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 10:50:38	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
2018-09-17 10:51:26	ga_ls8c_ard_3-0-0_105081_2018-09-17_final
2018-09-17 10:51:49	ga_ls8c_ard_3-0-0_105082_2018-09-17_final
2018-09-17 10:52:13	ga_ls8c_ard_3-0-0_105083_2018-09-17_final
2018-10-08 11:04:33	ga_ls8c_ard_3-0-0_108067_2018-10-08_final
2018-10-08 11:04:57	ga_ls8c_ard_3-0-0_108068_2018-10-08_final
2018-10-08 11:05:20	ga_ls8c_ard_3-0-0_108069_2018-10-08_final
2018-10-08 11:05:44	ga_ls8c_ard_3-0-0_108070_2018-10-08_final
2018-10-08 11:06:08	ga_ls8c_ard_3-0-0_108071_2018-10-08_final
2018-10-10 10:54:59	ga_ls8c_ard_3-0-0_106074_2018-10-10_final
2018-10-10 10:55:23	ga_ls8c_ard_3-0-0_106075_2018-10-10_final
2018-10-10 10:55:47	ga_ls8c_ard_3-0-0_106076_2018-10-10_final
2018-10-10 10:56:11	ga_ls8c_ard_3-0-0_106077_2018-10-10_final
2018-10-10 10:56:35	ga_ls8c_ard_3-0-0_106078_2018-10-10_final
2018-10-10 10:56:59	ga_ls8c_ard_3-0-0_106079_2018-10-10_final
2018-10-10 10:57:23	ga_ls8c_ard_3-0-0_106080_2018-10-10_final
2018-10-12 10:46:14	ga_ls8c_ard_3-0-0_104083_2018-10-12_final
2018-10-19 10:50:52	ga_ls8c_ard_3-0-0_105079_2018-10-19_final
2018-10-19 10:51:15	ga_ls8c_ard_3-0-0_105080_2018-10-19_final
2018-10-19 10:51:39	ga_ls8c_ard_3-0-0_105081_2018-10-19_final
2018-10-19 10:52:03	ga_ls8c_ard_3-0-0_105082_2018-10-19_final
2018-10-19 10:52:27	ga_ls8c_ard_3-0-0_105083_2018-10-19_final
2018-10-24 11:04:38	ga_ls8c_ard_3-0-0_108067_2018-10-24_final
2018-10-24 11:05:02	ga_ls8c_ard_3-0-0_108068_2018-10-24_final
2018-10-24 11:05:26	ga_ls8c_ard_3-0-0_108069_2018-10-24_final
2018-10-24 11:05:50	ga_ls8c_ard_3-0-0_108070_2018-10-24_final
2018-10-24 11:06:14	ga_ls8c_ard_3-0-0_108071_2018-10-24_final
2018-10-26 10:55:05	ga_ls8c_ard_3-0-0_106074_2018-10-26_final
2018-10-26 10:55:29	ga_ls8c_ard_3-0-0_106075_2018-10-26_final
2018-10-26 10:55:52	ga_ls8c_ard_3-0-0_106076_2018-10-26_final
2018-10-26 10:56:16	ga_ls8c_ard_3-0-0_106077_2018-10-26_final
2018-10-26 10:56:40	ga_ls8c_ard_3-0-0_106078_2018-10-26_final
2018-10-26 10:57:04	ga_ls8c_ard_3-0-0_106079_2018-10-26_final
2018-10-26 10:57:28	ga_ls8c_ard_3-0-0_106080_2018-10-26_final
2018-10-28 10:46:19	ga_ls8c_ard_3-0-0_104083_2018-10-28_final
2018-11-04 10:50:55	ga_ls8c_ard_3-0-0_105079_2018-11-04_final
2018-11-04 10:51:19	ga_ls8c_ard_3-0-0_105080_2018-11-04_final
2018-11-04 10:51:43	ga_ls8c_ard_3-0-0_105081_2018-11-04_final
2018-11-04 10:52:07	ga_ls8c_ard_3-0-0_105082_2018-11-04_final
2018-11-04 10:52:31	ga_ls8c_ard_3-0-0_105083_2018-11-04_final
2018-11-18 10:59:42	ga_ls8c_ard_3-0-0_107070_2018-11-18_final
2018-11-18 11:00:06	ga_ls8c_ard_3-0-0_107071_2018-11-18_final
2018-11-18 11:00:30	ga_ls8c_ard_3-0-0_107072_2018-11-18_final
2018-11-18 11:00:54	ga_ls8c_ard_3-0-0_107073_2018-11-18_final
2018-11-18 11:01:18	ga_ls8c_ard_3-0-0_107074_2018-11-18_final
2018-11-18 11:01:42	ga_ls8c_ard_3-0-0_107075_2018-11-18_final
2018-12-06 10:50:54	ga_ls8c_ard_3-0-0_105079_2018-12-06_final
2018-12-06 10:51:18	ga_ls8c_ard_3-0-0_105080_2018-12-06_final
2018-12-06 10:51:42	ga_ls8c_ard_3-0-0_105081_2018-12-06_final
2018-12-06 10:52:06	ga_ls8c_ard_3-0-0_105082_2018-12-06_final
2018-12-06 10:52:30	ga_ls8c_ard_3-0-0_105083_2018-12-06_final
2018-12-11 11:04:38	ga_ls8c_ard_3-0-0_108067_2018-12-11_final
2018-12-11 11:05:02	ga_ls8c_ard_3-0-0_108068_2018-12-11_final
2018-12-11 11:05:26	ga_ls8c_ard_3-0-0_108069_2018-12-11_final
2018-12-11 11:05:50	ga_ls8c_ard_3-0-0_108070_2018-12-11_final
2018-12-11 11:06:13	ga_ls8c_ard_3-0-0_108071_2018-12-11_final
2018-12-13 10:55:27	ga_ls8c_ard_3-0-0_106075_2018-12-13_final
2018-12-13 10:55:51	ga_ls8c_ard_3-0-0_106076_2018-12-13_final
2018-12-13 10:56:15	ga_ls8c_ard_3-0-0_106077_2018-12-13_final
2018-12-13 10:56:39	ga_ls8c_ard_3-0-0_106078_2018-12-13_final
2018-12-13 10:57:03	ga_ls8c_ard_3-0-0_106079_2018-12-13_final
2018-12-13 10:57:27	ga_ls8c_ard_3-0-0_106080_2018-12-13_final
2018-12-15 10:46:17	ga_ls8c_ard_3-0-0_104083_2018-12-15_final
2019-01-05 10:59:38	ga_ls8c_ard_3-0-0_107070_2019-01-05_final
2019-01-05 11:00:02	ga_ls8c_ard_3-0-0_107071_2019-01-05_final
2019-01-05 11:00:26	ga_ls8c_ard_3-0-0_107072_2019-01-05_final
2019-01-05 11:00:50	ga_ls8c_ard_3-0-0_107073_2019-01-05_final
2019-01-05 11:01:14	ga_ls8c_ard_3-0-0_107074_2019-01-05_final
2019-01-05 11:01:38	ga_ls8c_ard_3-0-0_107075_2019-01-05_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
2019-01-07 10:51:39	ga_ls8c_ard_3-0-0_105081_2019-01-07_final
2019-01-07 10:52:03	ga_ls8c_ard_3-0-0_105082_2019-01-07_final
2019-01-07 10:52:27	ga_ls8c_ard_3-0-0_105083_2019-01-07_final
2023-07-20 10:54:53	ga_ls8c_ard_3-2-1_106074_2023-07-20_final
2023-07-20 10:55:17	ga_ls8c_ard_3-2-1_106075_2023-07-20_final
2023-07-20 10:55:41	ga_ls8c_ard_3-2-1_106076_2023-07-20_final
2023-07-20 10:56:05	ga_ls8c_ard_3-2-1_106077_2023-07-20_final
2023-07-20 10:56:28	ga_ls8c_ard_3-2-1_106078_2023-07-20_final
2023-07-20 10:56:52	ga_ls8c_ard_3-2-1_106079_2023-07-20_final
2023-07-20 10:57:16	ga_ls8c_ard_3-2-1_106080_2023-07-20_final
2023-07-27 10:59:34	ga_ls8c_ard_3-2-1_107070_2023-07-27_final
2023-07-27 10:59:58	ga_ls8c_ard_3-2-1_107071_2023-07-27_final
2023-07-27 11:00:22	ga_ls8c_ard_3-2-1_107072_2023-07-27_final
2023-07-27 11:00:45	ga_ls8c_ard_3-2-1_107073_2023-07-27_final
2023-07-27 11:01:09	ga_ls8c_ard_3-2-1_107074_2023-07-27_final
2023-07-27 11:01:33	ga_ls8c_ard_3-2-1_107075_2023-07-27_final
2023-08-12 11:01:14	ga_ls8c_ard_3-2-1_107074_2023-08-12_final
2023-08-12 11:01:38	ga_ls8c_ard_3-2-1_107075_2023-08-12_final
2023-08-28 10:59:46	ga_ls8c_ard_3-2-1_107070_2023-08-28_final
2023-08-28 11:00:10	ga_ls8c_ard_3-2-1_107071_2023-08-28_final
2023-08-28 11:00:34	ga_ls8c_ard_3-2-1_107072_2023-08-28_final
2023-08-28 11:00:58	ga_ls8c_ard_3-2-1_107073_2023-08-28_final
2023-08-28 11:01:22	ga_ls8c_ard_3-2-1_107074_2023-08-28_final
2023-08-28 11:01:46	ga_ls8c_ard_3-2-1_107075_2023-08-28_final
2023-08-30 10:51:00	ga_ls8c_ard_3-2-1_105079_2023-08-30_final
2023-08-30 10:51:24	ga_ls8c_ard_3-2-1_105080_2023-08-30_final
2023-08-30 10:51:48	ga_ls8c_ard_3-2-1_105081_2023-08-30_final
2023-08-30 10:52:12	ga_ls8c_ard_3-2-1_105082_2023-08-30_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