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
2018-09-15 09:21:42	ga_ls8c_ard_3-0-0_091073_2018-09-14_final
2018-09-15 09:22:06	ga_ls8c_ard_3-0-0_091074_2018-09-14_final
2018-09-15 11:00:35	ga_ls8c_ard_3-0-0_107073_2018-09-15_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
2018-09-27 09:46:30	ga_ls8c_ard_3-0-0_095073_2018-09-27_final
2018-09-27 11:25:23	ga_ls8c_ard_3-0-0_111073_2018-09-27_final
2018-09-27 11:25:47	ga_ls8c_ard_3-0-0_111074_2018-09-27_final
2018-09-28 10:29:46	ga_ls8c_ard_3-0-0_102073_2018-09-28_final
2018-09-29 09:34:10	ga_ls8c_ard_3-0-0_093073_2018-09-29_final
2018-09-29 11:13:03	ga_ls8c_ard_3-0-0_109073_2018-09-29_final
2018-09-30 10:17:26	ga_ls8c_ard_3-0-0_100073_2018-09-30_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
2018-10-13 09:46:38	ga_ls8c_ard_3-0-0_095073_2018-10-13_final
2018-10-13 11:25:31	ga_ls8c_ard_3-0-0_111073_2018-10-13_final
2018-10-14 10:29:54	ga_ls8c_ard_3-0-0_102073_2018-10-14_final
2018-10-15 09:34:17	ga_ls8c_ard_3-0-0_093073_2018-10-15_final
2018-10-15 11:13:10	ga_ls8c_ard_3-0-0_109073_2018-10-15_final
2018-10-16 10:17:33	ga_ls8c_ard_3-0-0_100073_2018-10-16_final
2018-10-17 09:21:56	ga_ls8c_ard_3-0-0_091073_2018-10-16_final
2018-10-17 11:00:49	ga_ls8c_ard_3-0-0_107073_2018-10-17_final
2018-10-30 10:29:58	ga_ls8c_ard_3-0-0_102073_2018-10-30_final
2018-10-31 09:34:21	ga_ls8c_ard_3-0-0_093073_2018-10-31_final
2018-10-31 11:13:14	ga_ls8c_ard_3-0-0_109073_2018-10-31_final
2018-11-01 10:17:37	ga_ls8c_ard_3-0-0_100073_2018-11-01_final
2018-11-30 09:46:43	ga_ls8c_ard_3-0-0_095073_2018-11-30_final
2018-11-30 11:25:36	ga_ls8c_ard_3-0-0_111073_2018-11-30_final
2018-12-01 10:29:59	ga_ls8c_ard_3-0-0_102073_2018-12-01_final
2018-12-02 09:34:21	ga_ls8c_ard_3-0-0_093073_2018-12-02_final
2018-12-02 11:13:14	ga_ls8c_ard_3-0-0_109073_2018-12-02_final
2018-12-03 10:17:37	ga_ls8c_ard_3-0-0_100073_2018-12-03_final
2018-12-16 09:46:40	ga_ls8c_ard_3-0-0_095073_2018-12-16_final
2018-12-16 11:25:33	ga_ls8c_ard_3-0-0_111073_2018-12-16_final
2018-12-17 10:29:56	ga_ls8c_ard_3-0-0_102073_2018-12-17_final
2018-12-18 09:34:19	ga_ls8c_ard_3-0-0_093073_2018-12-18_final
2018-12-18 11:13:12	ga_ls8c_ard_3-0-0_109073_2018-12-18_final
2018-12-19 10:17:35	ga_ls8c_ard_3-0-0_100073_2018-12-19_final
2018-12-23 09:52:52	ga_ls8c_ard_3-0-0_096073_2018-12-23_final
2018-12-23 11:31:45	ga_ls8c_ard_3-0-0_112073_2018-12-23_final
2018-12-24 10:36:07	ga_ls8c_ard_3-0-0_103073_2018-12-24_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
2023-07-28 10:05:09	ga_ls8c_ard_3-2-1_098073_2023-07-28_final
2023-07-28 10:05:33	ga_ls8c_ard_3-2-1_098074_2023-07-28_final
2023-07-29 10:48:25	ga_ls8c_ard_3-2-1_105073_2023-07-29_final
2023-07-30 09:52:48	ga_ls8c_ard_3-2-1_096073_2023-07-30_final
2023-07-30 09:53:12	ga_ls8c_ard_3-2-1_096074_2023-07-30_final
2023-07-30 11:31:41	ga_ls8c_ard_3-2-1_112073_2023-07-30_final
2023-07-31 10:36:05	ga_ls8c_ard_3-2-1_103073_2023-07-31_final
2023-08-03 09:28:07	ga_ls8c_ard_3-2-1_092073_2023-08-02_final
2023-08-03 09:28:31	ga_ls8c_ard_3-2-1_092074_2023-08-02_final
2023-08-05 10:54:39	ga_ls8c_ard_3-2-1_106073_2023-08-05_final
2023-08-06 09:59:01	ga_ls8c_ard_3-2-1_097073_2023-08-06_final
2023-08-06 09:59:25	ga_ls8c_ard_3-2-1_097074_2023-08-06_final
2023-08-06 11:37:54	ga_ls8c_ard_3-2-1_113073_2023-08-06_final
2023-08-07 10:42:17	ga_ls8c_ard_3-2-1_104073_2023-08-07_final
2023-08-08 09:46:40	ga_ls8c_ard_3-2-1_095073_2023-08-08_final
2023-08-08 11:25:33	ga_ls8c_ard_3-2-1_111073_2023-08-08_final
2023-08-09 10:29:55	ga_ls8c_ard_3-2-1_102073_2023-08-09_final
2023-08-12 09:21:57	ga_ls8c_ard_3-2-1_091073_2023-08-11_final
2023-08-12 11:00:50	ga_ls8c_ard_3-2-1_107073_2023-08-12_final
2023-08-13 10:05:14	ga_ls8c_ard_3-2-1_098073_2023-08-13_final
2023-08-14 10:48:30	ga_ls8c_ard_3-2-1_105073_2023-08-14_final
2023-08-16 10:36:10	ga_ls8c_ard_3-2-1_103073_2023-08-16_final
2023-08-17 09:40:34	ga_ls8c_ard_3-2-1_094073_2023-08-17_final
2023-08-21 10:54:46	ga_ls8c_ard_3-2-1_106073_2023-08-21_final
2023-08-22 09:59:09	ga_ls8c_ard_3-2-1_097073_2023-08-22_final
2023-08-22 09:59:33	ga_ls8c_ard_3-2-1_097074_2023-08-22_final
2023-08-22 11:38:02	ga_ls8c_ard_3-2-1_113073_2023-08-22_final
2023-08-24 11:25:41	ga_ls8c_ard_3-2-1_111073_2023-08-24_final
2023-08-25 10:30:04	ga_ls8c_ard_3-2-1_102073_2023-08-25_final
2023-08-26 09:34:26	ga_ls8c_ard_3-2-1_093073_2023-08-26_final
2023-08-26 09:34:50	ga_ls8c_ard_3-2-1_093074_2023-08-26_final
2023-08-26 11:13:19	ga_ls8c_ard_3-2-1_109073_2023-08-26_final
2023-08-27 10:17:42	ga_ls8c_ard_3-2-1_100073_2023-08-27_final
2023-08-28 09:22:05	ga_ls8c_ard_3-2-1_091073_2023-08-27_final
2023-08-28 11:00:58	ga_ls8c_ard_3-2-1_107073_2023-08-28_final
2023-08-29 10:05:21	ga_ls8c_ard_3-2-1_098073_2023-08-29_final
2023-08-30 09:10:07	ga_ls8c_ard_3-2-1_089074_2023-08-29_final
2023-08-30 10:48:36	ga_ls8c_ard_3-2-1_105073_2023-08-30_final
2023-08-31 09:52:59	ga_ls8c_ard_3-2-1_096073_2023-08-31_final
2023-08-31 11:31:52	ga_ls8c_ard_3-2-1_112073_2023-08-31_final
2023-09-01 10:36:14	ga_ls8c_ard_3-2-1_103073_2023-09-01_final
2023-09-04 09:28:14	ga_ls8c_ard_3-2-1_092073_2023-09-03_final
2023-09-04 11:07:07	ga_ls8c_ard_3-2-1_108073_2023-09-04_final
2023-09-05 10:11:30	ga_ls8c_ard_3-2-1_099073_2023-09-05_final
2023-09-06 09:16:16	ga_ls8c_ard_3-2-1_090074_2023-09-05_final
2023-09-06 10:54:45	ga_ls8c_ard_3-2-1_106073_2023-09-06_final
2023-09-07 09:59:07	ga_ls8c_ard_3-2-1_097073_2023-09-07_final
2023-09-07 11:38:01	ga_ls8c_ard_3-2-1_113073_2023-09-07_final
2023-09-08 10:42:24	ga_ls8c_ard_3-2-1_104073_2023-09-08_final
2023-09-09 09:46:48	ga_ls8c_ard_3-2-1_095073_2023-09-09_final
2023-09-09 11:25:41	ga_ls8c_ard_3-2-1_111073_2023-09-09_final
2023-09-09 11:26:05	ga_ls8c_ard_3-2-1_111074_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