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
2015-02-26 11:57:11	ga_ls8c_ard_3-0-0_116075_2015-02-26_final
2015-06-18 11:56:17	ga_ls8c_ard_3-0-0_116074_2015-06-18_final
2015-06-18 11:56:41	ga_ls8c_ard_3-0-0_116075_2015-06-18_final
2017-09-20 11:50:58	ga_ls8c_ard_3-0-0_115074_2017-09-20_final
2017-09-20 11:51:22	ga_ls8c_ard_3-0-0_115075_2017-09-20_final
2017-09-20 11:51:45	ga_ls8c_ard_3-0-0_115076_2017-09-20_final
2017-09-20 11:52:09	ga_ls8c_ard_3-0-0_115077_2017-09-20_final
2017-09-20 11:52:33	ga_ls8c_ard_3-0-0_115078_2017-09-20_final
2017-09-20 11:52:57	ga_ls8c_ard_3-0-0_115079_2017-09-20_final
2017-09-20 11:53:21	ga_ls8c_ard_3-0-0_115080_2017-09-20_final
2017-10-06 11:51:04	ga_ls8c_ard_3-0-0_115074_2017-10-06_final
2017-10-06 11:51:28	ga_ls8c_ard_3-0-0_115075_2017-10-06_final
2017-10-06 11:51:52	ga_ls8c_ard_3-0-0_115076_2017-10-06_final
2017-10-06 11:52:16	ga_ls8c_ard_3-0-0_115077_2017-10-06_final
2017-10-06 11:52:40	ga_ls8c_ard_3-0-0_115078_2017-10-06_final
2017-10-06 11:53:04	ga_ls8c_ard_3-0-0_115079_2017-10-06_final
2017-10-06 11:53:28	ga_ls8c_ard_3-0-0_115080_2017-10-06_final
2017-10-13 11:57:16	ga_ls8c_ard_3-0-0_116074_2017-10-13_final
2017-10-13 11:57:40	ga_ls8c_ard_3-0-0_116075_2017-10-13_final
2017-10-15 11:46:31	ga_ls8c_ard_3-0-0_114078_2017-10-15_final
2017-10-15 11:46:55	ga_ls8c_ard_3-0-0_114079_2017-10-15_final
2017-10-15 11:47:19	ga_ls8c_ard_3-0-0_114080_2017-10-15_final
2017-10-15 11:47:43	ga_ls8c_ard_3-0-0_114081_2017-10-15_final
2018-01-03 11:46:22	ga_ls8c_ard_3-0-0_114078_2018-01-03_final
2018-01-03 11:46:46	ga_ls8c_ard_3-0-0_114079_2018-01-03_final
2018-01-03 11:47:10	ga_ls8c_ard_3-0-0_114080_2018-01-03_final
2018-01-03 11:47:34	ga_ls8c_ard_3-0-0_114081_2018-01-03_final
2018-01-10 11:50:54	ga_ls8c_ard_3-0-0_115074_2018-01-10_final
2018-01-10 11:51:18	ga_ls8c_ard_3-0-0_115075_2018-01-10_final
2018-01-10 11:51:42	ga_ls8c_ard_3-0-0_115076_2018-01-10_final
2018-01-10 11:52:06	ga_ls8c_ard_3-0-0_115077_2018-01-10_final
2018-01-10 11:52:30	ga_ls8c_ard_3-0-0_115078_2018-01-10_final
2018-01-10 11:52:54	ga_ls8c_ard_3-0-0_115079_2018-01-10_final
2018-01-10 11:53:18	ga_ls8c_ard_3-0-0_115080_2018-01-10_final
2018-01-12 11:41:43	ga_ls8c_ard_3-0-0_113082_2018-01-12_final
2018-01-12 11:42:07	ga_ls8c_ard_3-0-0_113083_2018-01-12_final
2018-01-12 11:42:31	ga_ls8c_ard_3-0-0_113084_2018-01-12_final
2018-01-26 11:50:45	ga_ls8c_ard_3-0-0_115074_2018-01-26_final
2018-01-26 11:51:09	ga_ls8c_ard_3-0-0_115075_2018-01-26_final
2018-01-26 11:51:33	ga_ls8c_ard_3-0-0_115076_2018-01-26_final
2018-01-26 11:51:57	ga_ls8c_ard_3-0-0_115077_2018-01-26_final
2018-01-26 11:52:21	ga_ls8c_ard_3-0-0_115078_2018-01-26_final
2018-01-26 11:52:45	ga_ls8c_ard_3-0-0_115079_2018-01-26_final
2018-01-26 11:53:09	ga_ls8c_ard_3-0-0_115080_2018-01-26_final
2018-01-28 11:41:58	ga_ls8c_ard_3-0-0_113083_2018-01-28_final
2018-01-28 11:42:22	ga_ls8c_ard_3-0-0_113084_2018-01-28_final
2018-02-11 11:50:38	ga_ls8c_ard_3-0-0_115074_2018-02-11_final
2018-02-11 11:51:02	ga_ls8c_ard_3-0-0_115075_2018-02-11_final
2018-02-11 11:51:26	ga_ls8c_ard_3-0-0_115076_2018-02-11_final
2018-02-11 11:51:50	ga_ls8c_ard_3-0-0_115077_2018-02-11_final
2018-02-11 11:52:14	ga_ls8c_ard_3-0-0_115078_2018-02-11_final
2018-02-11 11:52:38	ga_ls8c_ard_3-0-0_115079_2018-02-11_final
2018-02-11 11:53:02	ga_ls8c_ard_3-0-0_115080_2018-02-11_final
2018-02-13 11:41:51	ga_ls8c_ard_3-0-0_113083_2018-02-13_final
2018-02-13 11:42:15	ga_ls8c_ard_3-0-0_113084_2018-02-13_final
2018-11-01 11:56:54	ga_ls8c_ard_3-0-0_116074_2018-11-01_final
2018-11-01 11:57:18	ga_ls8c_ard_3-0-0_116075_2018-11-01_final
2018-12-12 11:50:41	ga_ls8c_ard_3-0-0_115074_2018-12-12_final
2018-12-12 11:51:05	ga_ls8c_ard_3-0-0_115075_2018-12-12_final
2018-12-12 11:51:29	ga_ls8c_ard_3-0-0_115076_2018-12-12_final
2018-12-12 11:51:53	ga_ls8c_ard_3-0-0_115077_2018-12-12_final
2018-12-12 11:52:17	ga_ls8c_ard_3-0-0_115078_2018-12-12_final
2018-12-12 11:52:40	ga_ls8c_ard_3-0-0_115079_2018-12-12_final
2018-12-12 11:53:04	ga_ls8c_ard_3-0-0_115080_2018-12-12_final
2018-12-14 11:41:54	ga_ls8c_ard_3-0-0_113083_2018-12-14_final
2018-12-14 11:42:18	ga_ls8c_ard_3-0-0_113084_2018-12-14_final
2019-01-20 11:56:48	ga_ls8c_ard_3-0-0_116074_2019-01-20_final
2019-01-20 11:57:12	ga_ls8c_ard_3-0-0_116075_2019-01-20_final
2023-07-28 11:46:02	ga_ls8c_ard_3-2-1_114078_2023-07-28_final
2023-07-28 11:46:26	ga_ls8c_ard_3-2-1_114079_2023-07-28_final
2023-07-28 11:46:50	ga_ls8c_ard_3-2-1_114080_2023-07-28_final
2023-07-28 11:47:13	ga_ls8c_ard_3-2-1_114081_2023-07-28_final
2023-08-04 11:50:40	ga_ls8c_ard_3-2-1_115074_2023-08-04_final
2023-08-04 11:51:04	ga_ls8c_ard_3-2-1_115075_2023-08-04_final
2023-08-04 11:51:28	ga_ls8c_ard_3-2-1_115076_2023-08-04_final
2023-08-04 11:51:52	ga_ls8c_ard_3-2-1_115077_2023-08-04_final
2023-08-04 11:52:16	ga_ls8c_ard_3-2-1_115078_2023-08-04_final
2023-08-04 11:52:39	ga_ls8c_ard_3-2-1_115079_2023-08-04_final
2023-08-04 11:53:03	ga_ls8c_ard_3-2-1_115080_2023-08-04_final
2023-08-06 11:41:30	ga_ls8c_ard_3-2-1_113082_2023-08-06_final
2023-08-06 11:41:54	ga_ls8c_ard_3-2-1_113083_2023-08-06_final
2023-08-06 11:42:18	ga_ls8c_ard_3-2-1_113084_2023-08-06_final
2023-08-11 11:57:14	ga_ls8c_ard_3-2-1_116075_2023-08-11_final
2023-08-13 11:46:07	ga_ls8c_ard_3-2-1_114078_2023-08-13_final
2023-08-13 11:46:30	ga_ls8c_ard_3-2-1_114079_2023-08-13_final
2023-08-13 11:46:54	ga_ls8c_ard_3-2-1_114080_2023-08-13_final
2023-08-13 11:47:18	ga_ls8c_ard_3-2-1_114081_2023-08-13_final
2023-09-05 11:50:47	ga_ls8c_ard_3-2-1_115074_2023-09-05_final
2023-09-05 11:51:11	ga_ls8c_ard_3-2-1_115075_2023-09-05_final
2023-09-05 11:51:34	ga_ls8c_ard_3-2-1_115076_2023-09-05_final
2023-09-05 11:51:58	ga_ls8c_ard_3-2-1_115077_2023-09-05_final
2023-09-05 11:52:22	ga_ls8c_ard_3-2-1_115078_2023-09-05_final
2023-09-05 11:52:46	ga_ls8c_ard_3-2-1_115079_2023-09-05_final
2023-09-05 11:53:10	ga_ls8c_ard_3-2-1_115080_2023-09-05_final
2023-10-07 11:50:56	ga_ls8c_ard_3-2-1_115074_2023-10-07_final
2023-10-07 11:51:20	ga_ls8c_ard_3-2-1_115075_2023-10-07_final
2023-10-07 11:51:44	ga_ls8c_ard_3-2-1_115076_2023-10-07_final
2023-10-07 11:52:08	ga_ls8c_ard_3-2-1_115077_2023-10-07_final
2023-10-07 11:52:32	ga_ls8c_ard_3-2-1_115078_2023-10-07_final
2023-10-07 11:52:56	ga_ls8c_ard_3-2-1_115079_2023-10-07_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