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
2022-03-29 10:42:34	ga_ls8c_ard_3-2-1_104074_2022-03-29_final
2022-03-29 10:42:58	ga_ls8c_ard_3-2-1_104075_2022-03-29_final
2022-03-29 10:43:22	ga_ls8c_ard_3-2-1_104076_2022-03-29_final
2022-03-29 10:43:46	ga_ls8c_ard_3-2-1_104077_2022-03-29_final
2022-03-29 10:44:10	ga_ls8c_ard_3-2-1_104078_2022-03-29_final
2022-03-29 10:44:34	ga_ls8c_ard_3-2-1_104079_2022-03-29_final
2022-03-29 10:44:58	ga_ls8c_ard_3-2-1_104080_2022-03-29_final
2022-03-29 10:45:22	ga_ls8c_ard_3-2-1_104081_2022-03-29_final
2022-03-29 10:45:46	ga_ls8c_ard_3-2-1_104082_2022-03-29_final
2022-04-03 10:59:30	ga_ls8c_ard_3-2-1_107070_2022-04-03_final
2022-04-03 10:59:54	ga_ls8c_ard_3-2-1_107071_2022-04-03_final
2022-04-03 11:00:18	ga_ls8c_ard_3-2-1_107072_2022-04-03_final
2022-04-03 11:00:42	ga_ls8c_ard_3-2-1_107073_2022-04-03_final
2022-04-03 11:01:06	ga_ls8c_ard_3-2-1_107074_2022-04-03_final
2022-04-03 11:01:30	ga_ls8c_ard_3-2-1_107075_2022-04-03_final
2022-04-03 11:01:54	ga_ls8c_ard_3-2-1_107076_2022-04-03_final
2022-04-03 11:02:18	ga_ls8c_ard_3-2-1_107077_2022-04-03_final
2022-04-05 10:46:46	ga_ls8c_ard_3-2-1_105069_2022-04-05_final
2022-04-05 10:47:10	ga_ls8c_ard_3-2-1_105070_2022-04-05_final
2022-04-05 10:47:34	ga_ls8c_ard_3-2-1_105071_2022-04-05_final
2022-04-05 10:47:58	ga_ls8c_ard_3-2-1_105072_2022-04-05_final
2022-04-05 10:48:22	ga_ls8c_ard_3-2-1_105073_2022-04-05_final
2022-04-05 10:48:46	ga_ls8c_ard_3-2-1_105074_2022-04-05_final
2022-04-05 10:49:10	ga_ls8c_ard_3-2-1_105075_2022-04-05_final
2022-04-05 10:49:34	ga_ls8c_ard_3-2-1_105076_2022-04-05_final
2022-04-05 10:49:58	ga_ls8c_ard_3-2-1_105077_2022-04-05_final
2022-04-05 10:50:22	ga_ls8c_ard_3-2-1_105078_2022-04-05_final
2022-04-05 10:50:46	ga_ls8c_ard_3-2-1_105079_2022-04-05_final
2022-04-05 10:51:10	ga_ls8c_ard_3-2-1_105080_2022-04-05_final
2022-04-05 10:51:33	ga_ls8c_ard_3-2-1_105081_2022-04-05_final
2022-04-05 10:51:57	ga_ls8c_ard_3-2-1_105082_2022-04-05_final
2022-04-05 10:52:21	ga_ls8c_ard_3-2-1_105083_2022-04-05_final
2022-04-07 10:38:01	ga_ls8c_ard_3-2-1_103078_2022-04-07_final
2022-04-07 10:38:25	ga_ls8c_ard_3-2-1_103079_2022-04-07_final
2022-04-07 10:38:49	ga_ls8c_ard_3-2-1_103080_2022-04-07_final
2022-04-07 10:39:13	ga_ls8c_ard_3-2-1_103081_2022-04-07_final
2022-04-07 10:39:37	ga_ls8c_ard_3-2-1_103082_2022-04-07_final
2022-04-10 11:05:22	ga_ls8c_ard_3-2-1_108069_2022-04-10_final
2022-04-10 11:05:46	ga_ls8c_ard_3-2-1_108070_2022-04-10_final
2022-04-10 11:06:09	ga_ls8c_ard_3-2-1_108071_2022-04-10_final
2022-04-10 11:06:33	ga_ls8c_ard_3-2-1_108072_2022-04-10_final
2022-04-10 11:06:57	ga_ls8c_ard_3-2-1_108073_2022-04-10_final
2022-04-12 10:52:37	ga_ls8c_ard_3-2-1_106068_2022-04-12_final
2022-04-12 10:53:01	ga_ls8c_ard_3-2-1_106069_2022-04-12_final
2022-04-12 10:53:25	ga_ls8c_ard_3-2-1_106070_2022-04-12_final
2022-04-12 10:53:49	ga_ls8c_ard_3-2-1_106071_2022-04-12_final
2022-04-12 10:54:13	ga_ls8c_ard_3-2-1_106072_2022-04-12_final
2022-04-12 10:54:37	ga_ls8c_ard_3-2-1_106073_2022-04-12_final
2022-04-12 10:55:01	ga_ls8c_ard_3-2-1_106074_2022-04-12_final
2022-04-12 10:55:24	ga_ls8c_ard_3-2-1_106075_2022-04-12_final
2022-04-12 10:55:48	ga_ls8c_ard_3-2-1_106076_2022-04-12_final
2022-04-12 10:56:12	ga_ls8c_ard_3-2-1_106077_2022-04-12_final
2022-04-12 10:56:36	ga_ls8c_ard_3-2-1_106078_2022-04-12_final
2022-04-12 10:57:00	ga_ls8c_ard_3-2-1_106079_2022-04-12_final
2022-04-12 10:57:24	ga_ls8c_ard_3-2-1_106080_2022-04-12_final
2022-04-12 10:57:48	ga_ls8c_ard_3-2-1_106081_2022-04-12_final
2022-04-14 10:42:40	ga_ls8c_ard_3-2-1_104074_2022-04-14_final
2022-04-14 10:43:04	ga_ls8c_ard_3-2-1_104075_2022-04-14_final
2022-04-14 10:43:27	ga_ls8c_ard_3-2-1_104076_2022-04-14_final
2022-04-14 10:43:51	ga_ls8c_ard_3-2-1_104077_2022-04-14_final
2022-04-14 10:44:15	ga_ls8c_ard_3-2-1_104078_2022-04-14_final
2022-04-14 10:44:39	ga_ls8c_ard_3-2-1_104079_2022-04-14_final
2022-04-14 10:45:03	ga_ls8c_ard_3-2-1_104080_2022-04-14_final
2022-04-14 10:45:27	ga_ls8c_ard_3-2-1_104081_2022-04-14_final
2022-04-14 10:45:51	ga_ls8c_ard_3-2-1_104082_2022-04-14_final
2022-04-19 10:59:36	ga_ls8c_ard_3-2-1_107070_2022-04-19_final
2022-04-19 11:00:00	ga_ls8c_ard_3-2-1_107071_2022-04-19_final
2022-04-19 11:00:24	ga_ls8c_ard_3-2-1_107072_2022-04-19_final
2022-04-19 11:00:48	ga_ls8c_ard_3-2-1_107073_2022-04-19_final
2022-04-19 11:01:11	ga_ls8c_ard_3-2-1_107074_2022-04-19_final
2022-04-19 11:01:35	ga_ls8c_ard_3-2-1_107075_2022-04-19_final
2022-04-19 11:01:59	ga_ls8c_ard_3-2-1_107076_2022-04-19_final
2022-04-19 11:02:23	ga_ls8c_ard_3-2-1_107077_2022-04-19_final
2022-04-21 10:46:50	ga_ls8c_ard_3-2-1_105069_2022-04-21_final
2022-04-21 10:47:13	ga_ls8c_ard_3-2-1_105070_2022-04-21_final
2022-04-21 10:47:37	ga_ls8c_ard_3-2-1_105071_2022-04-21_final
2022-04-21 10:48:01	ga_ls8c_ard_3-2-1_105072_2022-04-21_final
2022-04-21 10:48:25	ga_ls8c_ard_3-2-1_105073_2022-04-21_final
2022-04-21 10:48:49	ga_ls8c_ard_3-2-1_105074_2022-04-21_final
2022-04-21 10:49:13	ga_ls8c_ard_3-2-1_105075_2022-04-21_final
2022-04-21 10:49:37	ga_ls8c_ard_3-2-1_105076_2022-04-21_final
2022-04-21 10:50:01	ga_ls8c_ard_3-2-1_105077_2022-04-21_final
2022-04-21 10:50:25	ga_ls8c_ard_3-2-1_105078_2022-04-21_final
2022-04-21 10:50:49	ga_ls8c_ard_3-2-1_105079_2022-04-21_final
2022-04-21 10:51:13	ga_ls8c_ard_3-2-1_105080_2022-04-21_final
2022-04-21 10:51:37	ga_ls8c_ard_3-2-1_105081_2022-04-21_final
2022-04-21 10:52:01	ga_ls8c_ard_3-2-1_105082_2022-04-21_final
2022-04-21 10:52:25	ga_ls8c_ard_3-2-1_105083_2022-04-21_final
2022-04-23 10:38:03	ga_ls8c_ard_3-2-1_103078_2022-04-23_final
2022-04-23 10:38:27	ga_ls8c_ard_3-2-1_103079_2022-04-23_final
2022-04-23 10:38:50	ga_ls8c_ard_3-2-1_103080_2022-04-23_final
2022-04-23 10:39:14	ga_ls8c_ard_3-2-1_103081_2022-04-23_final
2022-04-23 10:39:38	ga_ls8c_ard_3-2-1_103082_2022-04-23_final
2022-04-26 11:05:20	ga_ls8c_ard_3-2-1_108069_2022-04-26_final
2022-04-26 11:05:44	ga_ls8c_ard_3-2-1_108070_2022-04-26_final
2022-04-26 11:06:08	ga_ls8c_ard_3-2-1_108071_2022-04-26_final
2022-04-26 11:06:31	ga_ls8c_ard_3-2-1_108072_2022-04-26_final
2022-04-26 11:06:55	ga_ls8c_ard_3-2-1_108073_2022-04-26_final
2022-04-30 10:43:47	ga_ls8c_ard_3-2-1_104077_2022-04-30_final
2022-04-30 10:45:23	ga_ls8c_ard_3-2-1_104081_2022-04-30_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