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
2013-04-02 10:52:12	ga_ls8c_ard_3-0-0_105082_2013-04-02_final
2013-04-28 10:53:33	ga_ls8c_ard_3-0-0_105081_2013-04-28_final
2013-07-01 10:53:46	ga_ls8c_ard_3-0-0_105081_2013-07-01_final
2013-07-01 10:54:10	ga_ls8c_ard_3-0-0_105082_2013-07-01_final
2013-07-17 10:53:46	ga_ls8c_ard_3-0-0_105081_2013-07-17_final
2013-07-17 10:54:10	ga_ls8c_ard_3-0-0_105082_2013-07-17_final
2013-08-23 11:07:59	ga_ls8c_ard_3-0-0_108070_2013-08-23_final
2013-08-23 11:08:23	ga_ls8c_ard_3-0-0_108071_2013-08-23_final
2013-08-23 11:08:47	ga_ls8c_ard_3-0-0_108072_2013-08-23_final
2013-08-23 11:09:11	ga_ls8c_ard_3-0-0_108073_2013-08-23_final
2015-02-02 11:04:42	ga_ls8c_ard_3-0-0_108067_2015-02-02_final
2015-02-02 11:05:06	ga_ls8c_ard_3-0-0_108068_2015-02-02_final
2015-02-02 11:05:30	ga_ls8c_ard_3-0-0_108069_2015-02-02_final
2015-02-02 11:05:54	ga_ls8c_ard_3-0-0_108070_2015-02-02_final
2015-02-02 11:06:18	ga_ls8c_ard_3-0-0_108071_2015-02-02_final
2015-02-02 11:06:42	ga_ls8c_ard_3-0-0_108072_2015-02-02_final
2015-02-02 11:07:05	ga_ls8c_ard_3-0-0_108073_2015-02-02_final
2015-05-25 11:03:49	ga_ls8c_ard_3-0-0_108067_2015-05-25_final
2015-05-25 11:04:13	ga_ls8c_ard_3-0-0_108068_2015-05-25_final
2015-05-25 11:04:37	ga_ls8c_ard_3-0-0_108069_2015-05-25_final
2015-05-25 11:05:01	ga_ls8c_ard_3-0-0_108070_2015-05-25_final
2015-05-25 11:05:25	ga_ls8c_ard_3-0-0_108071_2015-05-25_final
2015-05-25 11:05:49	ga_ls8c_ard_3-0-0_108072_2015-05-25_final
2015-05-25 11:06:13	ga_ls8c_ard_3-0-0_108073_2015-05-25_final
2015-06-10 11:04:00	ga_ls8c_ard_3-0-0_108067_2015-06-10_final
2015-06-10 11:04:23	ga_ls8c_ard_3-0-0_108068_2015-06-10_final
2015-06-10 11:04:47	ga_ls8c_ard_3-0-0_108069_2015-06-10_final
2015-06-10 11:05:11	ga_ls8c_ard_3-0-0_108070_2015-06-10_final
2015-06-10 11:05:35	ga_ls8c_ard_3-0-0_108071_2015-06-10_final
2015-06-10 11:05:59	ga_ls8c_ard_3-0-0_108072_2015-06-10_final
2015-06-10 11:06:23	ga_ls8c_ard_3-0-0_108073_2015-06-10_final
2017-05-07 10:59:54	ga_ls8c_ard_3-0-0_107072_2017-05-07_final
2017-05-07 11:00:18	ga_ls8c_ard_3-0-0_107073_2017-05-07_final
2017-05-07 11:00:41	ga_ls8c_ard_3-0-0_107074_2017-05-07_final
2017-05-07 11:01:05	ga_ls8c_ard_3-0-0_107075_2017-05-07_final
2018-02-26 11:04:29	ga_ls8c_ard_3-0-0_108067_2018-02-26_final
2018-02-26 11:04:53	ga_ls8c_ard_3-0-0_108068_2018-02-26_final
2018-02-26 11:05:17	ga_ls8c_ard_3-0-0_108069_2018-02-26_final
2018-02-26 11:05:41	ga_ls8c_ard_3-0-0_108070_2018-02-26_final
2018-02-26 11:06:05	ga_ls8c_ard_3-0-0_108071_2018-02-26_final
2018-02-26 11:06:28	ga_ls8c_ard_3-0-0_108072_2018-02-26_final
2018-02-26 11:06:52	ga_ls8c_ard_3-0-0_108073_2018-02-26_final
2018-03-14 11:04:20	ga_ls8c_ard_3-0-0_108067_2018-03-14_final
2018-03-14 11:04:44	ga_ls8c_ard_3-0-0_108068_2018-03-14_final
2018-03-14 11:05:08	ga_ls8c_ard_3-0-0_108069_2018-03-14_final
2018-03-14 11:05:31	ga_ls8c_ard_3-0-0_108070_2018-03-14_final
2018-03-14 11:05:55	ga_ls8c_ard_3-0-0_108071_2018-03-14_final
2018-03-14 11:06:19	ga_ls8c_ard_3-0-0_108072_2018-03-14_final
2018-03-14 11:06:43	ga_ls8c_ard_3-0-0_108073_2018-03-14_final
2018-05-17 11:03:45	ga_ls8c_ard_3-0-0_108067_2018-05-17_final
2018-05-17 11:04:09	ga_ls8c_ard_3-0-0_108068_2018-05-17_final
2018-05-17 11:04:32	ga_ls8c_ard_3-0-0_108069_2018-05-17_final
2018-05-17 11:04:56	ga_ls8c_ard_3-0-0_108070_2018-05-17_final
2018-05-17 11:05:20	ga_ls8c_ard_3-0-0_108071_2018-05-17_final
2018-05-17 11:05:44	ga_ls8c_ard_3-0-0_108072_2018-05-17_final
2018-05-17 11:06:08	ga_ls8c_ard_3-0-0_108073_2018-05-17_final
2018-07-04 11:03:50	ga_ls8c_ard_3-0-0_108067_2018-07-04_final
2018-07-04 11:04:14	ga_ls8c_ard_3-0-0_108068_2018-07-04_final
2018-07-04 11:04:38	ga_ls8c_ard_3-0-0_108069_2018-07-04_final
2018-07-04 11:05:02	ga_ls8c_ard_3-0-0_108070_2018-07-04_final
2018-07-04 11:05:26	ga_ls8c_ard_3-0-0_108071_2018-07-04_final
2018-07-04 11:05:50	ga_ls8c_ard_3-0-0_108072_2018-07-04_final
2018-07-04 11:06:14	ga_ls8c_ard_3-0-0_108073_2018-07-04_final
2019-07-07 11:04:41	ga_ls8c_ard_3-1-0_108067_2019-07-07_final
2019-07-07 11:05:04	ga_ls8c_ard_3-1-0_108068_2019-07-07_final
2019-07-07 11:05:28	ga_ls8c_ard_3-1-0_108069_2019-07-07_final
2019-07-07 11:05:52	ga_ls8c_ard_3-1-0_108070_2019-07-07_final
2019-07-07 11:06:16	ga_ls8c_ard_3-1-0_108071_2019-07-07_final
2019-07-07 11:06:40	ga_ls8c_ard_3-1-0_108072_2019-07-07_final
2019-07-07 11:07:04	ga_ls8c_ard_3-1-0_108073_2019-07-07_final
2019-07-14 11:10:52	ga_ls8c_ard_3-1-0_109067_2019-07-14_final
2019-07-14 11:11:16	ga_ls8c_ard_3-1-0_109068_2019-07-14_final
2019-07-16 11:00:31	ga_ls8c_ard_3-1-0_107072_2019-07-16_final
2019-07-16 11:00:55	ga_ls8c_ard_3-1-0_107073_2019-07-16_final
2019-07-16 11:01:19	ga_ls8c_ard_3-1-0_107074_2019-07-16_final
2019-07-16 11:01:43	ga_ls8c_ard_3-1-0_107075_2019-07-16_final
2019-07-16 11:02:06	ga_ls8c_ard_3-1-0_107076_2019-07-16_final
2019-07-16 11:02:30	ga_ls8c_ard_3-1-0_107077_2019-07-16_final
2019-07-16 11:02:54	ga_ls8c_ard_3-1-0_107078_2019-07-16_final
2019-10-02 11:11:17	ga_ls8c_ard_3-1-0_109067_2019-10-02_final
2019-10-02 11:11:41	ga_ls8c_ard_3-1-0_109068_2019-10-02_final
2019-10-04 11:00:56	ga_ls8c_ard_3-1-0_107072_2019-10-04_final
2019-10-04 11:01:20	ga_ls8c_ard_3-1-0_107073_2019-10-04_final
2019-10-04 11:01:44	ga_ls8c_ard_3-1-0_107074_2019-10-04_final
2019-10-04 11:02:08	ga_ls8c_ard_3-1-0_107075_2019-10-04_final
2019-10-04 11:02:32	ga_ls8c_ard_3-1-0_107076_2019-10-04_final
2019-10-04 11:02:55	ga_ls8c_ard_3-1-0_107077_2019-10-04_final
2019-10-04 11:03:19	ga_ls8c_ard_3-1-0_107078_2019-10-04_final
2019-10-06 10:52:10	ga_ls8c_ard_3-1-0_105081_2019-10-06_final
2019-10-06 10:52:34	ga_ls8c_ard_3-1-0_105082_2019-10-06_final
2019-10-06 10:52:58	ga_ls8c_ard_3-1-0_105083_2019-10-06_final
2019-11-12 11:05:07	ga_ls8c_ard_3-1-0_108067_2019-11-12_final
2019-11-12 11:05:31	ga_ls8c_ard_3-1-0_108068_2019-11-12_final
2019-11-12 11:05:55	ga_ls8c_ard_3-1-0_108069_2019-11-12_final
2019-11-12 11:06:18	ga_ls8c_ard_3-1-0_108070_2019-11-12_final
2019-11-12 11:06:42	ga_ls8c_ard_3-1-0_108071_2019-11-12_final
2019-11-12 11:07:06	ga_ls8c_ard_3-1-0_108072_2019-11-12_final
2019-11-12 11:07:30	ga_ls8c_ard_3-1-0_108073_2019-11-12_final
2019-11-23 10:52:07	ga_ls8c_ard_3-1-0_105081_2019-11-23_final
2019-11-23 10:52:31	ga_ls8c_ard_3-1-0_105082_2019-11-23_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years