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
2019-01-26 11:17:18	ga_ls8c_ard_3-0-0_110068_2019-01-26_final
2019-01-26 11:17:42	ga_ls8c_ard_3-0-0_110069_2019-01-26_final
2019-01-26 11:18:06	ga_ls8c_ard_3-0-0_110070_2019-01-26_final
2019-01-26 11:18:30	ga_ls8c_ard_3-0-0_110071_2019-01-26_final
2019-01-26 11:18:54	ga_ls8c_ard_3-0-0_110072_2019-01-26_final
2019-01-26 11:19:18	ga_ls8c_ard_3-0-0_110073_2019-01-26_final
2019-01-26 11:19:42	ga_ls8c_ard_3-0-0_110074_2019-01-26_final
2019-01-28 11:08:31	ga_ls8c_ard_3-0-0_108077_2019-01-28_final
2019-01-28 11:08:55	ga_ls8c_ard_3-0-0_108078_2019-01-28_final
2019-01-28 11:09:19	ga_ls8c_ard_3-0-0_108079_2019-01-28_final
2019-01-28 11:09:43	ga_ls8c_ard_3-0-0_108080_2019-01-28_final
2019-01-28 11:10:07	ga_ls8c_ard_3-0-0_108081_2019-01-28_final
2019-01-28 11:10:31	ga_ls8c_ard_3-0-0_108082_2019-01-28_final
2019-02-06 11:03:55	ga_ls8c_ard_3-0-0_107081_2019-02-06_final
2019-02-06 11:04:19	ga_ls8c_ard_3-1-0_107082_2019-02-06_final
2019-02-06 11:04:43	ga_ls8c_ard_3-0-0_107083_2019-02-06_final
2019-02-06 11:05:07	ga_ls8c_ard_3-0-0_107084_2019-02-06_final
2019-02-06 11:05:31	ga_ls8c_ard_3-0-0_107085_2019-02-06_final
2019-03-31 11:17:03	ga_ls8c_ard_3-1-0_110068_2019-03-31_final
2019-03-31 11:17:27	ga_ls8c_ard_3-1-0_110069_2019-03-31_final
2019-03-31 11:17:51	ga_ls8c_ard_3-1-0_110070_2019-03-31_final
2019-03-31 11:18:15	ga_ls8c_ard_3-1-0_110071_2019-03-31_final
2019-04-02 11:08:17	ga_ls8c_ard_3-1-0_108077_2019-04-02_final
2019-04-02 11:08:41	ga_ls8c_ard_3-1-0_108078_2019-04-02_final
2019-04-02 11:09:05	ga_ls8c_ard_3-1-0_108079_2019-04-02_final
2019-04-02 11:09:29	ga_ls8c_ard_3-1-0_108080_2019-04-02_final
2019-04-02 11:09:52	ga_ls8c_ard_3-1-0_108081_2019-04-02_final
2019-04-02 11:10:16	ga_ls8c_ard_3-1-0_108082_2019-04-02_final
2019-06-05 11:08:30	ga_ls8c_ard_3-0-0_108077_2019-06-05_final
2019-06-05 11:08:54	ga_ls8c_ard_3-0-0_108078_2019-06-05_final
2019-06-05 11:09:18	ga_ls8c_ard_3-0-0_108079_2019-06-05_final
2019-06-05 11:09:42	ga_ls8c_ard_3-0-0_108080_2019-06-05_final
2019-06-05 11:10:06	ga_ls8c_ard_3-0-0_108081_2019-06-05_final
2019-06-05 11:10:30	ga_ls8c_ard_3-0-0_108082_2019-06-05_final
2020-04-09 11:22:56	ga_ls8c_ard_3-1-0_111067_2020-04-09_final
2020-04-09 11:23:20	ga_ls8c_ard_3-1-0_111068_2020-04-09_final
2020-04-09 11:23:44	ga_ls8c_ard_3-1-0_111069_2020-04-09_final
2020-04-11 11:12:57	ga_ls8c_ard_3-1-0_109073_2020-04-11_final
2020-04-11 11:13:21	ga_ls8c_ard_3-1-0_109074_2020-04-11_final
2020-04-11 11:13:45	ga_ls8c_ard_3-1-0_109075_2020-04-11_final
2020-04-11 11:14:09	ga_ls8c_ard_3-1-0_109076_2020-04-11_final
2020-04-11 11:14:33	ga_ls8c_ard_3-1-0_109077_2020-04-11_final
2020-04-11 11:14:57	ga_ls8c_ard_3-1-0_109078_2020-04-11_final
2020-04-13 11:03:46	ga_ls8c_ard_3-1-0_107081_2020-04-13_final
2020-04-13 11:04:10	ga_ls8c_ard_3-1-0_107082_2020-04-13_final
2020-04-13 11:04:34	ga_ls8c_ard_3-1-0_107083_2020-04-13_final
2020-04-13 11:04:58	ga_ls8c_ard_3-1-0_107084_2020-04-13_final
2020-04-13 11:05:22	ga_ls8c_ard_3-1-0_107085_2020-04-13_final
2020-04-27 11:12:50	ga_ls8c_ard_3-1-0_109073_2020-04-27_final
2020-04-27 11:13:14	ga_ls8c_ard_3-1-0_109074_2020-04-27_final
2020-04-27 11:13:38	ga_ls8c_ard_3-1-0_109075_2020-04-27_final
2020-04-27 11:14:02	ga_ls8c_ard_3-1-0_109076_2020-04-27_final
2020-04-27 11:14:25	ga_ls8c_ard_3-1-0_109077_2020-04-27_final
2020-04-27 11:14:49	ga_ls8c_ard_3-1-0_109078_2020-04-27_final
2020-06-05 11:17:03	ga_ls8c_ard_3-1-0_110068_2020-06-05_final
2020-06-05 11:17:27	ga_ls8c_ard_3-1-0_110069_2020-06-05_final
2020-06-05 11:17:51	ga_ls8c_ard_3-1-0_110070_2020-06-05_final
2020-06-05 11:18:15	ga_ls8c_ard_3-1-0_110071_2020-06-05_final
2020-06-05 11:18:39	ga_ls8c_ard_3-1-0_110072_2020-06-05_final
2020-06-05 11:19:03	ga_ls8c_ard_3-1-0_110073_2020-06-05_final
2020-06-07 11:08:18	ga_ls8c_ard_3-1-0_108077_2020-06-07_final
2020-06-07 11:08:42	ga_ls8c_ard_3-1-0_108078_2020-06-07_final
2020-06-07 11:09:06	ga_ls8c_ard_3-1-0_108079_2020-06-07_final
2020-06-07 11:09:30	ga_ls8c_ard_3-1-0_108080_2020-06-07_final
2020-06-07 11:09:54	ga_ls8c_ard_3-1-0_108081_2020-06-07_final
2020-06-07 11:10:18	ga_ls8c_ard_3-1-0_108082_2020-06-07_final
2020-06-12 11:22:55	ga_ls8c_ard_3-1-0_111067_2020-06-12_final
2020-06-12 11:23:18	ga_ls8c_ard_3-1-0_111068_2020-06-12_final
2020-06-12 11:23:42	ga_ls8c_ard_3-1-0_111069_2020-06-12_final
2020-06-14 11:12:58	ga_ls8c_ard_3-1-0_109073_2020-06-14_final
2020-06-14 11:13:22	ga_ls8c_ard_3-1-0_109074_2020-06-14_final
2020-06-14 11:13:45	ga_ls8c_ard_3-1-0_109075_2020-06-14_final
2020-06-14 11:14:09	ga_ls8c_ard_3-1-0_109076_2020-06-14_final
2020-06-14 11:14:33	ga_ls8c_ard_3-1-0_109077_2020-06-14_final
2020-06-14 11:14:57	ga_ls8c_ard_3-1-0_109078_2020-06-14_final
2023-02-01 11:04:32	ga_ls8c_ard_3-2-1_107081_2023-02-01_final
2023-02-01 11:04:56	ga_ls8c_ard_3-2-1_107082_2023-02-01_final
2023-02-01 11:05:20	ga_ls8c_ard_3-2-1_107083_2023-02-01_final
2023-02-01 11:05:44	ga_ls8c_ard_3-2-1_107084_2023-02-01_final
2023-04-04 11:13:03	ga_ls8c_ard_3-2-1_109073_2023-04-04_final
2023-04-04 11:13:27	ga_ls8c_ard_3-2-1_109074_2023-04-04_final
2023-04-04 11:13:51	ga_ls8c_ard_3-2-1_109075_2023-04-04_final
2023-04-04 11:14:15	ga_ls8c_ard_3-2-1_109076_2023-04-04_final
2023-04-04 11:14:39	ga_ls8c_ard_3-2-1_109077_2023-04-04_final
2023-04-04 11:15:03	ga_ls8c_ard_3-2-1_109078_2023-04-04_final
2023-04-06 11:03:50	ga_ls8c_ard_3-2-1_107081_2023-04-06_final
2023-04-06 11:04:14	ga_ls8c_ard_3-2-1_107082_2023-04-06_final
2023-04-06 11:04:38	ga_ls8c_ard_3-2-1_107083_2023-04-06_final
2023-04-06 11:05:02	ga_ls8c_ard_3-2-1_107084_2023-04-06_final
2023-04-18 11:23:13	ga_ls8c_ard_3-2-1_111068_2023-04-18_final
2023-04-18 11:23:37	ga_ls8c_ard_3-2-1_111069_2023-04-18_final
2023-05-31 11:08:03	ga_ls8c_ard_3-2-1_108077_2023-05-31_final
2023-05-31 11:08:27	ga_ls8c_ard_3-2-1_108078_2023-05-31_final
2023-05-31 11:08:51	ga_ls8c_ard_3-2-1_108079_2023-05-31_final
2023-05-31 11:09:15	ga_ls8c_ard_3-2-1_108080_2023-05-31_final
2023-05-31 11:09:39	ga_ls8c_ard_3-2-1_108081_2023-05-31_final
2023-05-31 11:10:03	ga_ls8c_ard_3-2-1_108082_2023-05-31_final
2023-06-09 11:03:34	ga_ls8c_ard_3-2-1_107081_2023-06-09_final
2023-06-09 11:03:58	ga_ls8c_ard_3-2-1_107082_2023-06-09_final
2023-06-09 11:04:22	ga_ls8c_ard_3-2-1_107083_2023-06-09_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