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
2018-02-06 09:52:50	ga_ls8c_ard_3-0-0_096073_2018-02-06_final
2018-02-06 11:31:43	ga_ls8c_ard_3-0-0_112073_2018-02-06_final
2018-02-07 10:35:42	ga_ls8c_ard_3-0-0_103072_2018-02-07_final
2018-02-07 10:36:06	ga_ls8c_ard_3-0-0_103073_2018-02-07_final
2018-02-08 09:40:04	ga_ls8c_ard_3-0-0_094072_2018-02-08_final
2018-02-08 09:40:28	ga_ls8c_ard_3-0-0_094073_2018-02-08_final
2018-02-08 11:18:57	ga_ls8c_ard_3-0-0_110072_2018-02-08_final
2018-02-08 11:19:21	ga_ls8c_ard_3-0-0_110073_2018-02-08_final
2018-02-09 10:23:20	ga_ls8c_ard_3-0-0_101072_2018-02-09_final
2018-02-09 10:23:43	ga_ls8c_ard_3-0-0_101073_2018-02-09_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 09:39:58	ga_ls8c_ard_3-0-0_094072_2018-02-24_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 10:23:13	ga_ls8c_ard_3-1-0_101072_2018-02-25_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 11:31:05	ga_ls8c_ard_3-0-0_112072_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 10:23:04	ga_ls8c_ard_3-0-0_101072_2018-03-13_final
2018-03-13 10:23:28	ga_ls8c_ard_3-0-0_101073_2018-03-13_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 09:39:42	ga_ls8c_ard_3-0-0_094072_2018-03-28_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 10:22:57	ga_ls8c_ard_3-0-0_101072_2018-03-29_final
2018-03-29 10:23:21	ga_ls8c_ard_3-0-0_101073_2018-03-29_final
2018-09-16 10:04:34	ga_ls8c_ard_3-0-0_098072_2018-09-16_final
2018-09-16 10:04:58	ga_ls8c_ard_3-0-0_098073_2018-09-16_final
2018-09-17 10:47:50	ga_ls8c_ard_3-0-0_105072_2018-09-17_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
2023-01-04 10:36:40	ga_ls8c_ard_3-2-1_103073_2023-01-04_final
2023-01-05 09:41:02	ga_ls8c_ard_3-2-1_094073_2023-01-05_final
2023-01-06 10:23:54	ga_ls8c_ard_3-2-1_101072_2023-01-06_final
2023-01-06 10:24:18	ga_ls8c_ard_3-2-1_101073_2023-01-06_final
2023-01-07 09:28:40	ga_ls8c_ard_3-2-1_092073_2023-01-06_final
2023-04-14 10:11:05	ga_ls8c_ard_3-2-1_099073_2023-04-14_final
2023-04-15 10:54:20	ga_ls8c_ard_3-2-1_106073_2023-04-15_final
2023-05-06 09:33:51	ga_ls8c_ard_3-2-1_093073_2023-05-06_final
2023-05-08 11:00:20	ga_ls8c_ard_3-2-1_107073_2023-05-08_final
2023-05-09 10:04:42	ga_ls8c_ard_3-2-1_098073_2023-05-09_final
2023-05-10 10:47:56	ga_ls8c_ard_3-2-1_105073_2023-05-10_final
2023-05-11 09:52:18	ga_ls8c_ard_3-2-1_096073_2023-05-11_final
2023-05-11 11:31:11	ga_ls8c_ard_3-2-1_112073_2023-05-11_final
2023-05-13 11:18:48	ga_ls8c_ard_3-2-1_110073_2023-05-13_final
2023-05-14 10:23:10	ga_ls8c_ard_3-2-1_101073_2023-05-14_final
2023-05-15 09:27:32	ga_ls8c_ard_3-2-1_092073_2023-05-14_final
2023-05-15 11:06:25	ga_ls8c_ard_3-2-1_108073_2023-05-15_final
2023-05-16 10:10:47	ga_ls8c_ard_3-2-1_099073_2023-05-16_final
2023-05-18 11:36:54	ga_ls8c_ard_3-2-1_113072_2023-05-18_final
2023-05-18 11:37:18	ga_ls8c_ard_3-2-1_113073_2023-05-18_final
2023-05-27 09:52:18	ga_ls8c_ard_3-2-1_096073_2023-05-27_final
2023-05-27 11:30:47	ga_ls8c_ard_3-2-1_112072_2023-05-27_final
2023-05-27 11:31:11	ga_ls8c_ard_3-2-1_112073_2023-05-27_final
2023-05-28 10:35:09	ga_ls8c_ard_3-2-1_103072_2023-05-28_final
2023-05-28 10:35:33	ga_ls8c_ard_3-2-1_103073_2023-05-28_final
2023-05-29 09:39:32	ga_ls8c_ard_3-2-1_094072_2023-05-29_final
2023-05-29 09:39:56	ga_ls8c_ard_3-2-1_094073_2023-05-29_final
2023-05-29 11:18:25	ga_ls8c_ard_3-2-1_110072_2023-05-29_final
2023-05-29 11:18:49	ga_ls8c_ard_3-2-1_110073_2023-05-29_final
2023-05-30 10:22:48	ga_ls8c_ard_3-2-1_101072_2023-05-30_final
2023-05-30 10:23:12	ga_ls8c_ard_3-2-1_101073_2023-05-30_final
2023-05-31 09:27:10	ga_ls8c_ard_3-2-1_092072_2023-05-30_final
2023-05-31 09:27:34	ga_ls8c_ard_3-2-1_092073_2023-05-30_final
2023-05-31 11:06:03	ga_ls8c_ard_3-2-1_108072_2023-05-31_final
2023-05-31 11:06:27	ga_ls8c_ard_3-2-1_108073_2023-05-31_final
2023-06-01 10:10:26	ga_ls8c_ard_3-2-1_099072_2023-06-01_final
2023-06-01 10:10:50	ga_ls8c_ard_3-2-1_099073_2023-06-01_final
2023-06-02 10:53:42	ga_ls8c_ard_3-2-1_106072_2023-06-02_final
2023-06-02 10:54:06	ga_ls8c_ard_3-2-1_106073_2023-06-02_final
2023-06-05 09:45:46	ga_ls8c_ard_3-2-1_095072_2023-06-05_final
2023-06-05 09:46:10	ga_ls8c_ard_3-2-1_095073_2023-06-05_final
2023-06-05 11:24:39	ga_ls8c_ard_3-2-1_111072_2023-06-05_final
2023-06-05 11:25:03	ga_ls8c_ard_3-2-1_111073_2023-06-05_final
2023-06-06 10:29:02	ga_ls8c_ard_3-2-1_102072_2023-06-06_final
2023-06-06 10:29:26	ga_ls8c_ard_3-2-1_102073_2023-06-06_final
2023-06-07 09:33:26	ga_ls8c_ard_3-2-1_093072_2023-06-07_final
2023-06-07 09:33:50	ga_ls8c_ard_3-2-1_093073_2023-06-07_final
2023-06-07 11:12:19	ga_ls8c_ard_3-2-1_109072_2023-06-07_final
2023-06-07 11:12:43	ga_ls8c_ard_3-2-1_109073_2023-06-07_final
2023-06-08 10:16:42	ga_ls8c_ard_3-2-1_100072_2023-06-08_final
2023-06-08 10:17:06	ga_ls8c_ard_3-2-1_100073_2023-06-08_final
2023-06-09 09:21:05	ga_ls8c_ard_3-2-1_091072_2023-06-08_final
2023-06-09 09:21:29	ga_ls8c_ard_3-2-1_091073_2023-06-08_final
2023-06-09 10:59:59	ga_ls8c_ard_3-2-1_107072_2023-06-09_final
2023-06-09 11:00:22	ga_ls8c_ard_3-2-1_107073_2023-06-09_final
2023-06-10 10:04:22	ga_ls8c_ard_3-2-1_098072_2023-06-10_final
2023-06-10 10:04:46	ga_ls8c_ard_3-2-1_098073_2023-06-10_final
2023-06-11 10:47:38	ga_ls8c_ard_3-2-1_105072_2023-06-11_final
2023-06-11 10:48:02	ga_ls8c_ard_3-2-1_105073_2023-06-11_final
2023-06-12 09:52:01	ga_ls8c_ard_3-2-1_096072_2023-06-12_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