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
2018-02-08 09:40:28	ga_ls8c_ard_3-0-0_094073_2018-02-08_final
2018-02-08 11:19:21	ga_ls8c_ard_3-0-0_110073_2018-02-08_final
2018-02-09 10:23:43	ga_ls8c_ard_3-0-0_101073_2018-02-09_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
2018-03-10 09:52:36	ga_ls8c_ard_3-0-0_096073_2018-03-10_final
2018-03-10 11:31:29	ga_ls8c_ard_3-0-0_112073_2018-03-10_final
2018-03-11 10:35:51	ga_ls8c_ard_3-0-0_103073_2018-03-11_final
2018-03-12 09:40:13	ga_ls8c_ard_3-0-0_094073_2018-03-12_final
2018-03-12 11:19:06	ga_ls8c_ard_3-0-0_110073_2018-03-12_final
2018-03-13 10:23:28	ga_ls8c_ard_3-0-0_101073_2018-03-13_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
2018-03-26 09:52:29	ga_ls8c_ard_3-0-0_096073_2018-03-26_final
2018-03-26 11:31:22	ga_ls8c_ard_3-0-0_112073_2018-03-26_final
2018-03-27 10:35:44	ga_ls8c_ard_3-0-0_103073_2018-03-27_final
2018-03-28 09:40:06	ga_ls8c_ard_3-0-0_094073_2018-03-28_final
2018-03-28 11:18:59	ga_ls8c_ard_3-0-0_110073_2018-03-28_final
2018-03-29 10:23:21	ga_ls8c_ard_3-0-0_101073_2018-03-29_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
2018-06-30 09:52:02	ga_ls8c_ard_3-0-0_096073_2018-06-30_final
2018-06-30 09:52:26	ga_ls8c_ard_3-0-0_096074_2018-06-30_final
2018-06-30 11:30:55	ga_ls8c_ard_3-0-0_112073_2018-06-30_final
2018-06-30 11:31:19	ga_ls8c_ard_3-0-0_112074_2018-06-30_final
2018-07-01 10:35:18	ga_ls8c_ard_3-0-0_103073_2018-07-01_final
2018-07-01 10:35:42	ga_ls8c_ard_3-0-0_103074_2018-07-01_final
2018-07-02 09:39:41	ga_ls8c_ard_3-0-0_094073_2018-07-02_final
2018-07-02 09:40:05	ga_ls8c_ard_3-0-0_094074_2018-07-02_final
2018-07-02 11:18:34	ga_ls8c_ard_3-0-0_110073_2018-07-02_final
2018-07-02 11:18:58	ga_ls8c_ard_3-0-0_110074_2018-07-02_final
2018-07-03 10:22:57	ga_ls8c_ard_3-0-0_101073_2018-07-03_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
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
2022-09-04 09:59:42	ga_ls8c_ard_3-2-1_097073_2022-09-04_final
2022-09-04 11:38:35	ga_ls8c_ard_3-2-1_113073_2022-09-04_final
2022-09-04 11:38:59	ga_ls8c_ard_3-2-1_113074_2022-09-04_final
2022-09-06 09:47:22	ga_ls8c_ard_3-2-1_095073_2022-09-06_final
2022-09-06 11:26:15	ga_ls8c_ard_3-2-1_111073_2022-09-06_final
2022-09-07 10:30:38	ga_ls8c_ard_3-2-1_102073_2022-09-07_final
2022-09-07 10:31:02	ga_ls8c_ard_3-2-1_102074_2022-09-07_final
2022-09-08 09:35:01	ga_ls8c_ard_3-2-1_093073_2022-09-08_final
2022-09-08 09:35:25	ga_ls8c_ard_3-2-1_093074_2022-09-08_final
2022-09-08 11:13:54	ga_ls8c_ard_3-2-1_109073_2022-09-08_final
2022-09-08 11:14:18	ga_ls8c_ard_3-2-1_109074_2022-09-08_final
2022-09-09 10:18:18	ga_ls8c_ard_3-2-1_100073_2022-09-09_final
2022-09-10 09:22:41	ga_ls8c_ard_3-2-1_091073_2022-09-09_final
2022-09-10 09:23:05	ga_ls8c_ard_3-2-1_091074_2022-09-09_final
2022-09-10 11:01:34	ga_ls8c_ard_3-2-1_107073_2022-09-10_final
2022-09-10 11:01:58	ga_ls8c_ard_3-2-1_107074_2022-09-10_final
2022-09-11 10:05:57	ga_ls8c_ard_3-2-1_098073_2022-09-11_final
2022-09-11 11:45:14	ga_ls8c_ard_3-2-1_114074_2022-09-11_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
2023-05-22 09:33:44	ga_ls8c_ard_3-2-1_093073_2023-05-22_final
2023-05-22 09:34:08	ga_ls8c_ard_3-2-1_093074_2023-05-22_final
2023-05-24 11:00:16	ga_ls8c_ard_3-2-1_107073_2023-05-24_final
2023-05-24 11:00:40	ga_ls8c_ard_3-2-1_107074_2023-05-24_final
2023-05-26 10:47:55	ga_ls8c_ard_3-2-1_105073_2023-05-26_final
2023-05-26 10:48:19	ga_ls8c_ard_3-2-1_105074_2023-05-26_final
2023-05-28 10:35:33	ga_ls8c_ard_3-2-1_103073_2023-05-28_final
2023-05-29 09:39:56	ga_ls8c_ard_3-2-1_094073_2023-05-29_final
2023-05-29 09:40:20	ga_ls8c_ard_3-2-1_094074_2023-05-29_final
2023-05-29 11:18:49	ga_ls8c_ard_3-2-1_110073_2023-05-29_final
2023-05-30 10:23:12	ga_ls8c_ard_3-2-1_101073_2023-05-30_final
2023-05-30 10:23:36	ga_ls8c_ard_3-2-1_101074_2023-05-30_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
2023-06-02 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
2023-09-02 09:40:37	ga_ls8c_ard_3-2-1_094073_2023-09-02_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