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
2015-10-29 10:39:56	ga_ls8c_ard_3-0-0_103082_2015-10-29_final
2018-09-17 10:48:38	ga_ls8c_ard_3-0-0_105074_2018-09-17_final
2018-09-17 10:49:02	ga_ls8c_ard_3-0-0_105075_2018-09-17_final
2018-09-17 10:49:26	ga_ls8c_ard_3-0-0_105076_2018-09-17_final
2018-09-17 10:49:50	ga_ls8c_ard_3-0-0_105077_2018-09-17_final
2018-09-17 10:50:14	ga_ls8c_ard_3-0-0_105078_2018-09-17_final
2018-09-17 10:50:38	ga_ls8c_ard_3-0-0_105079_2018-09-17_final
2018-09-17 10:51:02	ga_ls8c_ard_3-0-0_105080_2018-09-17_final
2019-01-07 10:48:52	ga_ls8c_ard_3-0-0_105074_2019-01-07_final
2019-01-07 10:49:16	ga_ls8c_ard_3-0-0_105075_2019-01-07_final
2019-01-07 10:49:40	ga_ls8c_ard_3-0-0_105076_2019-01-07_final
2019-01-07 10:50:04	ga_ls8c_ard_3-0-0_105077_2019-01-07_final
2019-01-07 10:50:28	ga_ls8c_ard_3-0-0_105078_2019-01-07_final
2019-01-07 10:50:52	ga_ls8c_ard_3-0-0_105079_2019-01-07_final
2019-01-07 10:51:16	ga_ls8c_ard_3-0-0_105080_2019-01-07_final
2019-03-03 10:53:16	ga_ls8c_ard_3-0-0_106070_2019-03-03_final
2019-03-03 10:53:39	ga_ls8c_ard_3-0-0_106071_2019-03-03_final
2019-03-03 10:54:03	ga_ls8c_ard_3-0-0_106072_2019-03-03_final
2019-03-03 10:54:27	ga_ls8c_ard_3-0-0_106073_2019-03-03_final
2019-03-03 10:54:51	ga_ls8c_ard_3-0-0_106074_2019-03-03_final
2019-03-03 10:55:15	ga_ls8c_ard_3-0-0_106075_2019-03-03_final
2019-03-05 10:44:29	ga_ls8c_ard_3-0-0_104079_2019-03-05_final
2019-03-05 10:44:53	ga_ls8c_ard_3-0-0_104080_2019-03-05_final
2019-03-05 10:45:17	ga_ls8c_ard_3-0-0_104081_2019-03-05_final
2019-03-05 10:45:41	ga_ls8c_ard_3-0-0_104082_2019-03-05_final
2019-03-05 10:46:04	ga_ls8c_ard_3-0-0_104083_2019-03-05_final
2019-03-28 10:48:34	ga_ls8c_ard_3-1-0_105074_2019-03-28_final
2019-03-28 10:48:58	ga_ls8c_ard_3-1-0_105075_2019-03-28_final
2019-03-28 10:49:22	ga_ls8c_ard_3-1-0_105076_2019-03-28_final
2019-03-30 10:39:47	ga_ls8c_ard_3-1-0_103083_2019-03-30_final
2022-09-19 10:53:50	ga_ls8c_ard_3-2-1_106069_2022-09-19_final
2022-09-19 10:54:14	ga_ls8c_ard_3-2-1_106070_2022-09-19_final
2022-09-19 10:54:38	ga_ls8c_ard_3-2-1_106071_2022-09-19_final
2022-09-19 10:55:02	ga_ls8c_ard_3-2-1_106072_2022-09-19_final
2022-09-19 10:55:26	ga_ls8c_ard_3-2-1_106073_2022-09-19_final
2022-09-19 10:55:50	ga_ls8c_ard_3-2-1_106074_2022-09-19_final
2022-09-19 10:56:14	ga_ls8c_ard_3-2-1_106075_2022-09-19_final
2022-09-21 10:45:04	ga_ls8c_ard_3-2-1_104078_2022-09-21_final
2022-09-21 10:45:28	ga_ls8c_ard_3-2-1_104079_2022-09-21_final
2022-09-21 10:45:52	ga_ls8c_ard_3-2-1_104080_2022-09-21_final
2022-09-21 10:46:16	ga_ls8c_ard_3-2-1_104081_2022-09-21_final
2022-09-21 10:46:40	ga_ls8c_ard_3-2-1_104082_2022-09-21_final
2022-09-26 10:59:37	ga_ls8c_ard_3-2-1_107068_2022-09-26_final
2022-09-26 11:00:01	ga_ls8c_ard_3-2-1_107069_2022-09-26_final
2022-09-26 11:00:25	ga_ls8c_ard_3-2-1_107070_2022-09-26_final
2022-09-28 10:49:39	ga_ls8c_ard_3-2-1_105074_2022-09-28_final
2022-09-28 10:50:03	ga_ls8c_ard_3-2-1_105075_2022-09-28_final
2022-09-28 10:50:27	ga_ls8c_ard_3-2-1_105076_2022-09-28_final
2022-09-28 10:50:51	ga_ls8c_ard_3-2-1_105077_2022-09-28_final
2022-09-28 10:51:15	ga_ls8c_ard_3-2-1_105078_2022-09-28_final
2022-09-28 10:51:39	ga_ls8c_ard_3-2-1_105079_2022-09-28_final
2022-09-28 10:52:03	ga_ls8c_ard_3-2-1_105080_2022-09-28_final
2022-09-30 10:40:28	ga_ls8c_ard_3-2-1_103082_2022-09-30_final
2022-10-07 10:45:00	ga_ls8c_ard_3-2-1_104078_2022-10-07_final
2022-10-07 10:45:24	ga_ls8c_ard_3-2-1_104079_2022-10-07_final
2022-10-07 10:45:48	ga_ls8c_ard_3-2-1_104080_2022-10-07_final
2022-10-07 10:46:12	ga_ls8c_ard_3-2-1_104081_2022-10-07_final
2022-10-07 10:46:36	ga_ls8c_ard_3-2-1_104082_2022-10-07_final
2022-10-28 10:59:36	ga_ls8c_ard_3-2-1_107068_2022-10-28_final
2022-10-28 11:00:00	ga_ls8c_ard_3-2-1_107069_2022-10-28_final
2022-10-28 11:00:24	ga_ls8c_ard_3-2-1_107070_2022-10-28_final
2022-10-30 10:49:39	ga_ls8c_ard_3-2-1_105074_2022-10-30_final
2022-10-30 10:50:03	ga_ls8c_ard_3-2-1_105075_2022-10-30_final
2022-10-30 10:50:27	ga_ls8c_ard_3-2-1_105076_2022-10-30_final
2022-10-30 10:50:50	ga_ls8c_ard_3-2-1_105077_2022-10-30_final
2022-10-30 10:51:14	ga_ls8c_ard_3-2-1_105078_2022-10-30_final
2022-10-30 10:51:38	ga_ls8c_ard_3-2-1_105079_2022-10-30_final
2022-10-30 10:52:02	ga_ls8c_ard_3-2-1_105080_2022-10-30_final
2022-11-01 10:40:29	ga_ls8c_ard_3-2-1_103082_2022-11-01_final
2022-11-06 10:54:13	ga_ls8c_ard_3-2-1_106070_2022-11-06_final
2022-11-06 10:54:37	ga_ls8c_ard_3-2-1_106071_2022-11-06_final
2022-11-06 10:55:01	ga_ls8c_ard_3-2-1_106072_2022-11-06_final
2022-11-06 10:55:25	ga_ls8c_ard_3-2-1_106073_2022-11-06_final
2022-11-06 10:55:49	ga_ls8c_ard_3-2-1_106074_2022-11-06_final
2022-11-06 10:56:13	ga_ls8c_ard_3-2-1_106075_2022-11-06_final
2022-11-08 10:45:03	ga_ls8c_ard_3-2-1_104078_2022-11-08_final
2022-11-08 10:45:27	ga_ls8c_ard_3-2-1_104079_2022-11-08_final
2022-11-08 10:45:51	ga_ls8c_ard_3-2-1_104080_2022-11-08_final
2022-11-08 10:46:14	ga_ls8c_ard_3-2-1_104081_2022-11-08_final
2022-11-08 10:46:38	ga_ls8c_ard_3-2-1_104082_2022-11-08_final
2022-11-24 10:45:22	ga_ls8c_ard_3-2-1_104079_2022-11-24_final
2022-11-24 10:45:46	ga_ls8c_ard_3-2-1_104080_2022-11-24_final
2022-11-24 10:46:10	ga_ls8c_ard_3-2-1_104081_2022-11-24_final
2022-11-24 10:46:34	ga_ls8c_ard_3-2-1_104082_2022-11-24_final
2022-11-29 10:59:32	ga_ls8c_ard_3-2-1_107068_2022-11-29_final
2022-11-29 10:59:56	ga_ls8c_ard_3-2-1_107069_2022-11-29_final
2022-11-29 11:00:20	ga_ls8c_ard_3-2-1_107070_2022-11-29_final
2022-12-01 10:49:34	ga_ls8c_ard_3-2-1_105074_2022-12-01_final
2022-12-01 10:49:58	ga_ls8c_ard_3-2-1_105075_2022-12-01_final
2022-12-01 10:50:22	ga_ls8c_ard_3-2-1_105076_2022-12-01_final
2022-12-01 10:50:46	ga_ls8c_ard_3-2-1_105077_2022-12-01_final
2022-12-01 10:51:10	ga_ls8c_ard_3-2-1_105078_2022-12-01_final
2022-12-01 10:51:34	ga_ls8c_ard_3-2-1_105079_2022-12-01_final
2022-12-01 10:51:58	ga_ls8c_ard_3-2-1_105080_2022-12-01_final
2022-12-03 10:40:24	ga_ls8c_ard_3-2-1_103082_2022-12-03_final
2022-12-08 10:54:08	ga_ls8c_ard_3-2-1_106070_2022-12-08_final
2022-12-08 10:54:32	ga_ls8c_ard_3-2-1_106071_2022-12-08_final
2022-12-08 10:54:56	ga_ls8c_ard_3-2-1_106072_2022-12-08_final
2022-12-08 10:55:20	ga_ls8c_ard_3-2-1_106073_2022-12-08_final
2022-12-08 10:55:44	ga_ls8c_ard_3-2-1_106074_2022-12-08_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