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
2018-09-27 11:26:59	ga_ls8c_ard_3-0-0_111077_2018-09-27_final
2018-09-27 11:27:23	ga_ls8c_ard_3-0-0_111078_2018-09-27_final
2018-09-27 11:27:47	ga_ls8c_ard_3-0-0_111079_2018-09-27_final
2018-09-27 11:28:11	ga_ls8c_ard_3-0-0_111080_2018-09-27_final
2018-09-27 11:28:35	ga_ls8c_ard_3-0-0_111081_2018-09-27_final
2018-09-27 11:28:59	ga_ls8c_ard_3-0-0_111082_2018-09-27_final
2018-09-27 11:29:23	ga_ls8c_ard_3-0-0_111083_2018-09-27_final
2018-09-29 11:17:50	ga_ls8c_ard_3-0-0_109085_2018-09-29_final
2018-10-04 11:31:38	ga_ls8c_ard_3-0-0_112073_2018-10-04_final
2018-10-04 11:32:02	ga_ls8c_ard_3-0-0_112074_2018-10-04_final
2018-10-04 11:32:26	ga_ls8c_ard_3-0-0_112075_2018-10-04_final
2018-10-04 11:32:49	ga_ls8c_ard_3-0-0_112076_2018-10-04_final
2018-10-04 11:33:13	ga_ls8c_ard_3-0-0_112077_2018-10-04_final
2018-10-04 11:33:37	ga_ls8c_ard_3-0-0_112078_2018-10-04_final
2018-10-04 11:34:01	ga_ls8c_ard_3-0-0_112079_2018-10-04_final
2018-10-06 11:22:29	ga_ls8c_ard_3-0-0_110081_2018-10-06_final
2018-10-06 11:22:52	ga_ls8c_ard_3-0-0_110082_2018-10-06_final
2018-10-06 11:23:16	ga_ls8c_ard_3-0-0_110083_2018-10-06_final
2018-10-06 11:23:40	ga_ls8c_ard_3-0-0_110084_2018-10-06_final
2018-10-06 11:24:04	ga_ls8c_ard_3-0-0_110085_2018-10-06_final
2018-10-29 11:27:11	ga_ls8c_ard_3-0-0_111077_2018-10-29_final
2018-10-29 11:27:35	ga_ls8c_ard_3-0-0_111078_2018-10-29_final
2018-10-29 11:27:59	ga_ls8c_ard_3-0-0_111079_2018-10-29_final
2018-10-29 11:28:23	ga_ls8c_ard_3-0-0_111080_2018-10-29_final
2018-10-29 11:28:47	ga_ls8c_ard_3-0-0_111081_2018-10-29_final
2018-10-29 11:29:11	ga_ls8c_ard_3-0-0_111082_2018-10-29_final
2018-10-29 11:29:35	ga_ls8c_ard_3-0-0_111083_2018-10-29_final
2018-10-31 11:18:02	ga_ls8c_ard_3-0-0_109085_2018-10-31_final
2018-11-30 11:27:12	ga_ls8c_ard_3-0-0_111077_2018-11-30_final
2018-11-30 11:27:36	ga_ls8c_ard_3-0-0_111078_2018-11-30_final
2018-11-30 11:28:00	ga_ls8c_ard_3-0-0_111079_2018-11-30_final
2018-11-30 11:28:24	ga_ls8c_ard_3-0-0_111080_2018-11-30_final
2018-11-30 11:28:48	ga_ls8c_ard_3-0-0_111081_2018-11-30_final
2018-11-30 11:29:12	ga_ls8c_ard_3-0-0_111082_2018-11-30_final
2018-11-30 11:29:36	ga_ls8c_ard_3-0-0_111083_2018-11-30_final
2018-12-02 11:18:02	ga_ls8c_ard_3-0-0_109085_2018-12-02_final
2019-01-01 11:27:09	ga_ls8c_ard_3-0-0_111077_2019-01-01_final
2019-01-01 11:27:33	ga_ls8c_ard_3-0-0_111078_2019-01-01_final
2019-01-01 11:27:57	ga_ls8c_ard_3-0-0_111079_2019-01-01_final
2019-01-01 11:28:21	ga_ls8c_ard_3-0-0_111080_2019-01-01_final
2019-01-01 11:28:45	ga_ls8c_ard_3-0-0_111081_2019-01-01_final
2019-01-01 11:29:09	ga_ls8c_ard_3-0-0_111082_2019-01-01_final
2019-01-01 11:29:33	ga_ls8c_ard_3-0-0_111083_2019-01-01_final
2019-01-03 11:17:59	ga_ls8c_ard_3-0-0_109085_2019-01-03_final
2019-03-04 11:36:55	ga_ls8c_ard_3-0-0_113071_2019-03-04_final
2019-03-04 11:37:19	ga_ls8c_ard_3-0-0_113072_2019-03-04_final
2019-03-04 11:37:43	ga_ls8c_ard_3-1-0_113073_2019-03-04_final
2019-03-11 11:41:27	ga_ls8c_ard_3-1-0_114067_2019-03-11_final
2019-03-13 11:31:28	ga_ls8c_ard_3-1-0_112073_2019-03-13_final
2019-03-13 11:31:52	ga_ls8c_ard_3-1-0_112074_2019-03-13_final
2019-03-13 11:32:16	ga_ls8c_ard_3-1-0_112075_2019-03-13_final
2019-03-13 11:32:40	ga_ls8c_ard_3-1-0_112076_2019-03-13_final
2019-03-13 11:33:04	ga_ls8c_ard_3-1-0_112077_2019-03-13_final
2019-03-13 11:33:28	ga_ls8c_ard_3-1-0_112078_2019-03-13_final
2019-03-13 11:33:52	ga_ls8c_ard_3-1-0_112079_2019-03-13_final
2019-04-30 11:31:17	ga_ls8c_ard_3-0-0_112073_2019-04-30_final
2019-04-30 11:31:41	ga_ls8c_ard_3-0-0_112074_2019-04-30_final
2019-04-30 11:32:05	ga_ls8c_ard_3-0-0_112075_2019-04-30_final
2019-04-30 11:32:29	ga_ls8c_ard_3-0-0_112076_2019-04-30_final
2019-04-30 11:32:53	ga_ls8c_ard_3-0-0_112077_2019-04-30_final
2019-04-30 11:33:17	ga_ls8c_ard_3-0-0_112078_2019-04-30_final
2019-04-30 11:33:41	ga_ls8c_ard_3-0-0_112079_2019-04-30_final
2019-07-17 11:41:47	ga_ls8c_ard_3-1-0_114067_2019-07-17_final
2019-11-01 11:27:40	ga_ls8c_ard_3-1-0_111077_2019-11-01_final
2019-11-01 11:28:04	ga_ls8c_ard_3-1-0_111078_2019-11-01_final
2019-11-01 11:28:28	ga_ls8c_ard_3-1-0_111079_2019-11-01_final
2019-11-01 11:28:52	ga_ls8c_ard_3-1-0_111080_2019-11-01_final
2019-11-01 11:29:16	ga_ls8c_ard_3-1-0_111081_2019-11-01_final
2019-11-01 11:29:40	ga_ls8c_ard_3-1-0_111082_2019-11-01_final
2019-11-01 11:30:04	ga_ls8c_ard_3-1-0_111083_2019-11-01_final
2019-11-17 11:27:37	ga_ls8c_ard_3-1-0_111077_2019-11-17_final
2019-11-17 11:28:01	ga_ls8c_ard_3-1-0_111078_2019-11-17_final
2019-11-17 11:28:25	ga_ls8c_ard_3-1-0_111079_2019-11-17_final
2019-11-17 11:28:49	ga_ls8c_ard_3-1-0_111080_2019-11-17_final
2019-11-17 11:29:13	ga_ls8c_ard_3-1-0_111081_2019-11-17_final
2019-11-17 11:29:37	ga_ls8c_ard_3-1-0_111082_2019-11-17_final
2019-11-17 11:30:01	ga_ls8c_ard_3-1-0_111083_2019-11-17_final
2020-01-06 11:18:19	ga_ls8c_ard_3-1-0_109085_2020-01-06_final
2020-02-23 11:18:07	ga_ls8c_ard_3-1-0_109085_2020-02-23_final
2023-02-04 11:32:15	ga_ls8c_ard_3-2-1_112073_2023-02-04_final
2023-02-04 11:32:39	ga_ls8c_ard_3-2-1_112074_2023-02-04_final
2023-02-04 11:33:03	ga_ls8c_ard_3-2-1_112075_2023-02-04_final
2023-02-04 11:33:27	ga_ls8c_ard_3-2-1_112076_2023-02-04_final
2023-02-04 11:33:50	ga_ls8c_ard_3-2-1_112077_2023-02-04_final
2023-02-04 11:34:14	ga_ls8c_ard_3-2-1_112078_2023-02-04_final
2023-02-11 11:37:58	ga_ls8c_ard_3-2-1_113072_2023-02-11_final
2023-02-11 11:38:22	ga_ls8c_ard_3-2-1_113073_2023-02-11_final
2023-02-11 11:38:46	ga_ls8c_ard_3-2-1_113074_2023-02-11_final
2023-02-20 11:32:26	ga_ls8c_ard_3-2-1_112074_2023-02-20_final
2023-02-20 11:32:50	ga_ls8c_ard_3-2-1_112075_2023-02-20_final
2023-02-20 11:33:14	ga_ls8c_ard_3-2-1_112076_2023-02-20_final
2023-02-20 11:33:38	ga_ls8c_ard_3-2-1_112077_2023-02-20_final
2023-02-20 11:34:02	ga_ls8c_ard_3-2-1_112078_2023-02-20_final
2023-02-20 11:34:26	ga_ls8c_ard_3-2-1_112079_2023-02-20_final
2023-02-22 11:23:13	ga_ls8c_ard_3-2-1_110082_2023-02-22_final
2023-02-22 11:23:37	ga_ls8c_ard_3-2-1_110083_2023-02-22_final
2023-02-22 11:24:01	ga_ls8c_ard_3-2-1_110084_2023-02-22_final
2023-02-22 11:24:25	ga_ls8c_ard_3-2-1_110085_2023-02-22_final
2023-02-27 11:37:42	ga_ls8c_ard_3-2-1_113072_2023-02-27_final
2023-02-27 11:38:06	ga_ls8c_ard_3-2-1_113073_2023-02-27_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