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
2017-02-05 09:41:26	ga_ls8c_ard_3-0-0_094075_2017-02-05_final
2017-02-05 11:20:19	ga_ls8c_ard_3-0-0_110075_2017-02-05_final
2017-02-06 10:24:17	ga_ls8c_ard_3-0-0_101074_2017-02-06_final
2017-02-06 10:24:41	ga_ls8c_ard_3-0-0_101075_2017-02-06_final
2017-02-19 09:53:42	ga_ls8c_ard_3-0-0_096075_2017-02-19_final
2017-02-19 11:32:11	ga_ls8c_ard_3-0-0_112074_2017-02-19_final
2017-02-19 11:32:35	ga_ls8c_ard_3-0-0_112075_2017-02-19_final
2017-02-20 10:36:57	ga_ls8c_ard_3-0-0_103075_2017-02-20_final
2017-02-21 09:41:20	ga_ls8c_ard_3-0-0_094075_2017-02-21_final
2017-02-21 11:20:13	ga_ls8c_ard_3-0-0_110075_2017-02-21_final
2017-02-22 10:24:11	ga_ls8c_ard_3-0-0_101074_2017-02-22_final
2017-02-22 10:24:35	ga_ls8c_ard_3-0-0_101075_2017-02-22_final
2018-06-18 09:27:35	ga_ls8c_ard_3-0-0_092074_2018-06-17_final
2018-06-18 09:27:59	ga_ls8c_ard_3-0-0_092075_2018-06-17_final
2018-06-18 11:06:28	ga_ls8c_ard_3-0-0_108074_2018-06-18_final
2018-06-18 11:06:52	ga_ls8c_ard_3-0-0_108075_2018-06-18_final
2018-06-19 10:10:51	ga_ls8c_ard_3-0-0_099074_2018-06-19_final
2018-06-19 10:11:15	ga_ls8c_ard_3-0-0_099075_2018-06-19_final
2018-06-19 11:49:44	ga_ls8c_ard_3-0-0_115074_2018-06-19_final
2018-06-19 11:50:08	ga_ls8c_ard_3-0-0_115075_2018-06-19_final
2018-06-20 09:15:15	ga_ls8c_ard_3-0-0_090074_2018-06-19_final
2018-06-20 09:15:39	ga_ls8c_ard_3-0-0_090075_2018-06-19_final
2018-07-30 10:05:01	ga_ls8c_ard_3-0-0_098074_2018-07-30_final
2018-07-30 10:05:25	ga_ls8c_ard_3-0-0_098075_2018-07-30_final
2018-07-30 11:43:54	ga_ls8c_ard_3-0-0_114074_2018-07-30_final
2018-07-30 11:44:18	ga_ls8c_ard_3-0-0_114075_2018-07-30_final
2018-07-31 09:09:24	ga_ls8c_ard_3-0-0_089074_2018-07-30_final
2018-07-31 09:09:48	ga_ls8c_ard_3-0-0_089075_2018-07-30_final
2018-07-31 10:48:41	ga_ls8c_ard_3-0-0_105075_2018-07-31_final
2018-08-15 10:05:10	ga_ls8c_ard_3-0-0_098074_2018-08-15_final
2018-08-15 10:05:34	ga_ls8c_ard_3-0-0_098075_2018-08-15_final
2018-08-15 11:44:03	ga_ls8c_ard_3-0-0_114074_2018-08-15_final
2018-08-15 11:44:27	ga_ls8c_ard_3-0-0_114075_2018-08-15_final
2018-08-16 09:09:33	ga_ls8c_ard_3-0-0_089074_2018-08-15_final
2018-08-16 09:09:57	ga_ls8c_ard_3-0-0_089075_2018-08-15_final
2018-08-16 10:48:26	ga_ls8c_ard_3-0-0_105074_2018-08-16_final
2018-08-16 10:48:50	ga_ls8c_ard_3-0-0_105075_2018-08-16_final
2018-08-31 10:05:17	ga_ls8c_ard_3-0-0_098074_2018-08-31_final
2018-08-31 10:05:41	ga_ls8c_ard_3-0-0_098075_2018-08-31_final
2018-08-31 11:44:10	ga_ls8c_ard_3-0-0_114074_2018-08-31_final
2018-08-31 11:44:34	ga_ls8c_ard_3-0-0_114075_2018-08-31_final
2018-09-01 09:09:40	ga_ls8c_ard_3-0-0_089074_2018-08-31_final
2018-09-01 09:10:04	ga_ls8c_ard_3-0-0_089075_2018-08-31_final
2018-09-01 10:48:33	ga_ls8c_ard_3-0-0_105074_2018-09-01_final
2018-09-01 10:48:57	ga_ls8c_ard_3-0-0_105075_2018-09-01_final
2018-11-11 10:55:07	ga_ls8c_ard_3-0-0_106074_2018-11-11_final
2018-11-11 10:55:31	ga_ls8c_ard_3-0-0_106075_2018-11-11_final
2018-11-12 09:59:54	ga_ls8c_ard_3-0-0_097075_2018-11-12_final
2018-11-12 11:38:23	ga_ls8c_ard_3-0-0_113074_2018-11-12_final
2018-11-12 11:38:47	ga_ls8c_ard_3-0-0_113075_2018-11-12_final
2018-11-13 09:04:16	ga_ls8c_ard_3-2-1_088075_2018-11-12_interim
2018-11-13 10:42:46	ga_ls8c_ard_3-0-0_104074_2018-11-13_final
2018-11-13 10:43:09	ga_ls8c_ard_3-0-0_104075_2018-11-13_final
2018-11-18 09:22:25	ga_ls8c_ard_3-0-0_091074_2018-11-17_final
2018-11-18 09:22:49	ga_ls8c_ard_3-0-0_091075_2018-11-17_final
2018-11-18 11:01:42	ga_ls8c_ard_3-0-0_107075_2018-11-18_final
2019-01-05 09:22:21	ga_ls8c_ard_3-0-0_091074_2019-01-04_final
2019-01-05 09:22:45	ga_ls8c_ard_3-0-0_091075_2019-01-04_final
2019-01-05 11:01:38	ga_ls8c_ard_3-0-0_107075_2019-01-05_final
2019-01-12 09:28:30	ga_ls8c_ard_3-0-0_092074_2019-01-11_final
2019-01-12 09:28:54	ga_ls8c_ard_3-0-0_092075_2019-01-11_final
2019-01-12 11:07:23	ga_ls8c_ard_3-0-0_108074_2019-01-12_final
2019-01-12 11:07:47	ga_ls8c_ard_3-0-0_108075_2019-01-12_final
2019-01-13 10:11:46	ga_ls8c_ard_3-0-0_099074_2019-01-13_final
2019-01-13 10:12:10	ga_ls8c_ard_3-0-0_099075_2019-01-13_final
2019-01-13 11:51:03	ga_ls8c_ard_3-0-0_115075_2019-01-13_final
2019-01-14 09:16:32	ga_ls8c_ard_3-0-0_090075_2019-01-13_final
2019-01-14 10:55:25	ga_ls8c_ard_3-0-0_106075_2019-01-14_final
2019-01-15 09:59:24	ga_ls8c_ard_3-0-0_097074_2019-01-15_final
2019-01-15 09:59:48	ga_ls8c_ard_3-0-0_097075_2019-01-15_final
2019-01-15 11:38:41	ga_ls8c_ard_3-0-0_113075_2019-01-15_final
2019-01-16 10:43:03	ga_ls8c_ard_3-0-0_104075_2019-01-16_final
2019-07-17 10:06:05	ga_ls8c_ard_3-1-0_098075_2019-07-17_final
2019-07-17 11:44:34	ga_ls8c_ard_3-1-0_114074_2019-07-17_final
2019-07-17 11:44:58	ga_ls8c_ard_3-1-0_114075_2019-07-17_final
2019-07-18 09:10:04	ga_ls8c_ard_3-1-0_089074_2019-07-17_final
2019-07-18 09:10:28	ga_ls8c_ard_3-1-0_089075_2019-07-17_final
2019-07-18 10:48:57	ga_ls8c_ard_3-1-0_105074_2019-07-18_final
2019-07-18 10:49:21	ga_ls8c_ard_3-1-0_105075_2019-07-18_final
2019-09-09 09:28:54	ga_ls8c_ard_3-1-0_092074_2019-09-08_final
2019-09-09 09:29:18	ga_ls8c_ard_3-1-0_092075_2019-09-08_final
2019-09-09 11:08:11	ga_ls8c_ard_3-1-0_108075_2019-09-09_final
2019-09-10 10:12:10	ga_ls8c_ard_3-1-0_099074_2019-09-10_final
2019-09-10 10:12:34	ga_ls8c_ard_3-1-0_099075_2019-09-10_final
2019-09-10 11:51:03	ga_ls8c_ard_3-1-0_115074_2019-09-10_final
2019-09-10 11:51:27	ga_ls8c_ard_3-1-0_115075_2019-09-10_final
2019-09-11 09:16:33	ga_ls8c_ard_3-1-0_090074_2019-09-10_final
2019-09-11 09:16:57	ga_ls8c_ard_3-1-0_090075_2019-09-10_final
2019-09-11 10:55:26	ga_ls8c_ard_3-1-0_106074_2019-09-11_final
2019-09-11 10:55:50	ga_ls8c_ard_3-1-0_106075_2019-09-11_final
2019-09-12 10:00:13	ga_ls8c_ard_3-1-0_097075_2019-09-12_final
2019-09-12 11:38:42	ga_ls8c_ard_3-1-0_113074_2019-09-12_final
2019-09-12 11:39:06	ga_ls8c_ard_3-1-0_113075_2019-09-12_final
2019-09-13 10:43:29	ga_ls8c_ard_3-1-0_104075_2019-09-13_final
2019-10-21 10:06:32	ga_ls8c_ard_3-1-0_098075_2019-10-21_final
2019-10-21 11:45:01	ga_ls8c_ard_3-1-0_114074_2019-10-21_final
2019-10-21 11:45:25	ga_ls8c_ard_3-1-0_114075_2019-10-21_final
2019-10-22 09:10:31	ga_ls8c_ard_3-1-0_089074_2019-10-21_final
2019-10-22 09:10:55	ga_ls8c_ard_3-1-0_089075_2019-10-21_final
2019-10-22 10:49:24	ga_ls8c_ard_3-1-0_105074_2019-10-22_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