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
2018-08-17 09:52:50	ga_ls8c_ard_3-0-0_096074_2018-08-17_final
2018-08-17 09:53:14	ga_ls8c_ard_3-0-0_096075_2018-08-17_final
2018-08-17 11:31:43	ga_ls8c_ard_3-0-0_112074_2018-08-17_final
2018-08-17 11:32:07	ga_ls8c_ard_3-0-0_112075_2018-08-17_final
2018-08-18 10:36:06	ga_ls8c_ard_3-0-0_103074_2018-08-18_final
2018-08-18 10:36:30	ga_ls8c_ard_3-0-0_103075_2018-08-18_final
2018-08-19 09:40:29	ga_ls8c_ard_3-0-0_094074_2018-08-19_final
2018-08-19 09:40:53	ga_ls8c_ard_3-0-0_094075_2018-08-19_final
2018-08-19 11:19:22	ga_ls8c_ard_3-0-0_110074_2018-08-19_final
2018-08-19 11:19:46	ga_ls8c_ard_3-0-0_110075_2018-08-19_final
2018-08-20 10:23:45	ga_ls8c_ard_3-0-0_101074_2018-08-20_final
2018-08-20 10:24:09	ga_ls8c_ard_3-0-0_101075_2018-08-20_final
2018-09-02 09:52:56	ga_ls8c_ard_3-0-0_096074_2018-09-02_final
2018-09-02 09:53:20	ga_ls8c_ard_3-0-0_096075_2018-09-02_final
2018-09-02 11:31:49	ga_ls8c_ard_3-0-0_112074_2018-09-02_final
2018-09-02 11:32:13	ga_ls8c_ard_3-0-0_112075_2018-09-02_final
2018-09-03 10:36:12	ga_ls8c_ard_3-0-0_103074_2018-09-03_final
2018-09-03 10:36:36	ga_ls8c_ard_3-0-0_103075_2018-09-03_final
2018-09-04 09:40:35	ga_ls8c_ard_3-0-0_094074_2018-09-04_final
2018-09-04 09:40:59	ga_ls8c_ard_3-0-0_094075_2018-09-04_final
2018-09-04 11:19:28	ga_ls8c_ard_3-0-0_110074_2018-09-04_final
2018-09-04 11:19:52	ga_ls8c_ard_3-0-0_110075_2018-09-04_final
2018-09-05 10:23:51	ga_ls8c_ard_3-0-0_101074_2018-09-05_final
2018-09-05 10:24:15	ga_ls8c_ard_3-0-0_101075_2018-09-05_final
2018-09-16 10:05:22	ga_ls8c_ard_3-0-0_098074_2018-09-16_final
2018-09-16 10:05:46	ga_ls8c_ard_3-0-0_098075_2018-09-16_final
2018-09-16 11:44:15	ga_ls8c_ard_3-0-0_114074_2018-09-16_final
2018-09-16 11:44:39	ga_ls8c_ard_3-0-0_114075_2018-09-16_final
2018-09-17 09:09:45	ga_ls8c_ard_3-0-0_089074_2018-09-16_final
2018-09-17 09:10:09	ga_ls8c_ard_3-0-0_089075_2018-09-16_final
2018-09-17 10:48:38	ga_ls8c_ard_3-0-0_105074_2018-09-17_final
2018-09-17 10:49:02	ga_ls8c_ard_3-0-0_105075_2018-09-17_final
2019-01-06 10:05:36	ga_ls8c_ard_3-0-0_098074_2019-01-06_final
2019-01-06 10:06:00	ga_ls8c_ard_3-0-0_098075_2019-01-06_final
2019-01-06 11:44:29	ga_ls8c_ard_3-0-0_114074_2019-01-06_final
2019-01-06 11:44:53	ga_ls8c_ard_3-0-0_114075_2019-01-06_final
2019-01-07 09:09:59	ga_ls8c_ard_3-0-0_089074_2019-01-06_final
2019-01-07 09:10:23	ga_ls8c_ard_3-0-0_089075_2019-01-06_final
2019-01-07 10:48:52	ga_ls8c_ard_3-0-0_105074_2019-01-07_final
2019-01-07 10:49:16	ga_ls8c_ard_3-0-0_105075_2019-01-07_final
2023-03-23 10:48:51	ga_ls8c_ard_3-2-1_105074_2023-03-23_final
2023-03-23 10:49:15	ga_ls8c_ard_3-2-1_105075_2023-03-23_final
2023-03-24 09:53:37	ga_ls8c_ard_3-2-1_096075_2023-03-24_final
2023-03-24 11:32:30	ga_ls8c_ard_3-2-1_112075_2023-03-24_final
2023-03-25 10:36:29	ga_ls8c_ard_3-2-1_103074_2023-03-25_final
2023-03-25 10:36:52	ga_ls8c_ard_3-2-1_103075_2023-03-25_final
2023-03-26 09:41:15	ga_ls8c_ard_3-2-1_094075_2023-03-26_final
2023-03-26 11:19:44	ga_ls8c_ard_3-2-1_110074_2023-03-26_final
2023-03-26 11:20:08	ga_ls8c_ard_3-2-1_110075_2023-03-26_final
2023-03-29 10:12:08	ga_ls8c_ard_3-2-1_099075_2023-03-29_final
2023-03-29 11:51:01	ga_ls8c_ard_3-2-1_115075_2023-03-29_final
2023-03-30 09:16:06	ga_ls8c_ard_3-2-1_090074_2023-03-29_final
2023-03-30 09:16:30	ga_ls8c_ard_3-2-1_090075_2023-03-29_final
2023-03-30 10:55:23	ga_ls8c_ard_3-2-1_106075_2023-03-30_final
2023-03-31 09:59:45	ga_ls8c_ard_3-2-1_097075_2023-03-31_final
2023-03-31 11:38:14	ga_ls8c_ard_3-2-1_113074_2023-03-31_final
2023-03-31 11:38:38	ga_ls8c_ard_3-2-1_113075_2023-03-31_final
2023-04-04 11:13:51	ga_ls8c_ard_3-2-1_109075_2023-04-04_final
2023-04-06 11:01:27	ga_ls8c_ard_3-2-1_107075_2023-04-06_final
2023-04-08 10:49:02	ga_ls8c_ard_3-2-1_105075_2023-04-08_final
2023-04-09 09:52:59	ga_ls8c_ard_3-2-1_096074_2023-04-09_final
2023-04-09 09:53:23	ga_ls8c_ard_3-2-1_096075_2023-04-09_final
2023-04-14 10:11:53	ga_ls8c_ard_3-2-1_099075_2023-04-14_final
2023-04-14 11:50:22	ga_ls8c_ard_3-2-1_115074_2023-04-14_final
2023-04-14 11:50:46	ga_ls8c_ard_3-2-1_115075_2023-04-14_final
2023-04-15 09:15:51	ga_ls8c_ard_3-2-1_090074_2023-04-14_final
2023-04-15 09:16:15	ga_ls8c_ard_3-2-1_090075_2023-04-14_final
2023-04-15 10:55:08	ga_ls8c_ard_3-2-1_106075_2023-04-15_final
2023-04-21 10:18:01	ga_ls8c_ard_3-2-1_100075_2023-04-21_final
2023-04-21 11:56:54	ga_ls8c_ard_3-2-1_116075_2023-04-21_final
2023-04-24 09:09:38	ga_ls8c_ard_3-2-1_089074_2023-04-23_final
2023-04-24 09:10:02	ga_ls8c_ard_3-2-1_089075_2023-04-23_final
2023-04-24 10:48:55	ga_ls8c_ard_3-2-1_105075_2023-04-24_final
2023-04-25 09:53:18	ga_ls8c_ard_3-2-1_096075_2023-04-25_final
2023-04-27 09:40:56	ga_ls8c_ard_3-2-1_094075_2023-04-27_final
2023-04-27 11:19:49	ga_ls8c_ard_3-2-1_110075_2023-04-27_final
2023-04-28 10:23:47	ga_ls8c_ard_3-2-1_101074_2023-04-28_final
2023-04-28 10:24:11	ga_ls8c_ard_3-2-1_101075_2023-04-28_final
2023-05-01 10:55:03	ga_ls8c_ard_3-2-1_106075_2023-05-01_final
2023-05-02 09:59:26	ga_ls8c_ard_3-2-1_097075_2023-05-02_final
2023-05-02 11:38:19	ga_ls8c_ard_3-2-1_113075_2023-05-02_final
2023-05-04 09:47:02	ga_ls8c_ard_3-2-1_095075_2023-05-04_final
2023-05-04 11:25:31	ga_ls8c_ard_3-2-1_111074_2023-05-04_final
2023-05-04 11:25:55	ga_ls8c_ard_3-2-1_111075_2023-05-04_final
2023-05-05 10:30:17	ga_ls8c_ard_3-2-1_102075_2023-05-05_final
2023-05-08 09:21:51	ga_ls8c_ard_3-2-1_091074_2023-05-07_final
2023-05-08 09:22:15	ga_ls8c_ard_3-2-1_091075_2023-05-07_final
2023-07-21 09:59:40	ga_ls8c_ard_3-2-1_097075_2023-07-21_final
2023-07-22 10:42:32	ga_ls8c_ard_3-2-1_104074_2023-07-22_final
2023-07-22 10:42:56	ga_ls8c_ard_3-2-1_104075_2023-07-22_final
2023-07-23 09:46:56	ga_ls8c_ard_3-2-1_095074_2023-07-23_final
2023-07-23 09:47:20	ga_ls8c_ard_3-2-1_095075_2023-07-23_final
2023-07-23 11:25:49	ga_ls8c_ard_3-2-1_111074_2023-07-23_final
2023-07-23 11:26:13	ga_ls8c_ard_3-2-1_111075_2023-07-23_final
2023-07-26 10:17:53	ga_ls8c_ard_3-2-1_100074_2023-07-26_final
2023-07-26 10:18:17	ga_ls8c_ard_3-2-1_100075_2023-07-26_final
2023-07-26 11:57:10	ga_ls8c_ard_3-2-1_116075_2023-07-26_final
2023-07-27 09:22:16	ga_ls8c_ard_3-2-1_091074_2023-07-26_final
2023-07-27 09:22:40	ga_ls8c_ard_3-2-1_091075_2023-07-26_final
2023-07-27 11:01:09	ga_ls8c_ard_3-2-1_107074_2023-07-27_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years