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
2014-01-22 10:19:38	ga_ls8c_ard_3-0-0_100075_2014-01-22_final
2014-01-23 11:02:54	ga_ls8c_ard_3-0-0_107075_2014-01-23_final
2014-01-24 10:07:16	ga_ls8c_ard_3-0-0_098075_2014-01-24_final
2014-01-24 11:46:09	ga_ls8c_ard_3-0-0_114075_2014-01-24_final
2014-01-25 10:50:32	ga_ls8c_ard_3-0-0_105075_2014-01-25_final
2014-01-26 09:54:54	ga_ls8c_ard_3-0-0_096075_2014-01-26_final
2014-01-26 11:33:47	ga_ls8c_ard_3-0-0_112075_2014-01-26_final
2014-02-14 10:25:32	ga_ls8c_ard_3-0-0_101075_2014-02-14_final
2014-02-15 09:29:54	ga_ls8c_ard_3-0-0_092075_2014-02-14_final
2014-02-16 11:52:03	ga_ls8c_ard_3-0-0_115075_2014-02-16_final
2014-02-17 09:17:32	ga_ls8c_ard_3-0-0_090075_2014-02-16_final
2014-02-17 10:56:25	ga_ls8c_ard_3-0-0_106075_2014-02-17_final
2014-02-18 10:00:47	ga_ls8c_ard_3-0-0_097075_2014-02-18_final
2014-02-18 11:39:40	ga_ls8c_ard_3-0-0_113075_2014-02-18_final
2014-02-19 10:44:02	ga_ls8c_ard_3-0-0_104075_2014-02-19_final
2014-02-20 11:27:17	ga_ls8c_ard_3-0-0_111075_2014-02-20_final
2014-05-30 10:17:41	ga_ls8c_ard_3-0-0_100074_2014-05-30_final
2014-05-30 10:18:05	ga_ls8c_ard_3-0-0_100075_2014-05-30_final
2014-05-31 09:22:04	ga_ls8c_ard_3-0-0_091074_2014-05-30_final
2014-05-31 09:22:28	ga_ls8c_ard_3-0-0_091075_2014-05-30_final
2014-05-31 11:00:57	ga_ls8c_ard_3-0-0_107074_2014-05-31_final
2014-05-31 11:01:21	ga_ls8c_ard_3-0-0_107075_2014-05-31_final
2014-06-05 09:41:04	ga_ls8c_ard_3-0-0_094075_2014-06-05_final
2014-06-05 11:19:57	ga_ls8c_ard_3-0-0_110075_2014-06-05_final
2014-06-06 10:24:20	ga_ls8c_ard_3-0-0_101075_2014-06-06_final
2014-06-07 09:28:19	ga_ls8c_ard_3-0-0_092074_2014-06-06_final
2014-06-07 09:28:43	ga_ls8c_ard_3-0-0_092075_2014-06-06_final
2014-06-07 11:07:36	ga_ls8c_ard_3-0-0_108075_2014-06-07_final
2014-06-08 10:11:59	ga_ls8c_ard_3-0-0_099075_2014-06-08_final
2014-06-08 11:50:52	ga_ls8c_ard_3-0-0_115075_2014-06-08_final
2014-06-09 10:55:16	ga_ls8c_ard_3-0-0_106075_2014-06-09_final
2022-09-11 10:06:45	ga_ls8c_ard_3-2-1_098075_2022-09-11_final
2022-09-11 11:45:38	ga_ls8c_ard_3-2-1_114075_2022-09-11_final
2022-09-12 09:10:44	ga_ls8c_ard_3-2-1_089074_2022-09-11_final
2022-09-12 09:11:08	ga_ls8c_ard_3-2-1_089075_2022-09-11_final
2022-09-12 10:50:01	ga_ls8c_ard_3-2-1_105075_2022-09-12_final
2022-09-13 09:54:24	ga_ls8c_ard_3-2-1_096075_2022-09-13_final
2022-09-13 11:32:53	ga_ls8c_ard_3-2-1_112074_2022-09-13_final
2022-09-13 11:33:17	ga_ls8c_ard_3-2-1_112075_2022-09-13_final
2022-09-14 10:37:40	ga_ls8c_ard_3-2-1_103075_2022-09-14_final
2022-09-15 09:42:03	ga_ls8c_ard_3-2-1_094075_2022-09-15_final
2022-09-17 11:08:11	ga_ls8c_ard_3-2-1_108074_2022-09-17_final
2022-09-17 11:08:35	ga_ls8c_ard_3-2-1_108075_2022-09-17_final
2022-09-18 10:12:58	ga_ls8c_ard_3-2-1_099075_2022-09-18_final
2022-09-18 11:51:27	ga_ls8c_ard_3-2-1_115074_2022-09-18_final
2022-09-18 11:51:51	ga_ls8c_ard_3-2-1_115075_2022-09-18_final
2022-09-19 09:17:21	ga_ls8c_ard_3-2-1_090075_2022-09-18_final
2022-09-27 10:06:47	ga_ls8c_ard_3-2-1_098075_2022-09-27_final
2022-09-27 11:45:40	ga_ls8c_ard_3-2-1_114075_2022-09-27_final
2022-09-28 09:11:10	ga_ls8c_ard_3-2-1_089075_2022-09-27_final
2022-09-28 10:50:03	ga_ls8c_ard_3-2-1_105075_2022-09-28_final
2022-09-29 09:54:01	ga_ls8c_ard_3-2-1_096074_2022-09-29_final
2022-09-29 09:54:25	ga_ls8c_ard_3-2-1_096075_2022-09-29_final
2022-09-29 11:33:18	ga_ls8c_ard_3-2-1_112075_2022-09-29_final
2022-10-02 10:24:55	ga_ls8c_ard_3-2-1_101074_2022-10-02_final
2022-10-02 10:25:19	ga_ls8c_ard_3-2-1_101075_2022-10-02_final
2022-10-03 09:29:17	ga_ls8c_ard_3-2-1_092074_2022-10-02_final
2022-10-03 09:29:41	ga_ls8c_ard_3-2-1_092075_2022-10-02_final
2022-10-03 11:08:34	ga_ls8c_ard_3-2-1_108075_2022-10-03_final
2022-10-20 11:51:23	ga_ls8c_ard_3-2-1_115074_2022-10-20_final
2022-10-20 11:51:47	ga_ls8c_ard_3-2-1_115075_2022-10-20_final
2022-10-21 09:17:17	ga_ls8c_ard_3-2-1_090075_2022-10-20_final
2022-10-21 10:56:10	ga_ls8c_ard_3-2-1_106075_2022-10-21_final
2022-10-22 10:00:33	ga_ls8c_ard_3-2-1_097075_2022-10-22_final
2022-10-22 11:39:26	ga_ls8c_ard_3-2-1_113075_2022-10-22_final
2022-10-23 10:43:49	ga_ls8c_ard_3-2-1_104075_2022-10-23_final
2022-10-24 09:47:48	ga_ls8c_ard_3-2-1_095074_2022-10-24_final
2022-10-24 09:48:12	ga_ls8c_ard_3-2-1_095075_2022-10-24_final
2022-10-24 11:27:05	ga_ls8c_ard_3-2-1_111075_2022-10-24_final
2022-10-25 10:31:05	ga_ls8c_ard_3-2-1_102074_2022-10-25_final
2022-10-25 10:31:29	ga_ls8c_ard_3-2-1_102075_2022-10-25_final
2022-10-26 09:35:52	ga_ls8c_ard_3-2-1_093075_2022-10-26_final
2022-10-26 11:14:45	ga_ls8c_ard_3-2-1_109075_2022-10-26_final
2022-10-27 10:19:08	ga_ls8c_ard_3-2-1_100075_2022-10-27_final
2022-10-27 11:58:01	ga_ls8c_ard_3-2-1_116075_2022-10-27_final
2022-10-28 09:23:31	ga_ls8c_ard_3-2-1_091075_2022-10-27_final
2022-10-28 11:02:24	ga_ls8c_ard_3-2-1_107075_2022-10-28_final
2022-10-29 10:06:47	ga_ls8c_ard_3-2-1_098075_2022-10-29_final
2022-10-29 11:45:40	ga_ls8c_ard_3-2-1_114075_2022-10-29_final
2022-10-30 09:11:10	ga_ls8c_ard_3-2-1_089075_2022-10-29_final
2022-11-20 11:08:28	ga_ls8c_ard_3-2-1_108075_2022-11-20_final
2022-11-21 10:12:51	ga_ls8c_ard_3-2-1_099075_2022-11-21_final
2022-11-21 11:51:20	ga_ls8c_ard_3-2-1_115074_2022-11-21_final
2022-11-21 11:51:44	ga_ls8c_ard_3-2-1_115075_2022-11-21_final
2022-11-22 09:16:50	ga_ls8c_ard_3-2-1_090074_2022-11-21_final
2022-11-22 09:17:14	ga_ls8c_ard_3-2-1_090075_2022-11-21_final
2022-11-22 10:56:07	ga_ls8c_ard_3-2-1_106075_2022-11-22_final
2022-11-23 10:00:30	ga_ls8c_ard_3-2-1_097075_2022-11-23_final
2022-11-23 11:39:23	ga_ls8c_ard_3-2-1_113075_2022-11-23_final
2022-11-24 10:43:46	ga_ls8c_ard_3-2-1_104075_2022-11-24_final
2022-11-25 09:48:09	ga_ls8c_ard_3-2-1_095075_2022-11-25_final
2022-11-27 11:14:41	ga_ls8c_ard_3-2-1_109075_2022-11-27_final
2022-11-28 10:19:04	ga_ls8c_ard_3-2-1_100075_2022-11-28_final
2022-11-28 11:57:57	ga_ls8c_ard_3-2-1_116075_2022-11-28_final
2022-11-29 09:23:26	ga_ls8c_ard_3-2-1_091075_2022-11-28_final
2022-11-29 11:02:19	ga_ls8c_ard_3-2-1_107075_2022-11-29_final
2022-11-30 10:06:42	ga_ls8c_ard_3-2-1_098075_2022-11-30_final
2022-12-02 11:33:14	ga_ls8c_ard_3-2-1_112075_2022-12-02_final
2022-12-03 10:37:36	ga_ls8c_ard_3-2-1_103075_2022-12-03_final
2022-12-04 09:41:59	ga_ls8c_ard_3-2-1_094075_2022-12-04_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