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
2014-10-07 10:05:08	ga_ls8c_ard_3-0-0_098072_2014-10-07_final
2014-10-07 10:05:32	ga_ls8c_ard_3-0-0_098073_2014-10-07_final
2014-10-08 10:48:24	ga_ls8c_ard_3-0-0_105072_2014-10-08_final
2014-10-08 10:48:48	ga_ls8c_ard_3-0-0_105073_2014-10-08_final
2014-10-09 09:52:47	ga_ls8c_ard_3-0-0_096072_2014-10-09_final
2014-10-09 09:53:11	ga_ls8c_ard_3-0-0_096073_2014-10-09_final
2014-10-09 11:32:04	ga_ls8c_ard_3-0-0_112073_2014-10-09_final
2014-10-10 10:36:03	ga_ls8c_ard_3-0-0_103072_2014-10-10_final
2014-10-10 10:36:27	ga_ls8c_ard_3-0-0_103073_2014-10-10_final
2014-10-11 09:40:26	ga_ls8c_ard_3-0-0_094072_2014-10-11_final
2014-10-11 09:40:50	ga_ls8c_ard_3-0-0_094073_2014-10-11_final
2014-10-11 11:19:19	ga_ls8c_ard_3-0-0_110072_2014-10-11_final
2014-10-11 11:19:43	ga_ls8c_ard_3-0-0_110073_2014-10-11_final
2014-10-12 10:24:06	ga_ls8c_ard_3-0-0_101073_2014-10-12_final
2014-12-16 09:27:58	ga_ls8c_ard_3-0-0_092072_2014-12-15_final
2014-12-16 09:28:22	ga_ls8c_ard_3-0-0_092073_2014-12-15_final
2014-12-16 11:06:51	ga_ls8c_ard_3-0-0_108072_2014-12-16_final
2014-12-16 11:07:15	ga_ls8c_ard_3-0-0_108073_2014-12-16_final
2014-12-17 10:11:14	ga_ls8c_ard_3-0-0_099072_2014-12-17_final
2014-12-17 10:11:38	ga_ls8c_ard_3-0-0_099073_2014-12-17_final
2014-12-18 10:54:30	ga_ls8c_ard_3-0-0_106072_2014-12-18_final
2014-12-18 10:54:54	ga_ls8c_ard_3-0-0_106073_2014-12-18_final
2017-07-04 09:58:33	ga_ls8c_ard_3-0-0_097072_2017-07-04_final
2017-07-04 09:58:57	ga_ls8c_ard_3-0-0_097073_2017-07-04_final
2017-07-04 11:37:26	ga_ls8c_ard_3-0-0_113072_2017-07-04_final
2017-07-04 11:37:50	ga_ls8c_ard_3-1-0_113073_2017-07-04_final
2017-07-05 10:41:49	ga_ls8c_ard_3-0-0_104072_2017-07-05_final
2017-07-05 10:42:13	ga_ls8c_ard_3-0-0_104073_2017-07-05_final
2017-07-06 09:46:12	ga_ls8c_ard_3-0-0_095072_2017-07-06_final
2017-07-06 09:46:36	ga_ls8c_ard_3-0-0_095073_2017-07-06_final
2017-07-06 11:25:05	ga_ls8c_ard_3-0-0_111072_2017-07-06_final
2017-07-06 11:25:29	ga_ls8c_ard_3-0-0_111073_2017-07-06_final
2017-07-07 10:29:28	ga_ls8c_ard_3-0-0_102072_2017-07-07_final
2017-07-07 10:29:51	ga_ls8c_ard_3-0-0_102073_2017-07-07_final
2017-07-08 09:33:50	ga_ls8c_ard_3-0-0_093072_2017-07-08_final
2017-07-08 09:34:14	ga_ls8c_ard_3-0-0_093073_2017-07-08_final
2017-07-08 11:12:43	ga_ls8c_ard_3-0-0_109072_2017-07-08_final
2017-07-08 11:13:07	ga_ls8c_ard_3-0-0_109073_2017-07-08_final
2017-07-09 10:17:30	ga_ls8c_ard_3-0-0_100073_2017-07-09_final
2017-07-14 10:35:39	ga_ls8c_ard_3-0-0_103072_2017-07-14_final
2017-07-14 10:36:03	ga_ls8c_ard_3-0-0_103073_2017-07-14_final
2017-07-15 09:40:03	ga_ls8c_ard_3-0-0_094072_2017-07-15_final
2017-07-15 09:40:27	ga_ls8c_ard_3-0-0_094073_2017-07-15_final
2017-07-15 11:18:56	ga_ls8c_ard_3-0-0_110072_2017-07-15_final
2017-07-15 11:19:20	ga_ls8c_ard_3-0-0_110073_2017-07-15_final
2017-07-16 10:23:19	ga_ls8c_ard_3-0-0_101072_2017-07-16_final
2017-07-16 10:23:43	ga_ls8c_ard_3-0-0_101073_2017-07-16_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 10:16:33	ga_ls8c_ard_3-0-0_100072_2018-04-23_final
2018-04-23 10:16:56	ga_ls8c_ard_3-0-0_100073_2018-04-23_final
2018-04-24 09:21:19	ga_ls8c_ard_3-0-0_091073_2018-04-23_final
2018-04-24 11:00:12	ga_ls8c_ard_3-0-0_107073_2018-04-24_final
2018-07-14 10:04:06	ga_ls8c_ard_3-1-0_098072_2018-07-14_final
2018-07-14 10:04:30	ga_ls8c_ard_3-1-0_098073_2018-07-14_final
2018-07-15 10:47:22	ga_ls8c_ard_3-0-0_105072_2018-07-15_final
2018-07-15 10:47:46	ga_ls8c_ard_3-0-0_105073_2018-07-15_final
2018-07-16 09:51:45	ga_ls8c_ard_3-0-0_096072_2018-07-16_final
2018-07-16 09:52:09	ga_ls8c_ard_3-0-0_096073_2018-07-16_final
2018-07-16 11:30:39	ga_ls8c_ard_3-0-0_112072_2018-07-16_final
2018-07-16 11:31:02	ga_ls8c_ard_3-0-0_112073_2018-07-16_final
2018-07-20 09:27:04	ga_ls8c_ard_3-0-0_092072_2018-07-19_final
2018-07-20 09:27:28	ga_ls8c_ard_3-0-0_092073_2018-07-19_final
2018-07-20 11:05:57	ga_ls8c_ard_3-0-0_108072_2018-07-20_final
2018-07-20 11:06:21	ga_ls8c_ard_3-0-0_108073_2018-07-20_final
2018-07-21 10:10:20	ga_ls8c_ard_3-0-0_099072_2018-07-21_final
2018-07-21 10:10:44	ga_ls8c_ard_3-0-0_099073_2018-07-21_final
2018-07-21 11:49:37	ga_ls8c_ard_3-0-0_115073_2018-07-21_final
2018-07-22 10:53:36	ga_ls8c_ard_3-0-0_106072_2018-07-22_final
2018-07-22 10:54:00	ga_ls8c_ard_3-0-0_106073_2018-07-22_final
2023-02-04 09:52:58	ga_ls8c_ard_3-2-1_096072_2023-02-04_final
2023-02-04 09:53:22	ga_ls8c_ard_3-2-1_096073_2023-02-04_final
2023-02-04 11:32:15	ga_ls8c_ard_3-2-1_112073_2023-02-04_final
2023-03-01 09:46:51	ga_ls8c_ard_3-2-1_095073_2023-03-01_final
2023-03-01 11:25:45	ga_ls8c_ard_3-2-1_111073_2023-03-01_final
2023-03-02 10:29:43	ga_ls8c_ard_3-2-1_102072_2023-03-02_final
2023-03-02 10:30:07	ga_ls8c_ard_3-2-1_102073_2023-03-02_final
2023-03-03 09:34:05	ga_ls8c_ard_3-2-1_093072_2023-03-03_final
2023-03-03 09:34:29	ga_ls8c_ard_3-2-1_093073_2023-03-03_final
2023-03-03 11:13:22	ga_ls8c_ard_3-2-1_109073_2023-03-03_final
2023-03-04 10:17:21	ga_ls8c_ard_3-2-1_100072_2023-03-04_final
2023-03-04 10:17:44	ga_ls8c_ard_3-2-1_100073_2023-03-04_final
2023-03-19 09:33:57	ga_ls8c_ard_3-2-1_093072_2023-03-19_final
2023-03-19 09:34:21	ga_ls8c_ard_3-2-1_093073_2023-03-19_final
2023-03-19 11:13:14	ga_ls8c_ard_3-2-1_109073_2023-03-19_final
2023-03-20 10:17:36	ga_ls8c_ard_3-2-1_100073_2023-03-20_final
2023-03-23 10:48:27	ga_ls8c_ard_3-2-1_105073_2023-03-23_final
2023-03-24 09:52:49	ga_ls8c_ard_3-2-1_096073_2023-03-24_final
2023-10-15 11:00:44	ga_ls8c_ard_3-2-1_107072_2023-10-15_final
2023-10-15 11:00:44	ga_ls8c_ard_3-2-1_107072_2023-10-15_nrt
2023-10-15 11:01:08	ga_ls8c_ard_3-2-1_107073_2023-10-15_final
2023-10-15 11:01:08	ga_ls8c_ard_3-2-1_107073_2023-10-15_nrt
2023-10-19 10:35:59	ga_ls8c_ard_3-2-1_103072_2023-10-19_final
2023-10-19 10:36:23	ga_ls8c_ard_3-2-1_103073_2023-10-19_final
2023-10-20 09:40:21	ga_ls8c_ard_3-2-1_094072_2023-10-20_final
2023-10-20 09:40:45	ga_ls8c_ard_3-2-1_094073_2023-10-20_final
2023-10-20 11:19:38	ga_ls8c_ard_3-2-1_110073_2023-10-20_final
2023-10-21 10:23:38	ga_ls8c_ard_3-2-1_101072_2023-10-21_final
2023-10-21 10:24:02	ga_ls8c_ard_3-2-1_101073_2023-10-21_final
2023-10-22 09:28:01	ga_ls8c_ard_3-2-1_092072_2023-10-21_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years