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
2015-04-21 09:39:59	ga_ls8c_ard_3-0-0_094073_2015-04-21_final
2015-04-21 11:18:52	ga_ls8c_ard_3-0-0_110073_2015-04-21_final
2015-04-22 10:23:14	ga_ls8c_ard_3-0-0_101073_2015-04-22_final
2015-04-23 09:27:36	ga_ls8c_ard_3-0-0_092073_2015-04-22_final
2015-04-23 11:06:29	ga_ls8c_ard_3-0-0_108073_2015-04-23_final
2015-04-24 10:10:51	ga_ls8c_ard_3-0-0_099073_2015-04-24_final
2015-04-24 11:49:45	ga_ls8c_ard_3-0-0_115073_2015-04-24_final
2015-04-28 09:46:05	ga_ls8c_ard_3-0-0_095073_2015-04-28_final
2015-04-28 11:24:58	ga_ls8c_ard_3-0-0_111073_2015-04-28_final
2015-04-29 10:29:20	ga_ls8c_ard_3-0-0_102073_2015-04-29_final
2015-04-30 09:33:41	ga_ls8c_ard_3-0-0_093073_2015-04-30_final
2015-04-30 11:12:34	ga_ls8c_ard_3-0-0_109073_2015-04-30_final
2015-05-01 10:16:56	ga_ls8c_ard_3-0-0_100073_2015-05-01_final
2015-06-15 09:46:05	ga_ls8c_ard_3-0-0_095073_2015-06-15_final
2015-06-15 11:24:58	ga_ls8c_ard_3-0-0_111073_2015-06-15_final
2015-06-15 11:25:22	ga_ls8c_ard_3-0-0_111074_2015-06-15_final
2015-06-16 10:29:21	ga_ls8c_ard_3-0-0_102073_2015-06-16_final
2015-06-16 10:29:45	ga_ls8c_ard_3-0-0_102074_2015-06-16_final
2015-06-17 09:33:44	ga_ls8c_ard_3-0-0_093073_2015-06-17_final
2015-06-17 09:34:08	ga_ls8c_ard_3-0-0_093074_2015-06-17_final
2015-06-17 11:12:37	ga_ls8c_ard_3-0-0_109073_2015-06-17_final
2015-06-17 11:13:01	ga_ls8c_ard_3-0-0_109074_2015-06-17_final
2015-06-18 10:17:00	ga_ls8c_ard_3-0-0_100073_2015-06-18_final
2015-06-18 10:17:24	ga_ls8c_ard_3-0-0_100074_2015-06-18_final
2015-08-20 11:13:04	ga_ls8c_ard_3-0-0_109073_2015-08-20_final
2015-08-21 10:17:28	ga_ls8c_ard_3-0-0_100073_2015-08-21_final
2015-08-21 10:17:51	ga_ls8c_ard_3-0-0_100074_2015-08-21_final
2016-12-20 10:24:07	ga_ls8c_ard_3-0-0_101073_2016-12-20_final
2017-03-09 09:40:24	ga_ls8c_ard_3-0-0_094073_2017-03-09_final
2017-03-09 11:19:17	ga_ls8c_ard_3-0-0_110073_2017-03-09_final
2017-03-10 10:23:40	ga_ls8c_ard_3-0-0_101073_2017-03-10_final
2018-06-07 09:45:36	ga_ls8c_ard_3-0-0_095073_2018-06-07_final
2018-06-07 09:45:59	ga_ls8c_ard_3-0-0_095074_2018-06-07_final
2018-06-07 11:24:29	ga_ls8c_ard_3-0-0_111073_2018-06-07_final
2018-06-08 10:28:52	ga_ls8c_ard_3-0-0_102073_2018-06-08_final
2018-06-08 10:29:16	ga_ls8c_ard_3-0-0_102074_2018-06-08_final
2018-06-09 09:33:15	ga_ls8c_ard_3-0-0_093073_2018-06-09_final
2018-06-09 09:33:39	ga_ls8c_ard_3-0-0_093074_2018-06-09_final
2018-06-09 11:12:09	ga_ls8c_ard_3-0-0_109073_2018-06-09_final
2018-06-10 10:16:32	ga_ls8c_ard_3-0-0_100073_2018-06-10_final
2018-06-10 10:16:56	ga_ls8c_ard_3-0-0_100074_2018-06-10_final
2018-06-23 09:45:47	ga_ls8c_ard_3-0-0_095073_2018-06-23_final
2018-06-23 11:24:40	ga_ls8c_ard_3-0-0_111073_2018-06-23_final
2018-06-23 11:25:04	ga_ls8c_ard_3-0-0_111074_2018-06-23_final
2018-06-24 10:29:03	ga_ls8c_ard_3-0-0_102073_2018-06-24_final
2018-06-24 10:29:27	ga_ls8c_ard_3-0-0_102074_2018-06-24_final
2018-06-25 09:33:26	ga_ls8c_ard_3-0-0_093073_2018-06-25_final
2018-06-25 09:33:50	ga_ls8c_ard_3-0-0_093074_2018-06-25_final
2018-06-25 11:12:19	ga_ls8c_ard_3-0-0_109073_2018-06-25_final
2018-06-26 10:16:43	ga_ls8c_ard_3-0-0_100073_2018-06-26_final
2018-07-09 09:45:55	ga_ls8c_ard_3-0-0_095073_2018-07-09_final
2018-07-09 11:24:49	ga_ls8c_ard_3-0-0_111073_2018-07-09_final
2018-07-09 11:25:12	ga_ls8c_ard_3-0-0_111074_2018-07-09_final
2018-07-10 10:29:12	ga_ls8c_ard_3-0-0_102073_2018-07-10_final
2018-07-10 10:29:36	ga_ls8c_ard_3-0-0_102074_2018-07-10_final
2018-07-11 09:33:35	ga_ls8c_ard_3-0-0_093073_2018-07-11_final
2018-07-11 09:33:59	ga_ls8c_ard_3-0-0_093074_2018-07-11_final
2018-07-11 11:12:28	ga_ls8c_ard_3-0-0_109073_2018-07-11_final
2018-07-11 11:12:52	ga_ls8c_ard_3-0-0_109074_2018-07-11_final
2018-07-12 10:16:51	ga_ls8c_ard_3-0-0_100073_2018-07-12_final
2018-07-12 10:17:15	ga_ls8c_ard_3-0-0_100074_2018-07-12_final
2018-08-10 09:46:11	ga_ls8c_ard_3-0-0_095073_2018-08-10_final
2018-08-10 11:25:04	ga_ls8c_ard_3-0-0_111073_2018-08-10_final
2018-08-10 11:25:28	ga_ls8c_ard_3-0-0_111074_2018-08-10_final
2018-08-11 10:29:27	ga_ls8c_ard_3-0-0_102073_2018-08-11_final
2018-08-11 10:29:51	ga_ls8c_ard_3-0-0_102074_2018-08-11_final
2018-08-12 09:33:51	ga_ls8c_ard_3-0-0_093073_2018-08-12_final
2018-08-12 11:12:44	ga_ls8c_ard_3-0-0_109073_2018-08-12_final
2018-08-12 11:13:08	ga_ls8c_ard_3-0-0_109074_2018-08-12_final
2018-08-13 10:17:07	ga_ls8c_ard_3-1-0_100073_2018-08-13_final
2018-08-13 10:17:31	ga_ls8c_ard_3-0-0_100074_2018-08-13_final
2018-08-13 11:56:24	ga_ls8c_ard_3-0-0_116074_2018-08-13_final
2018-08-26 09:46:19	ga_ls8c_ard_3-0-0_095073_2018-08-26_final
2018-08-26 11:25:12	ga_ls8c_ard_3-0-0_111073_2018-08-26_final
2018-08-27 10:29:35	ga_ls8c_ard_3-0-0_102073_2018-08-27_final
2018-08-27 10:29:59	ga_ls8c_ard_3-0-0_102074_2018-08-27_final
2018-08-28 09:33:58	ga_ls8c_ard_3-0-0_093073_2018-08-28_final
2018-08-28 09:34:22	ga_ls8c_ard_3-0-0_093074_2018-08-28_final
2018-08-28 11:12:51	ga_ls8c_ard_3-0-0_109073_2018-08-28_final
2018-08-28 11:13:15	ga_ls8c_ard_3-1-0_109074_2018-08-28_final
2018-08-29 10:17:14	ga_ls8c_ard_3-0-0_100073_2018-08-29_final
2018-08-29 10:17:38	ga_ls8c_ard_3-0-0_100074_2018-08-29_final
2018-09-16 10:04:58	ga_ls8c_ard_3-0-0_098073_2018-09-16_final
2018-09-17 10:48:14	ga_ls8c_ard_3-0-0_105073_2018-09-17_final
2018-10-04 09:52:45	ga_ls8c_ard_3-0-0_096073_2018-10-04_final
2018-10-04 11:31:38	ga_ls8c_ard_3-0-0_112073_2018-10-04_final
2018-10-05 10:36:01	ga_ls8c_ard_3-0-0_103073_2018-10-05_final
2018-10-06 09:40:24	ga_ls8c_ard_3-0-0_094073_2018-10-06_final
2018-10-06 09:40:48	ga_ls8c_ard_3-0-0_094074_2018-10-06_final
2018-10-06 11:19:17	ga_ls8c_ard_3-0-0_110073_2018-10-06_final
2018-10-07 10:23:40	ga_ls8c_ard_3-0-0_101073_2018-10-07_final
2018-12-25 09:40:30	ga_ls8c_ard_3-0-0_094073_2018-12-25_final
2018-12-25 11:19:23	ga_ls8c_ard_3-0-0_110073_2018-12-25_final
2018-12-26 10:23:46	ga_ls8c_ard_3-0-0_101073_2018-12-26_final
2019-01-06 10:05:12	ga_ls8c_ard_3-0-0_098073_2019-01-06_final
2019-01-07 10:48:28	ga_ls8c_ard_3-0-0_105073_2019-01-07_final
2023-09-13 09:22:07	ga_ls8c_ard_3-2-1_091073_2023-09-12_final
2023-09-13 11:01:00	ga_ls8c_ard_3-2-1_107073_2023-09-13_final
2023-09-13 11:01:24	ga_ls8c_ard_3-2-1_107074_2023-09-13_final
2023-09-14 10:05:23	ga_ls8c_ard_3-2-1_098073_2023-09-14_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