1_100078_2023-03-04_final
2023-03-04 11:58:37	ga_ls8c_ard_3-2-1_116078_2023-03-04_final
2023-03-05 09:23:42	ga_ls8c_ard_3-2-1_091077_2023-03-04_final
2023-03-05 09:24:06	ga_ls8c_ard_3-2-1_091078_2023-03-04_final
2023-03-05 11:02:59	ga_ls8c_ard_3-2-1_107078_2023-03-05_final
2023-08-14 10:50:06	ga_ls8c_ard_3-2-1_105077_2023-08-14_final
2023-08-14 10:50:30	ga_ls8c_ard_3-2-1_105078_2023-08-14_final
2023-08-15 09:54:30	ga_ls8c_ard_3-2-1_096077_2023-08-15_final
2023-08-15 09:54:53	ga_ls8c_ard_3-2-1_096078_2023-08-15_final
2023-08-15 11:33:23	ga_ls8c_ard_3-2-1_112077_2023-08-15_final
2023-08-15 11:33:47	ga_ls8c_ard_3-2-1_112078_2023-08-15_final
2023-08-16 10:37:46	ga_ls8c_ard_3-2-1_103077_2023-08-16_final
2023-08-16 10:38:10	ga_ls8c_ard_3-2-1_103078_2023-08-16_final
2023-08-17 09:42:09	ga_ls8c_ard_3-2-1_094077_2023-08-17_final
2023-08-17 09:42:33	ga_ls8c_ard_3-2-1_094078_2023-08-17_final
2023-08-17 11:21:03	ga_ls8c_ard_3-2-1_110077_2023-08-17_final
2023-08-17 11:21:26	ga_ls8c_ard_3-2-1_110078_2023-08-17_final
2023-08-25 10:31:39	ga_ls8c_ard_3-2-1_102077_2023-08-25_final
2023-08-25 10:32:03	ga_ls8c_ard_3-2-1_102078_2023-08-25_final
2023-08-26 09:36:02	ga_ls8c_ard_3-2-1_093077_2023-08-26_final
2023-08-26 09:36:26	ga_ls8c_ard_3-2-1_093078_2023-08-26_final
2023-08-26 11:14:55	ga_ls8c_ard_3-2-1_109077_2023-08-26_final
2023-08-26 11:15:19	ga_ls8c_ard_3-2-1_109078_2023-08-26_final
2023-08-28 11:02:34	ga_ls8c_ard_3-2-1_107077_2023-08-28_final
2023-08-28 11:02:58	ga_ls8c_ard_3-2-1_107078_2023-08-28_final
2023-08-31 09:54:35	ga_ls8c_ard_3-2-1_096077_2023-08-31_final
2023-08-31 09:54:59	ga_ls8c_ard_3-2-1_096078_2023-08-31_final
2023-08-31 11:33:28	ga_ls8c_ard_3-2-1_112077_2023-08-31_final
2023-08-31 11:33:52	ga_ls8c_ard_3-2-1_112078_2023-08-31_final
2023-09-01 10:37:50	ga_ls8c_ard_3-2-1_103077_2023-09-01_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