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 10:12:02	ga_ls8c_ard_3-0-0_099074_2017-09-04_final
2017-09-04 10:12:26	ga_ls8c_ard_3-0-0_099075_2017-09-04_final
2017-09-04 11:50:55	ga_ls8c_ard_3-0-0_115074_2017-09-04_final
2017-09-04 11:51:19	ga_ls8c_ard_3-0-0_115075_2017-09-04_final
2017-09-05 09:16:25	ga_ls8c_ard_3-0-0_090074_2017-09-04_final
2017-09-05 09:16:49	ga_ls8c_ard_3-0-0_090075_2017-09-04_final
2017-09-05 10:55:18	ga_ls8c_ard_3-0-0_106074_2017-09-05_final
2017-09-05 10:55:42	ga_ls8c_ard_3-0-0_106075_2017-09-05_final
2017-09-06 09:59:40	ga_ls8c_ard_3-0-0_097074_2017-09-06_final
2017-09-06 10:00:04	ga_ls8c_ard_3-0-0_097075_2017-09-06_final
2017-09-06 11:38:33	ga_ls8c_ard_3-0-0_113074_2017-09-06_final
2017-09-06 11:38:57	ga_ls8c_ard_3-0-0_113075_2017-09-06_final
2017-09-07 10:42:56	ga_ls8c_ard_3-0-0_104074_2017-09-07_final
2017-09-07 10:43:20	ga_ls8c_ard_3-0-0_104075_2017-09-07_final
2017-09-08 09:47:19	ga_ls8c_ard_3-0-0_095074_2017-09-08_final
2017-09-08 09:47:43	ga_ls8c_ard_3-0-0_095075_2017-09-08_final
2017-09-08 11:26:12	ga_ls8c_ard_3-0-0_111074_2017-09-08_final
2017-09-08 11:26:36	ga_ls8c_ard_3-0-0_111075_2017-09-08_final
2017-10-25 10:43:08	ga_ls8c_ard_3-0-0_104074_2017-10-25_final
2017-10-25 10:43:32	ga_ls8c_ard_3-0-0_104075_2017-10-25_final
2017-10-26 09:47:30	ga_ls8c_ard_3-0-0_095074_2017-10-26_final
2017-10-26 09:47:54	ga_ls8c_ard_3-0-0_095075_2017-10-26_final
2017-10-26 11:26:23	ga_ls8c_ard_3-0-0_111074_2017-10-26_final
2017-10-26 11:26:47	ga_ls8c_ard_3-0-0_111075_2017-10-26_final
2017-10-27 10:30:46	ga_ls8c_ard_3-0-0_102074_2017-10-27_final
2017-10-27 10:31:10	ga_ls8c_ard_3-0-0_102075_2017-10-27_final
2017-11-26 10:43:00	ga_ls8c_ard_3-0-0_104074_2017-11-26_final
2017-11-26 10:43:24	ga_ls8c_ard_3-0-0_104075_2017-11-26_final
2017-11-27 09:47:22	ga_ls8c_ard_3-0-0_095074_2017-11-27_final
2017-11-27 09:47:46	ga_ls8c_ard_3-0-0_095075_2017-11-27_final
2017-11-27 11:26:15	ga_ls8c_ard_3-0-0_111074_2017-11-27_final
2017-11-27 11:26:39	ga_ls8c_ard_3-0-0_111075_2017-11-27_final
2017-11-28 10:30:37	ga_ls8c_ard_3-0-0_102074_2017-11-28_final
2017-11-28 10:31:01	ga_ls8c_ard_3-0-0_102075_2017-11-28_final
2022-01-22 10:55:46	ga_ls8c_ard_3-2-1_106075_2022-01-22_final
2022-01-23 09:59:44	ga_ls8c_ard_3-2-1_097074_2022-01-23_final
2022-01-23 10:00:08	ga_ls8c_ard_3-2-1_097075_2022-01-23_final
2022-01-23 11:38:37	ga_ls8c_ard_3-2-1_113074_2022-01-23_final
2022-01-23 11:39:01	ga_ls8c_ard_3-2-1_113075_2022-01-23_final
2022-01-24 10:42:59	ga_ls8c_ard_3-2-1_104074_2022-01-24_final
2022-01-24 10:43:23	ga_ls8c_ard_3-2-1_104075_2022-01-24_final
2022-01-25 09:47:22	ga_ls8c_ard_3-2-1_095074_2022-01-25_final
2022-01-25 09:47:46	ga_ls8c_ard_3-2-1_095075_2022-01-25_final
2022-01-25 11:26:15	ga_ls8c_ard_3-2-1_111074_2022-01-25_final
2022-01-25 11:26:39	ga_ls8c_ard_3-2-1_111075_2022-01-25_final
2022-03-27 10:55:22	ga_ls8c_ard_3-2-1_106075_2022-03-27_final
2022-04-02 10:17:50	ga_ls8c_ard_3-2-1_100074_2022-04-02_final
2022-04-02 10:18:14	ga_ls8c_ard_3-2-1_100075_2022-04-02_final
2022-04-02 11:57:07	ga_ls8c_ard_3-2-1_116075_2022-04-02_final
2022-04-03 09:22:37	ga_ls8c_ard_3-2-1_091075_2022-04-02_final
2022-04-03 11:01:06	ga_ls8c_ard_3-2-1_107074_2022-04-03_final
2022-04-03 11:01:30	ga_ls8c_ard_3-2-1_107075_2022-04-03_final
2022-04-04 10:05:53	ga_ls8c_ard_3-2-1_098075_2022-04-04_final
2022-04-04 11:44:46	ga_ls8c_ard_3-2-1_114075_2022-04-04_final
2022-04-05 09:09:53	ga_ls8c_ard_3-2-1_089074_2022-04-04_final
2022-04-05 09:10:17	ga_ls8c_ard_3-2-1_089075_2022-04-04_final
2022-04-05 10:49:10	ga_ls8c_ard_3-2-1_105075_2022-04-05_final
2022-04-06 09:53:09	ga_ls8c_ard_3-2-1_096074_2022-04-06_final
2022-04-06 09:53:33	ga_ls8c_ard_3-2-1_096075_2022-04-06_final
2022-04-06 11:32:02	ga_ls8c_ard_3-2-1_112074_2022-04-06_final
2022-04-06 11:32:26	ga_ls8c_ard_3-2-1_112075_2022-04-06_final
2023-02-12 10:43:07	ga_ls8c_ard_3-2-1_104074_2023-02-12_final
2023-02-12 10:43:31	ga_ls8c_ard_3-2-1_104075_2023-02-12_final
2023-02-13 09:47:29	ga_ls8c_ard_3-2-1_095074_2023-02-13_final
2023-02-13 09:47:53	ga_ls8c_ard_3-2-1_095075_2023-02-13_final
2023-02-13 11:26:22	ga_ls8c_ard_3-2-1_111074_2023-02-13_final
2023-02-13 11:26:46	ga_ls8c_ard_3-2-1_111075_2023-02-13_final
2023-02-14 10:30:44	ga_ls8c_ard_3-2-1_102074_2023-02-14_final
2023-02-14 10:31:08	ga_ls8c_ard_3-2-1_102075_2023-02-14_final
2023-02-15 09:35:06	ga_ls8c_ard_3-2-1_093074_2023-02-15_final
2023-02-15 09:35:30	ga_ls8c_ard_3-2-1_093075_2023-02-15_final
2023-02-15 11:13:59	ga_ls8c_ard_3-2-1_109074_2023-02-15_final
2023-02-15 11:14:23	ga_ls8c_ard_3-2-1_109075_2023-02-15_final
2023-02-16 10:18:21	ga_ls8c_ard_3-2-1_100074_2023-02-16_final
2023-02-16 10:18:45	ga_ls8c_ard_3-2-1_100075_2023-02-16_final
2023-02-16 11:57:38	ga_ls8c_ard_3-2-1_116075_2023-02-16_final
2023-02-17 09:22:43	ga_ls8c_ard_3-2-1_091074_2023-02-16_final
2023-02-17 09:23:07	ga_ls8c_ard_3-2-1_091075_2023-02-16_final
2023-02-17 11:02:00	ga_ls8c_ard_3-2-1_107075_2023-02-17_final
2023-02-18 10:05:57	ga_ls8c_ard_3-2-1_098074_2023-02-18_final
2023-02-18 10:06:21	ga_ls8c_ard_3-2-1_098075_2023-02-18_final
2023-02-18 11:45:14	ga_ls8c_ard_3-2-1_114075_2023-02-18_final
2023-02-19 09:10:19	ga_ls8c_ard_3-2-1_089074_2023-02-18_final
2023-02-19 09:10:43	ga_ls8c_ard_3-2-1_089075_2023-02-18_final
2023-02-19 10:49:12	ga_ls8c_ard_3-2-1_105074_2023-02-19_final
2023-02-19 10:49:36	ga_ls8c_ard_3-2-1_105075_2023-02-19_final
2023-02-20 09:53:33	ga_ls8c_ard_3-2-1_096074_2023-02-20_final
2023-02-24 11:08:01	ga_ls8c_ard_3-2-1_108075_2023-02-24_final
2023-02-25 10:11:58	ga_ls8c_ard_3-2-1_099074_2023-02-25_final
2023-02-25 10:12:22	ga_ls8c_ard_3-2-1_099075_2023-02-25_final
2023-02-25 11:50:52	ga_ls8c_ard_3-2-1_115074_2023-02-25_final
2023-02-25 11:51:15	ga_ls8c_ard_3-2-1_115075_2023-02-25_final
2023-02-26 09:16:21	ga_ls8c_ard_3-2-1_090074_2023-02-25_final
2023-02-26 09:16:45	ga_ls8c_ard_3-2-1_090075_2023-02-25_final
2023-02-26 10:55:14	ga_ls8c_ard_3-2-1_106074_2023-02-26_final
2023-02-26 10:55:38	ga_ls8c_ard_3-2-1_106075_2023-02-26_final
2023-02-27 09:59:37	ga_ls8c_ard_3-2-1_097074_2023-02-27_final
2023-02-27 10:00:01	ga_ls8c_ard_3-2-1_097075_2023-02-27_final
2023-02-27 11:38:54	ga_ls8c_ard_3-2-1_113075_2023-02-27_final
2023-02-28 10:42:53	ga_ls8c_ard_3-2-1_104074_2023-02-28_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