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
2016-07-06 10:15:12	ga_ls8c_ard_3-0-0_100067_2016-07-06_final
2016-07-22 10:15:18	ga_ls8c_ard_3-0-0_100067_2016-07-22_final
2016-08-07 10:15:20	ga_ls8c_ard_3-0-0_100067_2016-08-07_final
2016-11-27 10:15:39	ga_ls8c_ard_3-0-0_100067_2016-11-27_final
2017-04-04 10:14:52	ga_ls8c_ard_3-0-0_100067_2017-04-04_final
2017-05-06 10:14:37	ga_ls8c_ard_3-0-0_100067_2017-05-06_final
2017-05-22 10:14:49	ga_ls8c_ard_3-0-0_100067_2017-05-22_final
2017-06-23 10:15:03	ga_ls8c_ard_3-0-0_100067_2017-06-23_final
2017-07-09 10:15:07	ga_ls8c_ard_3-0-0_100067_2017-07-09_final
2017-09-11 10:15:25	ga_ls8c_ard_3-0-0_100067_2017-09-11_final
2017-10-13 10:15:36	ga_ls8c_ard_3-0-0_100067_2017-10-13_final
2017-11-14 10:15:34	ga_ls8c_ard_3-0-0_100067_2017-11-14_final
2017-11-30 10:15:27	ga_ls8c_ard_3-0-0_100067_2017-11-30_final
2017-12-16 10:15:29	ga_ls8c_ard_3-0-0_100067_2017-12-16_final
2018-01-01 10:15:28	ga_ls8c_ard_3-0-0_100067_2018-01-01_final
2018-01-17 10:15:21	ga_ls8c_ard_3-0-0_100067_2018-01-17_final
2018-02-02 10:15:11	ga_ls8c_ard_3-0-0_100067_2018-02-02_final
2018-02-18 10:15:06	ga_ls8c_ard_3-0-0_100067_2018-02-18_final
2018-03-06 10:14:58	ga_ls8c_ard_3-0-0_100067_2018-03-06_final
2018-03-22 10:14:50	ga_ls8c_ard_3-0-0_100067_2018-03-22_final
2018-04-07 10:14:42	ga_ls8c_ard_3-0-0_100067_2018-04-07_final
2018-04-23 10:14:33	ga_ls8c_ard_3-0-0_100067_2018-04-23_final
2018-05-09 10:14:24	ga_ls8c_ard_3-0-0_100067_2018-05-09_final
2018-05-25 10:14:12	ga_ls8c_ard_3-0-0_100067_2018-05-25_final
2018-06-10 10:14:08	ga_ls8c_ard_3-0-0_100067_2018-06-10_final
2018-06-26 10:14:19	ga_ls8c_ard_3-0-0_100067_2018-06-26_final
2018-07-12 10:14:27	ga_ls8c_ard_3-0-0_100067_2018-07-12_final
2018-07-28 10:14:34	ga_ls8c_ard_3-0-0_100067_2018-07-28_final
2018-08-13 10:14:43	ga_ls8c_ard_3-0-0_100067_2018-08-13_final
2018-08-29 10:14:51	ga_ls8c_ard_3-0-0_100067_2018-08-29_final
2018-09-14 10:14:56	ga_ls8c_ard_3-0-0_100067_2018-09-14_final
2018-09-30 10:15:02	ga_ls8c_ard_3-0-0_100067_2018-09-30_final
2018-10-16 10:15:09	ga_ls8c_ard_3-0-0_100067_2018-10-16_final
2018-11-01 10:15:13	ga_ls8c_ard_3-0-0_100067_2018-11-01_final
2018-11-17 10:15:15	ga_ls8c_ard_3-0-0_100067_2018-11-17_final
2018-12-03 10:15:13	ga_ls8c_ard_3-0-0_100067_2018-12-03_final
2018-12-19 10:15:11	ga_ls8c_ard_3-0-0_100067_2018-12-19_final
2019-01-04 10:15:11	ga_ls8c_ard_3-0-0_100067_2019-01-04_final
2019-01-20 10:15:08	ga_ls8c_ard_3-0-0_100067_2019-01-20_final
2019-02-05 10:15:04	ga_ls8c_ard_3-0-0_100067_2019-02-05_final
2019-02-21 10:15:02	ga_ls8c_ard_3-0-0_100067_2019-02-21_final
2019-03-09 10:14:57	ga_ls8c_ard_3-1-0_100067_2019-03-09_final
2019-03-25 10:14:53	ga_ls8c_ard_3-1-0_100067_2019-03-25_final
2019-04-10 10:14:48	ga_ls8c_ard_3-1-0_100067_2019-04-10_final
2019-04-26 10:14:42	ga_ls8c_ard_3-0-0_100067_2019-04-26_final
2019-05-12 10:14:51	ga_ls8c_ard_3-0-0_100067_2019-05-12_final
2019-05-28 10:15:00	ga_ls8c_ard_3-0-0_100067_2019-05-28_final
2019-06-13 10:15:07	ga_ls8c_ard_3-1-0_100067_2019-06-13_final
2019-06-29 10:15:12	ga_ls8c_ard_3-1-0_100067_2019-06-29_final
2019-07-15 10:15:15	ga_ls8c_ard_3-1-0_100067_2019-07-15_final
2019-07-31 10:15:21	ga_ls8c_ard_3-1-0_100067_2019-07-31_final
2019-08-16 10:15:27	ga_ls8c_ard_3-1-0_100067_2019-08-16_final
2019-09-01 10:15:31	ga_ls8c_ard_3-1-0_100067_2019-09-01_final
2019-09-17 10:15:36	ga_ls8c_ard_3-1-0_100067_2019-09-17_final
2019-10-03 10:15:40	ga_ls8c_ard_3-1-0_100067_2019-10-03_final
2019-10-19 10:15:42	ga_ls8c_ard_3-1-0_100067_2019-10-19_final
2019-11-04 10:15:42	ga_ls8c_ard_3-1-0_100067_2019-11-04_final
2019-11-20 10:15:38	ga_ls8c_ard_3-1-0_100067_2019-11-20_final
2019-12-06 10:15:37	ga_ls8c_ard_3-1-0_100067_2019-12-06_final
2019-12-22 10:15:35	ga_ls8c_ard_3-1-0_100067_2019-12-22_final
2020-01-07 10:15:31	ga_ls8c_ard_3-1-0_100067_2020-01-07_final
2020-01-23 10:15:27	ga_ls8c_ard_3-1-0_100067_2020-01-23_final
2020-02-08 10:15:22	ga_ls8c_ard_3-1-0_100067_2020-02-08_final
2020-02-24 10:15:18	ga_ls8c_ard_3-1-0_100067_2020-02-24_final
2020-03-11 10:15:12	ga_ls8c_ard_3-1-0_100067_2020-03-11_final
2020-03-27 10:15:03	ga_ls8c_ard_3-1-0_100067_2020-03-27_final
2020-04-12 10:14:56	ga_ls8c_ard_3-1-0_100067_2020-04-12_final
2020-04-28 10:14:48	ga_ls8c_ard_3-1-0_100067_2020-04-28_final
2020-05-14 10:14:43	ga_ls8c_ard_3-1-0_100067_2020-05-14_final
2020-05-30 10:14:47	ga_ls8c_ard_3-1-0_100067_2020-05-30_final
2020-06-15 10:14:57	ga_ls8c_ard_3-1-0_100067_2020-06-15_final
2020-07-01 10:15:05	ga_ls8c_ard_3-1-0_100067_2020-07-01_final
2020-07-17 10:15:11	ga_ls8c_ard_3-1-0_100067_2020-07-17_final
2020-08-02 10:15:16	ga_ls8c_ard_3-1-0_100067_2020-08-02_final
2020-08-18 10:15:21	ga_ls8c_ard_3-1-0_100067_2020-08-18_final
2020-09-03 10:15:29	ga_ls8c_ard_3-1-0_100067_2020-09-03_final
2020-09-19 10:15:35	ga_ls8c_ard_3-1-0_100067_2020-09-19_final
2020-10-05 10:15:38	ga_ls8c_ard_3-1-0_100067_2020-10-05_final
2020-10-21 10:15:39	ga_ls8c_ard_3-1-0_100067_2020-10-21_final
2020-11-22 10:15:38	ga_ls8c_ard_3-1-0_100067_2020-11-22_final
2020-12-08 10:15:40	ga_ls8c_ard_3-1-0_100067_2020-12-08_final
2021-01-09 10:15:32	ga_ls8c_ard_3-2-0_100067_2021-01-09_final
2021-01-25 10:15:27	ga_ls8c_ard_3-2-0_100067_2021-01-25_final
2021-02-26 10:15:19	ga_ls8c_ard_3-2-0_100067_2021-02-26_final
2021-03-14 10:15:10	ga_ls8c_ard_3-2-0_100067_2021-03-14_final
2021-03-30 10:15:06	ga_ls8c_ard_3-2-0_100067_2021-03-30_final
2021-04-15 10:15:00	ga_ls8c_ard_3-2-0_100067_2021-04-15_final
2021-05-01 10:14:51	ga_ls8c_ard_3-2-0_100067_2021-05-01_final
2021-05-17 10:14:55	ga_ls8c_ard_3-2-0_100067_2021-05-17_final
2021-06-02 10:15:04	ga_ls8c_ard_3-2-0_100067_2021-06-02_final
2021-06-18 10:15:10	ga_ls8c_ard_3-2-0_100067_2021-06-18_final
2021-07-04 10:15:13	ga_ls8c_ard_3-2-0_100067_2021-07-04_final
2021-07-20 10:15:16	ga_ls8c_ard_3-2-0_100067_2021-07-20_final
2021-08-05 10:15:24	ga_ls8c_ard_3-2-0_100067_2021-08-05_final
2021-08-21 10:15:29	ga_ls8c_ard_3-2-0_100067_2021-08-21_final
2021-09-06 10:15:34	ga_ls8c_ard_3-2-0_100067_2021-09-06_final
2021-09-22 10:15:36	ga_ls8c_ard_3-2-0_100067_2021-09-22_final
2021-10-08 10:15:42	ga_ls8c_ard_3-2-0_100067_2021-10-08_final
2021-10-24 10:15:45	ga_ls8c_ard_3-2-0_100067_2021-10-24_final
2021-11-09 10:15:42	ga_ls8c_ard_3-2-0_100067_2021-11-09_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