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
2018-09-17 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
2022-06-06 10:59:02	ga_ls8c_ard_3-2-1_107068_2022-06-06_final
2022-06-06 10:59:26	ga_ls8c_ard_3-2-1_107069_2022-06-06_final
2022-06-06 10:59:50	ga_ls8c_ard_3-2-1_107070_2022-06-06_final
2022-06-08 10:49:06	ga_ls8c_ard_3-2-1_105074_2022-06-08_final
2022-06-08 10:49:30	ga_ls8c_ard_3-2-1_105075_2022-06-08_final
2022-06-08 10:49:54	ga_ls8c_ard_3-2-1_105076_2022-06-08_final
2022-06-08 10:50:18	ga_ls8c_ard_3-2-1_105077_2022-06-08_final
2022-06-08 10:50:41	ga_ls8c_ard_3-2-1_105078_2022-06-08_final
2022-06-08 10:51:05	ga_ls8c_ard_3-2-1_105079_2022-06-08_final
2022-06-08 10:51:29	ga_ls8c_ard_3-2-1_105080_2022-06-08_final
2022-07-26 10:49:22	ga_ls8c_ard_3-2-1_105074_2022-07-26_final
2022-07-26 10:49:46	ga_ls8c_ard_3-2-1_105075_2022-07-26_final
2022-07-26 10:50:10	ga_ls8c_ard_3-2-1_105076_2022-07-26_final
2022-07-26 10:50:34	ga_ls8c_ard_3-2-1_105077_2022-07-26_final
2022-07-26 10:50:58	ga_ls8c_ard_3-2-1_105078_2022-07-26_final
2022-07-26 10:51:22	ga_ls8c_ard_3-2-1_105079_2022-07-26_final
2022-07-26 10:51:45	ga_ls8c_ard_3-2-1_105080_2022-07-26_final
2022-07-28 10:40:13	ga_ls8c_ard_3-2-1_103082_2022-07-28_final
2022-08-04 10:44:52	ga_ls8c_ard_3-2-1_104078_2022-08-04_final
2022-08-04 10:45:16	ga_ls8c_ard_3-2-1_104079_2022-08-04_final
2022-08-04 10:45:40	ga_ls8c_ard_3-2-1_104080_2022-08-04_final
2022-08-04 10:46:04	ga_ls8c_ard_3-2-1_104081_2022-08-04_final
2022-08-04 10:46:28	ga_ls8c_ard_3-2-1_104082_2022-08-04_final
2022-08-25 10:59:30	ga_ls8c_ard_3-2-1_107068_2022-08-25_final
2022-08-25 10:59:54	ga_ls8c_ard_3-2-1_107069_2022-08-25_final
2022-08-25 11:00:18	ga_ls8c_ard_3-2-1_107070_2022-08-25_final
2022-09-03 10:54:07	ga_ls8c_ard_3-2-1_106070_2022-09-03_final
2022-09-03 10:54:31	ga_ls8c_ard_3-2-1_106071_2022-09-03_final
2022-09-03 10:54:55	ga_ls8c_ard_3-2-1_106072_2022-09-03_final
2022-09-03 10:55:19	ga_ls8c_ard_3-2-1_106073_2022-09-03_final
2022-09-03 10:55:43	ga_ls8c_ard_3-2-1_106074_2022-09-03_final
2022-09-03 10:56:06	ga_ls8c_ard_3-2-1_106075_2022-09-03_final
2022-09-05 10:45:22	ga_ls8c_ard_3-2-1_104079_2022-09-05_final
2022-09-05 10:45:46	ga_ls8c_ard_3-2-1_104080_2022-09-05_final
2022-09-05 10:46:10	ga_ls8c_ard_3-2-1_104081_2022-09-05_final
2022-09-05 10:46:34	ga_ls8c_ard_3-2-1_104082_2022-09-05_final
2022-09-10 10:59:34	ga_ls8c_ard_3-2-1_107068_2022-09-10_final
2022-09-10 10:59:58	ga_ls8c_ard_3-2-1_107069_2022-09-10_final
2022-09-10 11:00:22	ga_ls8c_ard_3-2-1_107070_2022-09-10_final
2022-10-05 10:54:12	ga_ls8c_ard_3-2-1_106070_2022-10-05_final
2022-10-05 10:54:36	ga_ls8c_ard_3-2-1_106071_2022-10-05_final
2022-10-05 10:55:00	ga_ls8c_ard_3-2-1_106072_2022-10-05_final
2022-10-05 10:55:24	ga_ls8c_ard_3-2-1_106073_2022-10-05_final
2022-10-05 10:55:47	ga_ls8c_ard_3-2-1_106074_2022-10-05_final
2022-10-05 10:56:11	ga_ls8c_ard_3-2-1_106075_2022-10-05_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
2022-11-13 10:59:33	ga_ls8c_ard_3-2-1_107068_2022-11-13_final
2022-11-13 10:59:57	ga_ls8c_ard_3-2-1_107069_2022-11-13_final
2022-11-13 11:00:21	ga_ls8c_ard_3-2-1_107070_2022-11-13_final
2022-11-15 10:49:33	ga_ls8c_ard_3-2-1_105074_2022-11-15_final
2022-11-15 10:49:57	ga_ls8c_ard_3-2-1_105075_2022-11-15_final
2022-11-15 10:50:21	ga_ls8c_ard_3-2-1_105076_2022-11-15_final
2022-11-15 10:50:45	ga_ls8c_ard_3-2-1_105077_2022-11-15_final
2022-11-15 10:51:09	ga_ls8c_ard_3-2-1_105078_2022-11-15_final
2022-11-15 10:51:33	ga_ls8c_ard_3-2-1_105079_2022-11-15_final
2022-11-15 10:51:57	ga_ls8c_ard_3-2-1_105080_2022-11-15_final
2022-11-22 10:54:08	ga_ls8c_ard_3-2-1_106070_2022-11-22_final
2022-11-22 10:54:31	ga_ls8c_ard_3-2-1_106071_2022-11-22_final
2022-11-22 10:54:55	ga_ls8c_ard_3-2-1_106072_2022-11-22_final
2022-11-22 10:55:19	ga_ls8c_ard_3-2-1_106073_2022-11-22_final
2022-11-22 10:55:43	ga_ls8c_ard_3-2-1_106074_2022-11-22_final
2022-11-22 10:56:07	ga_ls8c_ard_3-2-1_106075_2022-11-22_final
2022-12-17 10:49:28	ga_ls8c_ard_3-2-1_105074_2022-12-17_final
2022-12-17 10:49:52	ga_ls8c_ard_3-2-1_105075_2022-12-17_final
2022-12-17 10:50:16	ga_ls8c_ard_3-2-1_105076_2022-12-17_final
2022-12-17 10:50:40	ga_ls8c_ard_3-2-1_105077_2022-12-17_final
2022-12-17 10:51:04	ga_ls8c_ard_3-2-1_105078_2022-12-17_final
2022-12-17 10:51:28	ga_ls8c_ard_3-2-1_105079_2022-12-17_final
2022-12-17 10:51:51	ga_ls8c_ard_3-2-1_105080_2022-12-17_final
2023-02-03 10:49:23	ga_ls8c_ard_3-2-1_105074_2023-02-03_final
2023-02-03 10:49:47	ga_ls8c_ard_3-2-1_105075_2023-02-03_final
2023-02-03 10:50:11	ga_ls8c_ard_3-2-1_105076_2023-02-03_final
2023-02-03 10:50:35	ga_ls8c_ard_3-2-1_105077_2023-02-03_final
2023-02-03 10:50:59	ga_ls8c_ard_3-2-1_105078_2023-02-03_final
2023-07-27 10:58:46	ga_ls8c_ard_3-2-1_107068_2023-07-27_final
2023-07-27 10:59:10	ga_ls8c_ard_3-2-1_107069_2023-07-27_final
2023-07-27 10:59:34	ga_ls8c_ard_3-2-1_107070_2023-07-27_final
2023-07-29 10:48:49	ga_ls8c_ard_3-2-1_105074_2023-07-29_final
2023-07-29 10:49:13	ga_ls8c_ard_3-2-1_105075_2023-07-29_final
2023-07-29 10:49:37	ga_ls8c_ard_3-2-1_105076_2023-07-29_final
2023-07-29 10:50:01	ga_ls8c_ard_3-2-1_105077_2023-07-29_final
2023-07-29 10:50:25	ga_ls8c_ard_3-2-1_105078_2023-07-29_final
2023-07-29 10:50:49	ga_ls8c_ard_3-2-1_105079_2023-07-29_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