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
2016-05-28 11:52:51	ga_ls8c_ard_3-0-0_115080_2016-05-28_final
2016-06-13 11:52:54	ga_ls8c_ard_3-0-0_115080_2016-06-13_final
2016-07-06 11:57:40	ga_ls8c_ard_3-0-0_116076_2016-07-06_final
2016-07-06 11:58:04	ga_ls8c_ard_3-0-0_116077_2016-07-06_final
2016-07-06 11:58:28	ga_ls8c_ard_3-0-0_116078_2016-07-06_final
2016-08-07 11:57:49	ga_ls8c_ard_3-0-0_116076_2016-08-07_final
2016-08-07 11:58:13	ga_ls8c_ard_3-0-0_116077_2016-08-07_final
2016-08-07 11:58:37	ga_ls8c_ard_3-0-0_116078_2016-08-07_final
2016-09-01 11:53:23	ga_ls8c_ard_3-0-0_115080_2016-09-01_final
2016-09-17 11:53:26	ga_ls8c_ard_3-0-0_115080_2016-09-17_final
2016-09-24 11:58:01	ga_ls8c_ard_3-0-0_116076_2016-09-24_final
2016-09-24 11:58:25	ga_ls8c_ard_3-0-0_116077_2016-09-24_final
2016-09-24 11:58:49	ga_ls8c_ard_3-0-0_116078_2016-09-24_final
2016-10-03 11:53:27	ga_ls8c_ard_3-0-0_115080_2016-10-03_final
2016-10-10 11:58:05	ga_ls8c_ard_3-0-0_116076_2016-10-10_final
2016-10-10 11:58:29	ga_ls8c_ard_3-0-0_116077_2016-10-10_final
2016-10-10 11:58:53	ga_ls8c_ard_3-0-0_116078_2016-10-10_final
2016-10-19 11:53:32	ga_ls8c_ard_3-0-0_115080_2016-10-19_final
2016-11-11 11:58:07	ga_ls8c_ard_3-0-0_116076_2016-11-11_final
2016-11-11 11:58:30	ga_ls8c_ard_3-0-0_116077_2016-11-11_final
2016-11-11 11:58:54	ga_ls8c_ard_3-0-0_116078_2016-11-11_final
2017-01-23 11:53:19	ga_ls8c_ard_3-0-0_115080_2017-01-23_final
2017-02-24 11:53:05	ga_ls8c_ard_3-0-0_115080_2017-02-24_final
2018-04-23 11:57:01	ga_ls8c_ard_3-0-0_116076_2018-04-23_final
2018-04-23 11:57:25	ga_ls8c_ard_3-0-0_116077_2018-04-23_final
2018-04-23 11:57:49	ga_ls8c_ard_3-0-0_116078_2018-04-23_final
2018-05-02 11:52:21	ga_ls8c_ard_3-0-0_115080_2018-05-02_final
2018-05-09 11:56:52	ga_ls8c_ard_3-0-0_116076_2018-05-09_final
2018-05-09 11:57:16	ga_ls8c_ard_3-0-0_116077_2018-05-09_final
2018-05-09 11:57:40	ga_ls8c_ard_3-0-0_116078_2018-05-09_final
2018-05-25 11:56:40	ga_ls8c_ard_3-0-0_116076_2018-05-25_final
2018-05-25 11:57:04	ga_ls8c_ard_3-0-0_116077_2018-05-25_final
2018-05-25 11:57:28	ga_ls8c_ard_3-0-0_116078_2018-05-25_final
2018-07-05 11:52:17	ga_ls8c_ard_3-0-0_115080_2018-07-05_final
2019-02-05 11:57:33	ga_ls8c_ard_3-0-0_116076_2019-02-05_final
2019-02-05 11:57:57	ga_ls8c_ard_3-0-0_116077_2019-02-05_final
2019-02-05 11:58:21	ga_ls8c_ard_3-0-0_116078_2019-02-05_final
2019-02-21 11:57:30	ga_ls8c_ard_3-0-0_116076_2019-02-21_final
2019-02-21 11:57:54	ga_ls8c_ard_3-0-0_116077_2019-02-21_final
2019-02-21 11:58:18	ga_ls8c_ard_3-0-0_116078_2019-02-21_final
2019-03-25 11:57:21	ga_ls8c_ard_3-1-0_116076_2019-03-25_final
2019-03-25 11:57:45	ga_ls8c_ard_3-1-0_116077_2019-03-25_final
2019-03-25 11:58:09	ga_ls8c_ard_3-1-0_116078_2019-03-25_final
2019-05-05 11:52:39	ga_ls8c_ard_3-0-0_115080_2019-05-05_final
2019-05-12 11:57:19	ga_ls8c_ard_3-0-0_116076_2019-05-12_final
2019-05-12 11:57:43	ga_ls8c_ard_3-0-0_116077_2019-05-12_final
2019-05-12 11:58:07	ga_ls8c_ard_3-0-0_116078_2019-05-12_final
2019-05-21 11:52:50	ga_ls8c_ard_3-0-0_115080_2019-05-21_final
2019-06-22 11:53:04	ga_ls8c_ard_3-1-0_115080_2019-06-22_final
2019-06-29 11:57:41	ga_ls8c_ard_3-1-0_116076_2019-06-29_final
2019-06-29 11:58:05	ga_ls8c_ard_3-1-0_116077_2019-06-29_final
2019-06-29 11:58:29	ga_ls8c_ard_3-1-0_116078_2019-06-29_final
2019-07-24 11:53:12	ga_ls8c_ard_3-1-0_115080_2019-07-24_final
2019-07-31 11:57:50	ga_ls8c_ard_3-1-0_116076_2019-07-31_final
2019-07-31 11:58:14	ga_ls8c_ard_3-1-0_116077_2019-07-31_final
2019-07-31 11:58:38	ga_ls8c_ard_3-1-0_116078_2019-07-31_final
2019-08-16 11:57:55	ga_ls8c_ard_3-1-0_116076_2019-08-16_final
2019-08-16 11:58:19	ga_ls8c_ard_3-1-0_116077_2019-08-16_final
2019-08-16 11:58:43	ga_ls8c_ard_3-1-0_116078_2019-08-16_final
2019-08-25 11:53:23	ga_ls8c_ard_3-1-0_115080_2019-08-25_final
2019-09-01 11:57:59	ga_ls8c_ard_3-1-0_116076_2019-09-01_final
2019-09-01 11:58:23	ga_ls8c_ard_3-1-0_116077_2019-09-01_final
2019-09-01 11:58:47	ga_ls8c_ard_3-1-0_116078_2019-09-01_final
2019-09-17 11:58:04	ga_ls8c_ard_3-1-0_116076_2019-09-17_final
2019-09-17 11:58:28	ga_ls8c_ard_3-1-0_116077_2019-09-17_final
2019-09-17 11:58:52	ga_ls8c_ard_3-1-0_116078_2019-09-17_final
2019-09-26 11:53:32	ga_ls8c_ard_3-1-0_115080_2019-09-26_final
2019-10-19 11:58:11	ga_ls8c_ard_3-1-0_116076_2019-10-19_final
2019-10-19 11:58:35	ga_ls8c_ard_3-1-0_116077_2019-10-19_final
2019-10-19 11:58:59	ga_ls8c_ard_3-1-0_116078_2019-10-19_final
2019-11-04 11:58:10	ga_ls8c_ard_3-1-0_116076_2019-11-04_final
2019-11-04 11:58:34	ga_ls8c_ard_3-1-0_116077_2019-11-04_final
2019-11-04 11:58:58	ga_ls8c_ard_3-1-0_116078_2019-11-04_final
2019-11-13 11:53:33	ga_ls8c_ard_3-1-0_115080_2019-11-13_final
2019-12-06 11:58:06	ga_ls8c_ard_3-1-0_116076_2019-12-06_final
2019-12-06 11:58:30	ga_ls8c_ard_3-1-0_116077_2019-12-06_final
2019-12-06 11:58:54	ga_ls8c_ard_3-1-0_116078_2019-12-06_final
2020-03-11 11:57:41	ga_ls8c_ard_3-1-0_116076_2020-03-11_final
2020-03-11 11:58:04	ga_ls8c_ard_3-1-0_116077_2020-03-11_final
2020-03-11 11:58:28	ga_ls8c_ard_3-1-0_116078_2020-03-11_final
2020-05-14 11:57:12	ga_ls8c_ard_3-1-0_116076_2020-05-14_final
2020-05-14 11:57:36	ga_ls8c_ard_3-1-0_116077_2020-05-14_final
2020-05-14 11:58:00	ga_ls8c_ard_3-1-0_116078_2020-05-14_final
2021-07-29 11:53:14	ga_ls8c_ard_3-2-0_115080_2021-07-29_final
2021-11-02 11:53:37	ga_ls8c_ard_3-2-0_115080_2021-11-02_final
2021-12-04 11:53:34	ga_ls8c_ard_3-2-0_115080_2021-12-04_final
2021-12-11 11:58:08	ga_ls8c_ard_3-2-1_116076_2021-12-11_final
2021-12-11 11:58:32	ga_ls8c_ard_3-2-1_116077_2021-12-11_final
2021-12-11 11:58:56	ga_ls8c_ard_3-2-1_116078_2021-12-11_final
2021-12-20 11:53:32	ga_ls8c_ard_3-2-1_115080_2021-12-20_final
2022-01-12 11:58:01	ga_ls8c_ard_3-2-1_116076_2022-01-12_final
2022-01-12 11:58:25	ga_ls8c_ard_3-2-1_116077_2022-01-12_final
2022-01-12 11:58:49	ga_ls8c_ard_3-2-1_116078_2022-01-12_final
2022-06-30 11:53:27	ga_ls8c_ard_3-2-1_115080_2022-06-30_final
2022-07-07 11:58:02	ga_ls8c_ard_3-2-1_116076_2022-07-07_final
2022-07-07 11:58:26	ga_ls8c_ard_3-2-1_116077_2022-07-07_final
2022-07-07 11:58:50	ga_ls8c_ard_3-2-1_116078_2022-07-07_final
2022-07-16 11:53:25	ga_ls8c_ard_3-2-1_115080_2022-07-16_final
2022-07-23 11:58:07	ga_ls8c_ard_3-2-1_116076_2022-07-23_final
2022-07-23 11:58:31	ga_ls8c_ard_3-2-1_116077_2022-07-23_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