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
2016-10-02 11:05:00	ga_ls8c_ard_3-0-0_108067_2016-10-02_final
2016-10-02 11:05:24	ga_ls8c_ard_3-0-0_108068_2016-10-02_final
2016-10-18 11:05:05	ga_ls8c_ard_3-0-0_108067_2016-10-18_final
2016-10-18 11:05:29	ga_ls8c_ard_3-0-0_108068_2016-10-18_final
2016-10-18 11:05:53	ga_ls8c_ard_3-0-0_108069_2016-10-18_final
2016-10-18 11:06:17	ga_ls8c_ard_3-0-0_108070_2016-10-18_final
2016-11-19 11:05:05	ga_ls8c_ard_3-0-0_108067_2016-11-19_final
2016-11-19 11:05:29	ga_ls8c_ard_3-0-0_108068_2016-11-19_final
2016-11-19 11:05:53	ga_ls8c_ard_3-0-0_108069_2016-11-19_final
2016-11-19 11:06:17	ga_ls8c_ard_3-0-0_108070_2016-11-19_final
2016-11-21 10:55:31	ga_ls8c_ard_3-0-0_106074_2016-11-21_final
2016-11-21 10:55:55	ga_ls8c_ard_3-0-0_106075_2016-11-21_final
2016-11-21 10:56:19	ga_ls8c_ard_3-0-0_106076_2016-11-21_final
2016-11-21 10:56:43	ga_ls8c_ard_3-0-0_106077_2016-11-21_final
2016-11-21 10:57:07	ga_ls8c_ard_3-0-0_106078_2016-11-21_final
2016-11-21 10:57:31	ga_ls8c_ard_3-0-0_106079_2016-11-21_final
2016-11-21 10:57:55	ga_ls8c_ard_3-0-0_106080_2016-11-21_final
2016-11-23 10:46:45	ga_ls8c_ard_3-0-0_104083_2016-11-23_final
2017-07-26 10:59:41	ga_ls8c_ard_3-0-0_107070_2017-07-26_final
2017-07-26 11:00:05	ga_ls8c_ard_3-0-0_107071_2017-07-26_final
2017-07-26 11:00:29	ga_ls8c_ard_3-0-0_107072_2017-07-26_final
2017-07-26 11:00:53	ga_ls8c_ard_3-0-0_107073_2017-07-26_final
2017-07-26 11:01:17	ga_ls8c_ard_3-0-0_107074_2017-07-26_final
2017-07-26 11:01:41	ga_ls8c_ard_3-0-0_107075_2017-07-26_final
2017-08-20 10:55:15	ga_ls8c_ard_3-0-0_106074_2017-08-20_final
2017-08-20 10:55:39	ga_ls8c_ard_3-0-0_106075_2017-08-20_final
2017-08-20 10:56:03	ga_ls8c_ard_3-0-0_106076_2017-08-20_final
2017-08-20 10:56:27	ga_ls8c_ard_3-0-0_106077_2017-08-20_final
2017-08-20 10:56:51	ga_ls8c_ard_3-0-0_106078_2017-08-20_final
2017-08-20 10:57:15	ga_ls8c_ard_3-0-0_106079_2017-08-20_final
2017-08-20 10:57:39	ga_ls8c_ard_3-0-0_106080_2017-08-20_final
2017-08-22 10:46:30	ga_ls8c_ard_3-0-0_104083_2017-08-22_final
2017-08-27 10:59:52	ga_ls8c_ard_3-0-0_107070_2017-08-27_final
2017-08-27 11:00:16	ga_ls8c_ard_3-0-0_107071_2017-08-27_final
2017-08-27 11:00:40	ga_ls8c_ard_3-0-0_107072_2017-08-27_final
2017-08-27 11:01:03	ga_ls8c_ard_3-0-0_107073_2017-08-27_final
2017-08-27 11:01:27	ga_ls8c_ard_3-0-0_107074_2017-08-27_final
2017-08-27 11:01:51	ga_ls8c_ard_3-0-0_107075_2017-08-27_final
2017-08-29 10:51:06	ga_ls8c_ard_3-0-0_105079_2017-08-29_final
2017-08-29 10:51:30	ga_ls8c_ard_3-0-0_105080_2017-08-29_final
2017-08-29 10:51:54	ga_ls8c_ard_3-0-0_105081_2017-08-29_final
2017-08-29 10:52:18	ga_ls8c_ard_3-0-0_105082_2017-08-29_final
2017-08-29 10:52:42	ga_ls8c_ard_3-0-0_105083_2017-08-29_final
2017-09-05 10:55:18	ga_ls8c_ard_3-0-0_106074_2017-09-05_final
2017-09-05 10:55:42	ga_ls8c_ard_3-0-0_106075_2017-09-05_final
2017-09-05 10:56:05	ga_ls8c_ard_3-0-0_106076_2017-09-05_final
2017-09-05 10:56:29	ga_ls8c_ard_3-0-0_106077_2017-09-05_final
2017-09-05 10:56:53	ga_ls8c_ard_3-0-0_106078_2017-09-05_final
2017-09-05 10:57:17	ga_ls8c_ard_3-0-0_106079_2017-09-05_final
2017-09-05 10:57:41	ga_ls8c_ard_3-0-0_106080_2017-09-05_final
2017-09-07 10:46:32	ga_ls8c_ard_3-0-0_104083_2017-09-07_final
2017-09-21 10:55:21	ga_ls8c_ard_3-0-0_106074_2017-09-21_final
2017-09-21 10:55:45	ga_ls8c_ard_3-0-0_106075_2017-09-21_final
2017-09-21 10:56:09	ga_ls8c_ard_3-0-0_106076_2017-09-21_final
2017-09-21 10:56:33	ga_ls8c_ard_3-0-0_106077_2017-09-21_final
2017-09-21 10:56:56	ga_ls8c_ard_3-0-0_106078_2017-09-21_final
2017-09-21 10:57:20	ga_ls8c_ard_3-0-0_106079_2017-09-21_final
2017-09-21 10:57:44	ga_ls8c_ard_3-0-0_106080_2017-09-21_final
2017-09-23 10:46:36	ga_ls8c_ard_3-0-0_104083_2017-09-23_final
2017-10-14 11:00:03	ga_ls8c_ard_3-0-0_107070_2017-10-14_final
2017-10-14 11:00:27	ga_ls8c_ard_3-0-0_107071_2017-10-14_final
2017-10-14 11:00:51	ga_ls8c_ard_3-0-0_107072_2017-10-14_final
2017-10-14 11:01:15	ga_ls8c_ard_3-0-0_107073_2017-10-14_final
2017-10-14 11:01:39	ga_ls8c_ard_3-0-0_107074_2017-10-14_final
2017-10-14 11:02:03	ga_ls8c_ard_3-0-0_107075_2017-10-14_final
2018-09-17 10:50:38	ga_ls8c_ard_3-0-0_105079_2018-09-17_final
2018-09-17 10:51:02	ga_ls8c_ard_3-0-0_105080_2018-09-17_final
2018-09-17 10:51:26	ga_ls8c_ard_3-0-0_105081_2018-09-17_final
2018-09-17 10:51:49	ga_ls8c_ard_3-0-0_105082_2018-09-17_final
2018-09-17 10:52:13	ga_ls8c_ard_3-0-0_105083_2018-09-17_final
2019-01-07 10:50:52	ga_ls8c_ard_3-0-0_105079_2019-01-07_final
2019-01-07 10:51:16	ga_ls8c_ard_3-0-0_105080_2019-01-07_final
2019-01-07 10:51:39	ga_ls8c_ard_3-0-0_105081_2019-01-07_final
2019-01-07 10:52:03	ga_ls8c_ard_3-0-0_105082_2019-01-07_final
2019-01-07 10:52:27	ga_ls8c_ard_3-0-0_105083_2019-01-07_final
2022-02-16 10:51:04	ga_ls8c_ard_3-2-1_105079_2022-02-16_final
2022-02-16 10:51:28	ga_ls8c_ard_3-2-1_105080_2022-02-16_final
2022-02-16 10:51:52	ga_ls8c_ard_3-2-1_105081_2022-02-16_final
2022-02-16 10:52:16	ga_ls8c_ard_3-2-1_105082_2022-02-16_final
2022-02-16 10:52:40	ga_ls8c_ard_3-2-1_105083_2022-02-16_final
2022-06-29 11:05:47	ga_ls8c_ard_3-2-1_108069_2022-06-29_final
2022-06-29 11:06:11	ga_ls8c_ard_3-2-1_108070_2022-06-29_final
2022-07-01 10:55:26	ga_ls8c_ard_3-2-1_106074_2022-07-01_final
2022-07-01 10:55:50	ga_ls8c_ard_3-2-1_106075_2022-07-01_final
2022-07-01 10:56:14	ga_ls8c_ard_3-2-1_106076_2022-07-01_final
2022-07-01 10:56:37	ga_ls8c_ard_3-2-1_106077_2022-07-01_final
2022-07-01 10:57:01	ga_ls8c_ard_3-2-1_106078_2022-07-01_final
2022-07-01 10:57:25	ga_ls8c_ard_3-2-1_106079_2022-07-01_final
2022-07-01 10:57:49	ga_ls8c_ard_3-2-1_106080_2022-07-01_final
2022-07-03 10:46:16	ga_ls8c_ard_3-2-1_104082_2022-07-03_final
2022-07-08 11:00:01	ga_ls8c_ard_3-2-1_107070_2022-07-08_final
2022-07-08 11:00:24	ga_ls8c_ard_3-2-1_107071_2022-07-08_final
2022-07-08 11:00:48	ga_ls8c_ard_3-2-1_107072_2022-07-08_final
2022-07-08 11:01:12	ga_ls8c_ard_3-2-1_107073_2022-07-08_final
2022-07-08 11:01:36	ga_ls8c_ard_3-2-1_107074_2022-07-08_final
2022-07-08 11:02:00	ga_ls8c_ard_3-2-1_107075_2022-07-08_final
2022-07-10 10:51:14	ga_ls8c_ard_3-2-1_105079_2022-07-10_final
2022-07-10 10:51:38	ga_ls8c_ard_3-2-1_105080_2022-07-10_final
2022-07-10 10:52:02	ga_ls8c_ard_3-2-1_105081_2022-07-10_final
2022-07-10 10:52:26	ga_ls8c_ard_3-2-1_105082_2022-07-10_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