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
2017-10-28 11:18:01	ga_ls8c_ard_3-0-0_109084_2017-10-28_final
2017-10-28 11:18:25	ga_ls8c_ard_3-0-0_109085_2017-10-28_final
2017-10-31 11:42:08	ga_ls8c_ard_3-0-0_114067_2017-10-31_final
2017-11-02 11:31:46	ga_ls8c_ard_3-0-0_112072_2017-11-02_final
2017-11-02 11:32:10	ga_ls8c_ard_3-0-0_112073_2017-11-02_final
2017-11-02 11:32:34	ga_ls8c_ard_3-0-0_112074_2017-11-02_final
2017-11-02 11:32:58	ga_ls8c_ard_3-0-0_112075_2017-11-02_final
2017-11-02 11:33:22	ga_ls8c_ard_3-0-0_112076_2017-11-02_final
2017-11-02 11:33:45	ga_ls8c_ard_3-0-0_112077_2017-11-02_final
2017-11-02 11:34:09	ga_ls8c_ard_3-0-0_112078_2017-11-02_final
2017-11-13 11:17:58	ga_ls8c_ard_3-0-0_109084_2017-11-13_final
2017-11-13 11:18:22	ga_ls8c_ard_3-0-0_109085_2017-11-13_final
2017-11-25 11:35:50	ga_ls8c_ard_3-0-0_113067_2017-11-25_final
2017-11-25 11:37:50	ga_ls8c_ard_3-0-0_113072_2017-11-25_final
2017-11-25 11:38:14	ga_ls8c_ard_3-1-0_113073_2017-11-25_final
2017-12-04 11:31:37	ga_ls8c_ard_3-0-0_112072_2017-12-04_final
2017-12-04 11:32:01	ga_ls8c_ard_3-0-0_112073_2017-12-04_final
2017-12-04 11:32:25	ga_ls8c_ard_3-0-0_112074_2017-12-04_final
2017-12-04 11:32:49	ga_ls8c_ard_3-0-0_112075_2017-12-04_final
2017-12-04 11:33:13	ga_ls8c_ard_3-0-0_112076_2017-12-04_final
2017-12-04 11:33:37	ga_ls8c_ard_3-0-0_112077_2017-12-04_final
2017-12-04 11:34:00	ga_ls8c_ard_3-0-0_112078_2017-12-04_final
2017-12-15 11:18:17	ga_ls8c_ard_3-0-0_109085_2017-12-15_final
2017-12-31 11:17:52	ga_ls8c_ard_3-0-0_109084_2017-12-31_final
2017-12-31 11:18:16	ga_ls8c_ard_3-0-0_109085_2017-12-31_final
2018-01-16 11:18:09	ga_ls8c_ard_3-0-0_109085_2018-01-16_final
2018-02-01 11:18:00	ga_ls8c_ard_3-0-0_109085_2018-02-01_final
2018-02-13 11:35:28	ga_ls8c_ard_3-0-0_113067_2018-02-13_final
2018-02-13 11:37:28	ga_ls8c_ard_3-0-0_113072_2018-02-13_final
2018-02-13 11:37:52	ga_ls8c_ard_3-0-0_113073_2018-02-13_final
2018-02-15 11:27:05	ga_ls8c_ard_3-0-0_111077_2018-02-15_final
2018-02-15 11:27:29	ga_ls8c_ard_3-0-0_111078_2018-02-15_final
2018-02-15 11:27:53	ga_ls8c_ard_3-0-0_111079_2018-02-15_final
2018-02-15 11:28:17	ga_ls8c_ard_3-0-0_111080_2018-02-15_final
2018-02-15 11:28:41	ga_ls8c_ard_3-0-0_111081_2018-02-15_final
2018-02-15 11:29:05	ga_ls8c_ard_3-0-0_111082_2018-02-15_final
2018-05-04 11:34:47	ga_ls8c_ard_3-0-0_113067_2018-05-04_final
2018-05-04 11:36:47	ga_ls8c_ard_3-0-0_113072_2018-05-04_final
2018-05-04 11:37:11	ga_ls8c_ard_3-0-0_113073_2018-05-04_final
2018-07-09 11:26:24	ga_ls8c_ard_3-0-0_111077_2018-07-09_final
2018-07-09 11:26:48	ga_ls8c_ard_3-0-0_111078_2018-07-09_final
2018-07-09 11:27:12	ga_ls8c_ard_3-0-0_111079_2018-07-09_final
2018-07-09 11:27:36	ga_ls8c_ard_3-0-0_111080_2018-07-09_final
2018-07-09 11:28:00	ga_ls8c_ard_3-0-0_111081_2018-07-09_final
2018-07-09 11:28:24	ga_ls8c_ard_3-0-0_111082_2018-07-09_final
2018-12-16 11:27:09	ga_ls8c_ard_3-0-0_111077_2018-12-16_final
2018-12-16 11:27:33	ga_ls8c_ard_3-0-0_111078_2018-12-16_final
2018-12-16 11:27:57	ga_ls8c_ard_3-0-0_111079_2018-12-16_final
2018-12-16 11:28:21	ga_ls8c_ard_3-0-0_111080_2018-12-16_final
2018-12-16 11:28:45	ga_ls8c_ard_3-0-0_111081_2018-12-16_final
2018-12-16 11:29:09	ga_ls8c_ard_3-0-0_111082_2018-12-16_final
2019-01-17 11:27:07	ga_ls8c_ard_3-0-0_111077_2019-01-17_final
2019-01-17 11:27:31	ga_ls8c_ard_3-0-0_111078_2019-01-17_final
2019-01-17 11:27:55	ga_ls8c_ard_3-0-0_111079_2019-01-17_final
2019-01-17 11:28:18	ga_ls8c_ard_3-0-0_111080_2019-01-17_final
2019-01-17 11:28:42	ga_ls8c_ard_3-0-0_111081_2019-01-17_final
2019-01-17 11:29:06	ga_ls8c_ard_3-0-0_111082_2019-01-17_final
2022-01-23 11:37:49	ga_ls8c_ard_3-2-1_113072_2022-01-23_final
2022-01-23 11:38:13	ga_ls8c_ard_3-2-1_113073_2022-01-23_final
2022-01-25 11:27:26	ga_ls8c_ard_3-2-1_111077_2022-01-25_final
2022-01-25 11:27:50	ga_ls8c_ard_3-2-1_111078_2022-01-25_final
2022-01-25 11:28:14	ga_ls8c_ard_3-2-1_111079_2022-01-25_final
2022-01-25 11:28:38	ga_ls8c_ard_3-2-1_111080_2022-01-25_final
2022-02-17 11:31:31	ga_ls8c_ard_3-2-1_112072_2022-02-17_final
2022-02-17 11:31:55	ga_ls8c_ard_3-2-1_112073_2022-02-17_final
2022-02-17 11:32:19	ga_ls8c_ard_3-2-1_112074_2022-02-17_final
2022-02-17 11:32:43	ga_ls8c_ard_3-2-1_112075_2022-02-17_final
2022-02-17 11:33:07	ga_ls8c_ard_3-2-1_112076_2022-02-17_final
2022-02-17 11:33:31	ga_ls8c_ard_3-2-1_112077_2022-02-17_final
2022-02-17 11:33:55	ga_ls8c_ard_3-2-1_112078_2022-02-17_final
2022-02-19 11:22:44	ga_ls8c_ard_3-2-1_110081_2022-02-19_final
2022-02-19 11:23:08	ga_ls8c_ard_3-2-1_110082_2022-02-19_final
2022-02-19 11:23:32	ga_ls8c_ard_3-2-1_110083_2022-02-19_final
2022-02-19 11:23:56	ga_ls8c_ard_3-2-1_110084_2022-02-19_final
2022-02-19 11:24:20	ga_ls8c_ard_3-2-1_110085_2022-02-19_final
2022-03-05 11:31:28	ga_ls8c_ard_3-2-1_112072_2022-03-05_final
2022-03-05 11:31:52	ga_ls8c_ard_3-2-1_112073_2022-03-05_final
2022-03-05 11:32:16	ga_ls8c_ard_3-2-1_112074_2022-03-05_final
2022-03-05 11:32:40	ga_ls8c_ard_3-2-1_112075_2022-03-05_final
2022-03-05 11:33:04	ga_ls8c_ard_3-2-1_112076_2022-03-05_final
2022-03-05 11:33:28	ga_ls8c_ard_3-2-1_112077_2022-03-05_final
2022-03-05 11:33:52	ga_ls8c_ard_3-2-1_112078_2022-03-05_final
2022-03-07 11:22:42	ga_ls8c_ard_3-2-1_110081_2022-03-07_final
2022-03-07 11:23:06	ga_ls8c_ard_3-2-1_110082_2022-03-07_final
2022-03-07 11:23:30	ga_ls8c_ard_3-2-1_110083_2022-03-07_final
2022-03-07 11:23:54	ga_ls8c_ard_3-2-1_110084_2022-03-07_final
2022-03-07 11:24:17	ga_ls8c_ard_3-2-1_110085_2022-03-07_final
2022-03-28 11:37:25	ga_ls8c_ard_3-2-1_113072_2022-03-28_final
2022-03-28 11:37:49	ga_ls8c_ard_3-2-1_113073_2022-03-28_final
2022-04-15 11:26:43	ga_ls8c_ard_3-2-1_111076_2022-04-15_final
2022-04-15 11:27:07	ga_ls8c_ard_3-2-1_111077_2022-04-15_final
2022-04-15 11:27:31	ga_ls8c_ard_3-2-1_111078_2022-04-15_final
2022-04-15 11:27:55	ga_ls8c_ard_3-2-1_111079_2022-04-15_final
2022-04-15 11:28:19	ga_ls8c_ard_3-2-1_111080_2022-04-15_final
2022-04-15 11:28:43	ga_ls8c_ard_3-2-1_111081_2022-04-15_final
2022-04-15 11:29:07	ga_ls8c_ard_3-2-1_111082_2022-04-15_final
2022-04-17 11:17:33	ga_ls8c_ard_3-2-1_109084_2022-04-17_final
2022-05-01 11:27:04	ga_ls8c_ard_3-2-1_111077_2022-05-01_final
2022-05-01 11:27:28	ga_ls8c_ard_3-2-1_111078_2022-05-01_final
2022-05-01 11:27:52	ga_ls8c_ard_3-2-1_111079_2022-05-01_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