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
2018-02-24 11:17:15	ga_ls8c_ard_3-0-0_110068_2018-02-24_final
2018-02-24 11:17:39	ga_ls8c_ard_3-0-0_110069_2018-02-24_final
2018-02-24 11:18:03	ga_ls8c_ard_3-0-0_110070_2018-02-24_final
2018-02-24 11:18:27	ga_ls8c_ard_3-0-0_110071_2018-02-24_final
2018-02-24 11:18:51	ga_ls8c_ard_3-0-0_110072_2018-02-24_final
2018-02-24 11:19:15	ga_ls8c_ard_3-0-0_110073_2018-02-24_final
2018-02-24 11:19:39	ga_ls8c_ard_3-0-0_110074_2018-02-24_final
2018-03-12 11:17:07	ga_ls8c_ard_3-0-0_110068_2018-03-12_final
2018-03-12 11:17:30	ga_ls8c_ard_3-0-0_110069_2018-03-12_final
2018-03-12 11:17:54	ga_ls8c_ard_3-0-0_110070_2018-03-12_final
2018-03-12 11:18:18	ga_ls8c_ard_3-0-0_110071_2018-03-12_final
2018-03-12 11:18:42	ga_ls8c_ard_3-0-0_110072_2018-03-12_final
2018-03-12 11:19:06	ga_ls8c_ard_3-0-0_110073_2018-03-12_final
2018-03-12 11:19:30	ga_ls8c_ard_3-0-0_110074_2018-03-12_final
2018-10-06 11:17:17	ga_ls8c_ard_3-0-0_110068_2018-10-06_final
2018-10-06 11:17:41	ga_ls8c_ard_3-0-0_110069_2018-10-06_final
2018-10-06 11:18:05	ga_ls8c_ard_3-0-0_110070_2018-10-06_final
2018-10-06 11:18:29	ga_ls8c_ard_3-0-0_110071_2018-10-06_final
2018-10-06 11:18:53	ga_ls8c_ard_3-0-0_110072_2018-10-06_final
2018-10-06 11:19:17	ga_ls8c_ard_3-0-0_110073_2018-10-06_final
2018-10-06 11:19:41	ga_ls8c_ard_3-0-0_110074_2018-10-06_final
2018-10-22 11:17:23	ga_ls8c_ard_3-0-0_110068_2018-10-22_final
2018-10-22 11:17:47	ga_ls8c_ard_3-0-0_110069_2018-10-22_final
2018-10-22 11:18:11	ga_ls8c_ard_3-0-0_110070_2018-10-22_final
2018-10-22 11:18:35	ga_ls8c_ard_3-0-0_110071_2018-10-22_final
2018-10-22 11:18:59	ga_ls8c_ard_3-0-0_110072_2018-10-22_final
2018-10-22 11:19:23	ga_ls8c_ard_3-0-0_110073_2018-10-22_final
2018-10-22 11:19:47	ga_ls8c_ard_3-0-0_110074_2018-10-22_final
2018-11-07 11:17:26	ga_ls8c_ard_3-0-0_110068_2018-11-07_final
2018-11-07 11:17:50	ga_ls8c_ard_3-0-0_110069_2018-11-07_final
2018-11-07 11:18:14	ga_ls8c_ard_3-0-0_110070_2018-11-07_final
2018-11-07 11:18:38	ga_ls8c_ard_3-0-0_110071_2018-11-07_final
2018-11-07 11:19:02	ga_ls8c_ard_3-0-0_110072_2018-11-07_final
2018-11-07 11:19:26	ga_ls8c_ard_3-0-0_110073_2018-11-07_final
2018-11-07 11:19:50	ga_ls8c_ard_3-0-0_110074_2018-11-07_final
2018-12-25 11:17:23	ga_ls8c_ard_3-0-0_110068_2018-12-25_final
2018-12-25 11:17:47	ga_ls8c_ard_3-0-0_110069_2018-12-25_final
2018-12-25 11:18:11	ga_ls8c_ard_3-0-0_110070_2018-12-25_final
2018-12-25 11:18:35	ga_ls8c_ard_3-0-0_110071_2018-12-25_final
2018-12-25 11:18:59	ga_ls8c_ard_3-0-0_110072_2018-12-25_final
2018-12-25 11:19:23	ga_ls8c_ard_3-0-0_110073_2018-12-25_final
2018-12-25 11:19:47	ga_ls8c_ard_3-0-0_110074_2018-12-25_final
2023-06-05 11:23:03	ga_ls8c_ard_3-2-1_111068_2023-06-05_final
2023-06-05 11:23:27	ga_ls8c_ard_3-2-1_111069_2023-06-05_final
2023-06-07 11:12:43	ga_ls8c_ard_3-2-1_109073_2023-06-07_final
2023-06-07 11:13:07	ga_ls8c_ard_3-2-1_109074_2023-06-07_final
2023-06-07 11:13:31	ga_ls8c_ard_3-2-1_109075_2023-06-07_final
2023-06-07 11:13:55	ga_ls8c_ard_3-2-1_109076_2023-06-07_final
2023-06-07 11:14:18	ga_ls8c_ard_3-2-1_109077_2023-06-07_final
2023-06-07 11:14:42	ga_ls8c_ard_3-2-1_109078_2023-06-07_final
2023-06-09 11:04:22	ga_ls8c_ard_3-2-1_107083_2023-06-09_final
2023-06-09 11:04:46	ga_ls8c_ard_3-2-1_107084_2023-06-09_final
2023-06-14 11:17:22	ga_ls8c_ard_3-2-1_110069_2023-06-14_final
2023-06-14 11:17:46	ga_ls8c_ard_3-2-1_110070_2023-06-14_final
2023-06-14 11:18:10	ga_ls8c_ard_3-2-1_110071_2023-06-14_final
2023-06-14 11:18:34	ga_ls8c_ard_3-2-1_110072_2023-06-14_final
2023-06-14 11:18:58	ga_ls8c_ard_3-2-1_110073_2023-06-14_final
2023-06-14 11:19:21	ga_ls8c_ard_3-2-1_110074_2023-06-14_final
2023-06-16 11:08:12	ga_ls8c_ard_3-2-1_108077_2023-06-16_final
2023-06-16 11:08:36	ga_ls8c_ard_3-2-1_108078_2023-06-16_final
2023-06-16 11:09:00	ga_ls8c_ard_3-2-1_108079_2023-06-16_final
2023-06-16 11:09:24	ga_ls8c_ard_3-2-1_108080_2023-06-16_final
2023-06-16 11:09:48	ga_ls8c_ard_3-2-1_108081_2023-06-16_final
2023-06-16 11:10:12	ga_ls8c_ard_3-2-1_108082_2023-06-16_final
2023-06-16 11:10:36	ga_ls8c_ard_3-2-1_108083_2023-06-16_final
2023-06-21 11:23:10	ga_ls8c_ard_3-2-1_111068_2023-06-21_final
2023-06-21 11:23:33	ga_ls8c_ard_3-2-1_111069_2023-06-21_final
2023-06-23 11:12:48	ga_ls8c_ard_3-2-1_109073_2023-06-23_final
2023-06-23 11:13:12	ga_ls8c_ard_3-2-1_109074_2023-06-23_final
2023-06-23 11:13:36	ga_ls8c_ard_3-2-1_109075_2023-06-23_final
2023-06-23 11:14:00	ga_ls8c_ard_3-2-1_109076_2023-06-23_final
2023-06-23 11:14:24	ga_ls8c_ard_3-2-1_109077_2023-06-23_final
2023-06-23 11:14:48	ga_ls8c_ard_3-2-1_109078_2023-06-23_final
2023-06-23 11:15:11	ga_ls8c_ard_3-2-1_109079_2023-06-23_final
2023-06-25 11:03:40	ga_ls8c_ard_3-2-1_107081_2023-06-25_final
2023-06-25 11:04:04	ga_ls8c_ard_3-2-1_107082_2023-06-25_final
2023-06-25 11:04:28	ga_ls8c_ard_3-2-1_107083_2023-06-25_final
2023-06-25 11:04:52	ga_ls8c_ard_3-2-1_107084_2023-06-25_final
2023-07-07 11:23:22	ga_ls8c_ard_3-2-1_111068_2023-07-07_final
2023-07-07 11:23:46	ga_ls8c_ard_3-2-1_111069_2023-07-07_final
2023-07-09 11:13:01	ga_ls8c_ard_3-2-1_109073_2023-07-09_final
2023-07-09 11:13:25	ga_ls8c_ard_3-2-1_109074_2023-07-09_final
2023-07-09 11:13:48	ga_ls8c_ard_3-2-1_109075_2023-07-09_final
2023-07-09 11:14:12	ga_ls8c_ard_3-2-1_109076_2023-07-09_final
2023-07-09 11:14:36	ga_ls8c_ard_3-2-1_109077_2023-07-09_final
2023-07-09 11:15:00	ga_ls8c_ard_3-2-1_109078_2023-07-09_final
2023-07-11 11:03:51	ga_ls8c_ard_3-2-1_107081_2023-07-11_final
2023-07-11 11:04:15	ga_ls8c_ard_3-2-1_107082_2023-07-11_final
2023-07-11 11:04:39	ga_ls8c_ard_3-2-1_107083_2023-07-11_final
2023-07-11 11:05:03	ga_ls8c_ard_3-2-1_107084_2023-07-11_final
2023-07-16 11:17:37	ga_ls8c_ard_3-2-1_110069_2023-07-16_final
2023-07-16 11:18:01	ga_ls8c_ard_3-2-1_110070_2023-07-16_final
2023-07-16 11:18:25	ga_ls8c_ard_3-2-1_110071_2023-07-16_final
2023-07-16 11:18:49	ga_ls8c_ard_3-2-1_110072_2023-07-16_final
2023-07-16 11:19:13	ga_ls8c_ard_3-2-1_110073_2023-07-16_final
2023-07-16 11:19:37	ga_ls8c_ard_3-2-1_110074_2023-07-16_final
2023-07-18 11:10:02	ga_ls8c_ard_3-2-1_108081_2023-07-18_final
2023-07-18 11:10:26	ga_ls8c_ard_3-2-1_108082_2023-07-18_final
2023-07-18 11:10:50	ga_ls8c_ard_3-2-1_108083_2023-07-18_final
2023-08-24 11:23:41	ga_ls8c_ard_3-2-1_111068_2023-08-24_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