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
2018-01-30 09:46:42	ga_ls8c_ard_3-0-0_095073_2018-01-30_final
2018-01-30 11:25:35	ga_ls8c_ard_3-0-0_111073_2018-01-30_final
2018-01-30 11:25:59	ga_ls8c_ard_3-0-0_111074_2018-01-30_final
2018-01-31 10:29:57	ga_ls8c_ard_3-0-0_102073_2018-01-31_final
2018-02-01 09:34:19	ga_ls8c_ard_3-0-0_093073_2018-02-01_final
2018-02-01 11:13:12	ga_ls8c_ard_3-0-0_109073_2018-02-01_final
2018-02-02 10:17:34	ga_ls8c_ard_3-0-0_100073_2018-02-02_final
2018-02-15 09:46:37	ga_ls8c_ard_3-0-0_095073_2018-02-15_final
2018-02-15 11:25:30	ga_ls8c_ard_3-0-0_111073_2018-02-15_final
2018-02-16 10:29:52	ga_ls8c_ard_3-0-0_102073_2018-02-16_final
2018-02-17 09:34:14	ga_ls8c_ard_3-0-0_093073_2018-02-17_final
2018-02-17 11:13:07	ga_ls8c_ard_3-0-0_109073_2018-02-17_final
2018-02-18 10:17:30	ga_ls8c_ard_3-0-0_100073_2018-02-18_final
2018-02-22 09:52:45	ga_ls8c_ard_3-0-0_096073_2018-02-22_final
2018-02-22 11:31:38	ga_ls8c_ard_3-0-0_112073_2018-02-22_final
2018-02-23 10:36:00	ga_ls8c_ard_3-0-0_103073_2018-02-23_final
2018-02-24 09:40:22	ga_ls8c_ard_3-0-0_094073_2018-02-24_final
2018-02-24 11:19:15	ga_ls8c_ard_3-0-0_110073_2018-02-24_final
2018-02-25 10:23:37	ga_ls8c_ard_3-0-0_101073_2018-02-25_final
2018-03-03 09:46:29	ga_ls8c_ard_3-0-0_095073_2018-03-03_final
2018-03-03 11:25:22	ga_ls8c_ard_3-0-0_111073_2018-03-03_final
2018-03-04 10:29:44	ga_ls8c_ard_3-0-0_102073_2018-03-04_final
2018-03-05 09:34:07	ga_ls8c_ard_3-0-0_093073_2018-03-05_final
2018-03-05 11:13:00	ga_ls8c_ard_3-0-0_109073_2018-03-05_final
2018-03-06 10:17:22	ga_ls8c_ard_3-0-0_100073_2018-03-06_final
2018-03-19 09:46:21	ga_ls8c_ard_3-0-0_095073_2018-03-19_final
2018-03-19 11:25:14	ga_ls8c_ard_3-0-0_111073_2018-03-19_final
2018-03-20 10:29:36	ga_ls8c_ard_3-0-0_102073_2018-03-20_final
2018-03-21 09:33:58	ga_ls8c_ard_3-0-0_093073_2018-03-21_final
2018-03-21 11:12:51	ga_ls8c_ard_3-0-0_109073_2018-03-21_final
2018-03-22 10:17:13	ga_ls8c_ard_3-0-0_100073_2018-03-22_final
2018-04-04 09:46:13	ga_ls8c_ard_3-0-0_095073_2018-04-04_final
2018-04-04 11:25:07	ga_ls8c_ard_3-0-0_111073_2018-04-04_final
2018-04-05 10:29:29	ga_ls8c_ard_3-0-0_102073_2018-04-05_final
2018-04-06 09:33:51	ga_ls8c_ard_3-0-0_093073_2018-04-06_final
2018-04-06 11:12:44	ga_ls8c_ard_3-0-0_109073_2018-04-06_final
2018-04-07 10:17:06	ga_ls8c_ard_3-0-0_100073_2018-04-07_final
2018-04-11 09:52:20	ga_ls8c_ard_3-0-0_096073_2018-04-11_final
2018-04-11 11:31:13	ga_ls8c_ard_3-0-0_112073_2018-04-11_final
2018-04-12 10:35:35	ga_ls8c_ard_3-0-0_103073_2018-04-12_final
2018-04-13 09:39:58	ga_ls8c_ard_3-0-0_094073_2018-04-13_final
2018-04-13 11:18:51	ga_ls8c_ard_3-0-0_110073_2018-04-13_final
2018-04-14 10:23:13	ga_ls8c_ard_3-0-0_101073_2018-04-14_final
2018-04-20 09:46:04	ga_ls8c_ard_3-0-0_095073_2018-04-20_final
2018-04-20 11:24:57	ga_ls8c_ard_3-0-0_111073_2018-04-20_final
2018-04-21 10:29:19	ga_ls8c_ard_3-0-0_102073_2018-04-21_final
2018-04-22 09:33:41	ga_ls8c_ard_3-0-0_093073_2018-04-22_final
2018-04-22 11:12:34	ga_ls8c_ard_3-0-0_109073_2018-04-22_final
2018-04-23 10:16:56	ga_ls8c_ard_3-0-0_100073_2018-04-23_final
2018-05-07 10:29:10	ga_ls8c_ard_3-0-0_102073_2018-05-07_final
2018-05-08 09:33:32	ga_ls8c_ard_3-0-0_093073_2018-05-08_final
2018-05-08 11:12:25	ga_ls8c_ard_3-0-0_109073_2018-05-08_final
2018-05-09 10:16:47	ga_ls8c_ard_3-0-0_100073_2018-05-09_final
2018-09-16 10:04:58	ga_ls8c_ard_3-0-0_098073_2018-09-16_final
2018-09-16 10:05:22	ga_ls8c_ard_3-0-0_098074_2018-09-16_final
2018-09-17 09:09:45	ga_ls8c_ard_3-0-0_089074_2018-09-16_final
2018-09-17 10:48:14	ga_ls8c_ard_3-0-0_105073_2018-09-17_final
2018-09-17 10:48:38	ga_ls8c_ard_3-0-0_105074_2018-09-17_final
2019-01-06 10:05:12	ga_ls8c_ard_3-0-0_098073_2019-01-06_final
2019-01-06 10:05:36	ga_ls8c_ard_3-0-0_098074_2019-01-06_final
2019-01-07 10:48:28	ga_ls8c_ard_3-0-0_105073_2019-01-07_final
2023-04-29 09:27:45	ga_ls8c_ard_3-2-1_092073_2023-04-28_final
2023-04-29 11:06:38	ga_ls8c_ard_3-2-1_108073_2023-04-29_final
2023-04-30 10:11:00	ga_ls8c_ard_3-2-1_099073_2023-04-30_final
2023-05-31 09:27:34	ga_ls8c_ard_3-2-1_092073_2023-05-30_final
2023-05-31 09:27:58	ga_ls8c_ard_3-2-1_092074_2023-05-30_final
2023-05-31 11:06:27	ga_ls8c_ard_3-2-1_108073_2023-05-31_final
2023-05-31 11:06:51	ga_ls8c_ard_3-2-1_108074_2023-05-31_final
2023-06-01 10:10:50	ga_ls8c_ard_3-2-1_099073_2023-06-01_final
2023-06-01 10:11:14	ga_ls8c_ard_3-2-1_099074_2023-06-01_final
2023-06-01 11:50:07	ga_ls8c_ard_3-2-1_115074_2023-06-01_final
2023-06-02 09:15:36	ga_ls8c_ard_3-2-1_090074_2023-06-01_final
2023-06-02 10:54:06	ga_ls8c_ard_3-2-1_106073_2023-06-02_final
2023-06-02 10:54:29	ga_ls8c_ard_3-2-1_106074_2023-06-02_final
2023-07-04 10:54:26	ga_ls8c_ard_3-2-1_106073_2023-07-04_final
2023-07-04 10:54:50	ga_ls8c_ard_3-2-1_106074_2023-07-04_final
2023-07-05 09:58:49	ga_ls8c_ard_3-2-1_097073_2023-07-05_final
2023-07-05 09:59:13	ga_ls8c_ard_3-2-1_097074_2023-07-05_final
2023-07-05 11:37:42	ga_ls8c_ard_3-2-1_113073_2023-07-05_final
2023-07-05 11:38:06	ga_ls8c_ard_3-2-1_113074_2023-07-05_final
2023-07-07 11:25:21	ga_ls8c_ard_3-2-1_111073_2023-07-07_final
2023-07-07 11:25:45	ga_ls8c_ard_3-2-1_111074_2023-07-07_final
2023-07-08 10:29:44	ga_ls8c_ard_3-2-1_102073_2023-07-08_final
2023-07-08 10:30:08	ga_ls8c_ard_3-2-1_102074_2023-07-08_final
2023-07-09 09:34:08	ga_ls8c_ard_3-2-1_093073_2023-07-09_final
2023-07-09 09:34:31	ga_ls8c_ard_3-2-1_093074_2023-07-09_final
2023-07-11 09:21:47	ga_ls8c_ard_3-2-1_091073_2023-07-10_final
2023-07-11 09:22:11	ga_ls8c_ard_3-2-1_091074_2023-07-10_final
2023-07-11 11:00:40	ga_ls8c_ard_3-2-1_107073_2023-07-11_final
2023-07-13 10:48:18	ga_ls8c_ard_3-2-1_105073_2023-07-13_final
2023-07-13 10:48:42	ga_ls8c_ard_3-2-1_105074_2023-07-13_final
2023-07-14 09:52:41	ga_ls8c_ard_3-2-1_096073_2023-07-14_final
2023-07-14 09:53:05	ga_ls8c_ard_3-2-1_096074_2023-07-14_final
2023-07-14 11:31:34	ga_ls8c_ard_3-2-1_112073_2023-07-14_final
2023-07-14 11:31:58	ga_ls8c_ard_3-2-1_112074_2023-07-14_final
2023-09-08 10:42:24	ga_ls8c_ard_3-2-1_104073_2023-09-08_final
2023-09-08 10:42:48	ga_ls8c_ard_3-2-1_104074_2023-09-08_final
2023-09-09 09:46:48	ga_ls8c_ard_3-2-1_095073_2023-09-09_final
2023-09-09 09:47:12	ga_ls8c_ard_3-2-1_095074_2023-09-09_final
2023-09-09 11:25:41	ga_ls8c_ard_3-2-1_111073_2023-09-09_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