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
2017-10-24 11:37:57	ga_ls8c_ard_3-0-0_113072_2017-10-24_final
2017-10-24 11:38:21	ga_ls8c_ard_3-0-0_113073_2017-10-24_final
2017-10-24 11:38:45	ga_ls8c_ard_3-0-0_113074_2017-10-24_final
2017-10-24 11:39:09	ga_ls8c_ard_3-0-0_113075_2017-10-24_final
2017-10-24 11:39:33	ga_ls8c_ard_3-0-0_113076_2017-10-24_final
2017-10-24 11:39:57	ga_ls8c_ard_3-0-0_113077_2017-10-24_final
2017-10-24 11:40:21	ga_ls8c_ard_3-0-0_113078_2017-10-24_final
2017-11-09 11:37:55	ga_ls8c_ard_3-0-0_113072_2017-11-09_final
2017-11-09 11:38:19	ga_ls8c_ard_3-0-0_113073_2017-11-09_final
2017-11-09 11:38:43	ga_ls8c_ard_3-0-0_113074_2017-11-09_final
2017-11-09 11:39:07	ga_ls8c_ard_3-0-0_113075_2017-11-09_final
2017-11-09 11:39:31	ga_ls8c_ard_3-0-0_113076_2017-11-09_final
2017-11-09 11:39:55	ga_ls8c_ard_3-0-0_113077_2017-11-09_final
2017-11-09 11:40:19	ga_ls8c_ard_3-0-0_113078_2017-11-09_final
2017-11-11 11:29:09	ga_ls8c_ard_3-0-0_111081_2017-11-11_final
2017-11-11 11:29:33	ga_ls8c_ard_3-0-0_111082_2017-11-11_final
2017-11-11 11:29:57	ga_ls8c_ard_3-0-0_111083_2017-11-11_final
2017-11-11 11:30:21	ga_ls8c_ard_3-0-0_111084_2017-11-11_final
2017-11-11 11:30:45	ga_ls8c_ard_3-0-0_111085_2017-11-11_final
2017-12-13 11:29:02	ga_ls8c_ard_3-0-0_111081_2017-12-13_final
2017-12-13 11:29:26	ga_ls8c_ard_3-0-0_111082_2017-12-13_final
2017-12-13 11:29:50	ga_ls8c_ard_3-0-0_111083_2017-12-13_final
2017-12-13 11:30:14	ga_ls8c_ard_3-0-0_111084_2017-12-13_final
2017-12-13 11:30:38	ga_ls8c_ard_3-0-0_111085_2017-12-13_final
2017-12-27 11:37:50	ga_ls8c_ard_3-0-0_113072_2017-12-27_final
2017-12-27 11:38:14	ga_ls8c_ard_3-1-0_113073_2017-12-27_final
2017-12-27 11:38:37	ga_ls8c_ard_3-0-0_113074_2017-12-27_final
2017-12-27 11:39:01	ga_ls8c_ard_3-0-0_113075_2017-12-27_final
2017-12-27 11:39:25	ga_ls8c_ard_3-0-0_113076_2017-12-27_final
2017-12-27 11:39:49	ga_ls8c_ard_3-0-0_113077_2017-12-27_final
2017-12-27 11:40:13	ga_ls8c_ard_3-0-0_113078_2017-12-27_final
2017-12-29 11:29:03	ga_ls8c_ard_3-0-0_111081_2017-12-29_final
2017-12-29 11:29:27	ga_ls8c_ard_3-0-0_111082_2017-12-29_final
2017-12-29 11:29:51	ga_ls8c_ard_3-0-0_111083_2017-12-29_final
2017-12-29 11:30:15	ga_ls8c_ard_3-0-0_111084_2017-12-29_final
2017-12-29 11:30:39	ga_ls8c_ard_3-0-0_111085_2017-12-29_final
2018-01-12 11:37:43	ga_ls8c_ard_3-0-0_113072_2018-01-12_final
2018-01-12 11:38:07	ga_ls8c_ard_3-0-0_113073_2018-01-12_final
2018-01-12 11:38:31	ga_ls8c_ard_3-0-0_113074_2018-01-12_final
2018-01-12 11:38:55	ga_ls8c_ard_3-0-0_113075_2018-01-12_final
2018-01-12 11:39:19	ga_ls8c_ard_3-0-0_113076_2018-01-12_final
2018-01-12 11:39:43	ga_ls8c_ard_3-0-0_113077_2018-01-12_final
2018-01-12 11:40:07	ga_ls8c_ard_3-0-0_113078_2018-01-12_final
2018-01-14 11:28:56	ga_ls8c_ard_3-0-0_111081_2018-01-14_final
2018-01-14 11:29:20	ga_ls8c_ard_3-0-0_111082_2018-01-14_final
2018-01-14 11:29:44	ga_ls8c_ard_3-0-0_111083_2018-01-14_final
2018-01-14 11:30:08	ga_ls8c_ard_3-0-0_111084_2018-01-14_final
2018-01-14 11:30:32	ga_ls8c_ard_3-0-0_111085_2018-01-14_final
2018-01-28 11:37:58	ga_ls8c_ard_3-1-0_113073_2018-01-28_final
2018-01-28 11:38:22	ga_ls8c_ard_3-0-0_113074_2018-01-28_final
2018-01-28 11:38:46	ga_ls8c_ard_3-0-0_113075_2018-01-28_final
2018-01-28 11:39:10	ga_ls8c_ard_3-0-0_113076_2018-01-28_final
2018-01-28 11:39:34	ga_ls8c_ard_3-0-0_113077_2018-01-28_final
2018-01-28 11:39:58	ga_ls8c_ard_3-0-0_113078_2018-01-28_final
2023-10-25 11:38:14	ga_ls8c_ard_3-2-1_113073_2023-10-25_final
2023-10-27 11:29:05	ga_ls8c_ard_3-2-1_111081_2023-10-27_final
2023-10-27 11:29:29	ga_ls8c_ard_3-2-1_111082_2023-10-27_final
2023-10-27 11:29:53	ga_ls8c_ard_3-2-1_111083_2023-10-27_final
2023-10-27 11:30:17	ga_ls8c_ard_3-2-1_111084_2023-10-27_final
2023-11-03 11:33:40	ga_ls8c_ard_3-2-1_112077_2023-11-03_final
2023-11-03 11:34:04	ga_ls8c_ard_3-2-1_112078_2023-11-03_final
2023-11-03 11:34:28	ga_ls8c_ard_3-2-1_112079_2023-11-03_final
2023-11-03 11:34:52	ga_ls8c_ard_3-2-1_112080_2023-11-03_final
2023-11-03 11:35:16	ga_ls8c_ard_3-2-1_112081_2023-11-03_final
2023-11-03 11:35:40	ga_ls8c_ard_3-2-1_112082_2023-11-03_final
2023-11-05 11:24:29	ga_ls8c_ard_3-2-1_110085_2023-11-05_final
2023-11-12 11:29:02	ga_ls8c_ard_3-2-1_111081_2023-11-12_final
2023-11-12 11:29:26	ga_ls8c_ard_3-2-1_111082_2023-11-12_final
2023-11-12 11:29:50	ga_ls8c_ard_3-2-1_111083_2023-11-12_final
2023-11-12 11:30:14	ga_ls8c_ard_3-2-1_111084_2023-11-12_final
2023-11-19 11:33:41	ga_ls8c_ard_3-2-1_112077_2023-11-19_final
2023-11-19 11:34:05	ga_ls8c_ard_3-2-1_112078_2023-11-19_final
2023-11-19 11:34:29	ga_ls8c_ard_3-2-1_112079_2023-11-19_final
2023-11-19 11:34:53	ga_ls8c_ard_3-2-1_112080_2023-11-19_final
2023-11-19 11:35:17	ga_ls8c_ard_3-2-1_112081_2023-11-19_final
2023-11-19 11:35:41	ga_ls8c_ard_3-2-1_112082_2023-11-19_final
2023-11-26 11:37:54	ga_ls8c_ard_3-2-1_113072_2023-11-26_final
2023-11-26 11:38:18	ga_ls8c_ard_3-2-1_113073_2023-11-26_final
2023-11-26 11:38:42	ga_ls8c_ard_3-2-1_113074_2023-11-26_final
2023-11-26 11:39:06	ga_ls8c_ard_3-2-1_113075_2023-11-26_final
2023-11-26 11:39:29	ga_ls8c_ard_3-2-1_113076_2023-11-26_final
2023-11-26 11:39:53	ga_ls8c_ard_3-2-1_113077_2023-11-26_final
2023-11-26 11:40:17	ga_ls8c_ard_3-2-1_113078_2023-11-26_final
2024-02-07 11:33:34	ga_ls8c_ard_3-2-1_112077_2024-02-07_final
2024-02-07 11:33:58	ga_ls8c_ard_3-2-1_112078_2024-02-07_final
2024-02-07 11:34:22	ga_ls8c_ard_3-2-1_112079_2024-02-07_final
2024-02-07 11:34:46	ga_ls8c_ard_3-2-1_112080_2024-02-07_final
2024-02-07 11:35:10	ga_ls8c_ard_3-2-1_112081_2024-02-07_final
2024-02-07 11:35:34	ga_ls8c_ard_3-2-1_112082_2024-02-07_final
2024-02-25 11:24:20	ga_ls8c_ard_3-2-1_110085_2024-02-25_final
2024-03-01 11:37:37	ga_ls8c_ard_3-2-1_113072_2024-03-01_final
2024-03-01 11:38:01	ga_ls8c_ard_3-2-1_113073_2024-03-01_final
2024-03-01 11:38:25	ga_ls8c_ard_3-2-1_113074_2024-03-01_final
2024-03-01 11:38:49	ga_ls8c_ard_3-2-1_113075_2024-03-01_final
2024-03-01 11:39:13	ga_ls8c_ard_3-2-1_113076_2024-03-01_final
2024-03-01 11:39:37	ga_ls8c_ard_3-2-1_113077_2024-03-01_final
2024-03-01 11:40:01	ga_ls8c_ard_3-2-1_113078_2024-03-01_final
2024-03-03 11:28:49	ga_ls8c_ard_3-2-1_111081_2024-03-03_final
2024-03-03 11:29:13	ga_ls8c_ard_3-2-1_111082_2024-03-03_final
2024-03-03 11:29:37	ga_ls8c_ard_3-2-1_111083_2024-03-03_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