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
2016-12-19 11:17:45	ga_ls8c_ard_3-0-0_110068_2016-12-19_final
2016-12-19 11:18:09	ga_ls8c_ard_3-0-0_110069_2016-12-19_final
2016-12-19 11:18:33	ga_ls8c_ard_3-0-0_110070_2016-12-19_final
2016-12-19 11:18:57	ga_ls8c_ard_3-0-0_110071_2016-12-19_final
2016-12-19 11:19:21	ga_ls8c_ard_3-0-0_110072_2016-12-19_final
2016-12-19 11:19:45	ga_ls8c_ard_3-0-0_110073_2016-12-19_final
2016-12-19 11:20:09	ga_ls8c_ard_3-0-0_110074_2016-12-19_final
2017-01-29 11:13:24	ga_ls8c_ard_3-0-0_109073_2017-01-29_final
2017-01-29 11:13:48	ga_ls8c_ard_3-0-0_109074_2017-01-29_final
2017-01-29 11:14:11	ga_ls8c_ard_3-0-0_109075_2017-01-29_final
2017-01-29 11:14:35	ga_ls8c_ard_3-0-0_109076_2017-01-29_final
2017-01-29 11:14:59	ga_ls8c_ard_3-0-0_109077_2017-01-29_final
2017-01-29 11:15:23	ga_ls8c_ard_3-0-0_109078_2017-01-29_final
2017-01-29 11:15:47	ga_ls8c_ard_3-0-0_109079_2017-01-29_final
2017-02-05 11:17:55	ga_ls8c_ard_3-0-0_110069_2017-02-05_final
2017-02-05 11:18:19	ga_ls8c_ard_3-0-0_110070_2017-02-05_final
2017-02-05 11:18:43	ga_ls8c_ard_3-0-0_110071_2017-02-05_final
2017-02-05 11:19:07	ga_ls8c_ard_3-0-0_110072_2017-02-05_final
2017-02-05 11:19:31	ga_ls8c_ard_3-0-0_110073_2017-02-05_final
2017-02-05 11:19:55	ga_ls8c_ard_3-0-0_110074_2017-02-05_final
2017-02-12 11:23:15	ga_ls8c_ard_3-0-0_111067_2017-02-12_final
2017-02-12 11:23:39	ga_ls8c_ard_3-0-0_111068_2017-02-12_final
2017-02-12 11:24:02	ga_ls8c_ard_3-0-0_111069_2017-02-12_final
2017-02-14 11:13:16	ga_ls8c_ard_3-0-0_109073_2017-02-14_final
2017-02-14 11:13:40	ga_ls8c_ard_3-0-0_109074_2017-02-14_final
2017-02-14 11:14:04	ga_ls8c_ard_3-1-0_109075_2017-02-14_final
2017-02-14 11:14:28	ga_ls8c_ard_3-0-0_109076_2017-02-14_final
2017-02-14 11:14:52	ga_ls8c_ard_3-0-0_109077_2017-02-14_final
2017-02-14 11:15:16	ga_ls8c_ard_3-0-0_109078_2017-02-14_final
2017-02-14 11:15:40	ga_ls8c_ard_3-0-0_109079_2017-02-14_final
2017-02-21 11:17:25	ga_ls8c_ard_3-0-0_110068_2017-02-21_final
2017-02-21 11:17:49	ga_ls8c_ard_3-0-0_110069_2017-02-21_final
2017-02-21 11:18:13	ga_ls8c_ard_3-0-0_110070_2017-02-21_final
2017-02-21 11:18:37	ga_ls8c_ard_3-0-0_110071_2017-02-21_final
2017-02-21 11:19:01	ga_ls8c_ard_3-0-0_110072_2017-02-21_final
2017-02-21 11:19:25	ga_ls8c_ard_3-0-0_110073_2017-02-21_final
2017-02-21 11:19:49	ga_ls8c_ard_3-0-0_110074_2017-02-21_final
2017-03-09 11:17:18	ga_ls8c_ard_3-0-0_110068_2017-03-09_final
2017-03-09 11:17:42	ga_ls8c_ard_3-0-0_110069_2017-03-09_final
2017-03-09 11:18:06	ga_ls8c_ard_3-0-0_110070_2017-03-09_final
2017-03-09 11:18:30	ga_ls8c_ard_3-0-0_110071_2017-03-09_final
2017-03-09 11:18:54	ga_ls8c_ard_3-0-0_110072_2017-03-09_final
2017-03-09 11:19:17	ga_ls8c_ard_3-0-0_110073_2017-03-09_final
2017-03-09 11:19:41	ga_ls8c_ard_3-0-0_110074_2017-03-09_final
2017-03-16 11:23:00	ga_ls8c_ard_3-0-0_111067_2017-03-16_final
2017-03-16 11:23:24	ga_ls8c_ard_3-0-0_111068_2017-03-16_final
2017-03-16 11:23:48	ga_ls8c_ard_3-0-0_111069_2017-03-16_final
2017-05-03 11:22:34	ga_ls8c_ard_3-0-0_111067_2017-05-03_final
2017-05-03 11:22:58	ga_ls8c_ard_3-0-0_111068_2017-05-03_final
2017-05-03 11:23:22	ga_ls8c_ard_3-0-0_111069_2017-05-03_final
2017-05-05 11:12:38	ga_ls8c_ard_3-0-0_109073_2017-05-05_final
2017-05-05 11:13:02	ga_ls8c_ard_3-0-0_109074_2017-05-05_final
2017-05-05 11:13:25	ga_ls8c_ard_3-0-0_109075_2017-05-05_final
2017-05-05 11:13:49	ga_ls8c_ard_3-0-0_109076_2017-05-05_final
2017-05-05 11:14:13	ga_ls8c_ard_3-0-0_109077_2017-05-05_final
2017-05-05 11:14:37	ga_ls8c_ard_3-0-0_109078_2017-05-05_final
2017-05-05 11:15:01	ga_ls8c_ard_3-0-0_109079_2017-05-05_final
2017-06-20 11:23:01	ga_ls8c_ard_3-0-0_111067_2017-06-20_final
2017-06-20 11:23:25	ga_ls8c_ard_3-0-0_111068_2017-06-20_final
2017-06-20 11:23:49	ga_ls8c_ard_3-0-0_111069_2017-06-20_final
2017-07-08 11:13:07	ga_ls8c_ard_3-0-0_109073_2017-07-08_final
2017-07-08 11:13:31	ga_ls8c_ard_3-0-0_109074_2017-07-08_final
2017-07-08 11:13:55	ga_ls8c_ard_3-0-0_109075_2017-07-08_final
2017-07-08 11:14:19	ga_ls8c_ard_3-0-0_109076_2017-07-08_final
2017-07-08 11:14:43	ga_ls8c_ard_3-0-0_109077_2017-07-08_final
2018-06-18 11:08:04	ga_ls8c_ard_3-0-0_108078_2018-06-18_final
2018-06-18 11:08:28	ga_ls8c_ard_3-0-0_108079_2018-06-18_final
2018-06-18 11:08:52	ga_ls8c_ard_3-0-0_108080_2018-06-18_final
2018-06-18 11:09:16	ga_ls8c_ard_3-0-0_108081_2018-06-18_final
2018-06-18 11:09:40	ga_ls8c_ard_3-0-0_108082_2018-06-18_final
2018-06-18 11:10:04	ga_ls8c_ard_3-0-0_108083_2018-06-18_final
2018-11-18 11:04:30	ga_ls8c_ard_3-1-0_107082_2018-11-18_final
2018-11-18 11:04:53	ga_ls8c_ard_3-0-0_107083_2018-11-18_final
2018-11-18 11:05:17	ga_ls8c_ard_3-0-0_107084_2018-11-18_final
2018-11-18 11:05:41	ga_ls8c_ard_3-0-0_107085_2018-11-18_final
2019-01-05 11:04:25	ga_ls8c_ard_3-1-0_107082_2019-01-05_final
2019-01-05 11:04:49	ga_ls8c_ard_3-0-0_107083_2019-01-05_final
2019-01-05 11:05:13	ga_ls8c_ard_3-0-0_107084_2019-01-05_final
2019-01-05 11:05:37	ga_ls8c_ard_3-0-0_107085_2019-01-05_final
2019-01-12 11:08:59	ga_ls8c_ard_3-0-0_108078_2019-01-12_final
2019-01-12 11:09:23	ga_ls8c_ard_3-0-0_108079_2019-01-12_final
2019-01-12 11:09:47	ga_ls8c_ard_3-0-0_108080_2019-01-12_final
2019-01-12 11:10:11	ga_ls8c_ard_3-0-0_108081_2019-01-12_final
2019-01-12 11:10:35	ga_ls8c_ard_3-0-0_108082_2019-01-12_final
2019-01-12 11:10:59	ga_ls8c_ard_3-0-0_108083_2019-01-12_final
2019-07-23 11:09:08	ga_ls8c_ard_3-1-0_108078_2019-07-23_final
2019-07-23 11:09:32	ga_ls8c_ard_3-1-0_108079_2019-07-23_final
2019-07-23 11:09:55	ga_ls8c_ard_3-1-0_108080_2019-07-23_final
2019-07-23 11:10:19	ga_ls8c_ard_3-1-0_108081_2019-07-23_final
2019-07-23 11:10:43	ga_ls8c_ard_3-1-0_108082_2019-07-23_final
2019-07-23 11:11:07	ga_ls8c_ard_3-1-0_108083_2019-07-23_final
2019-09-09 11:09:22	ga_ls8c_ard_3-1-0_108078_2019-09-09_final
2019-09-09 11:09:46	ga_ls8c_ard_3-1-0_108079_2019-09-09_final
2019-09-09 11:10:10	ga_ls8c_ard_3-1-0_108080_2019-09-09_final
2019-09-09 11:10:34	ga_ls8c_ard_3-1-0_108081_2019-09-09_final
2019-09-09 11:10:58	ga_ls8c_ard_3-1-0_108082_2019-09-09_final
2019-09-09 11:11:22	ga_ls8c_ard_3-1-0_108083_2019-09-09_final
2019-10-04 11:04:55	ga_ls8c_ard_3-1-0_107082_2019-10-04_final
2019-10-04 11:05:19	ga_ls8c_ard_3-1-0_107083_2019-10-04_final
2019-10-04 11:05:43	ga_ls8c_ard_3-1-0_107084_2019-10-04_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