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
2015-10-17 11:52:01	ga_ls8c_ard_3-0-0_115077_2015-10-17_final
2015-10-17 11:52:25	ga_ls8c_ard_3-0-0_115078_2015-10-17_final
2015-10-17 11:52:49	ga_ls8c_ard_3-0-0_115079_2015-10-17_final
2015-10-17 11:53:13	ga_ls8c_ard_3-0-0_115080_2015-10-17_final
2015-12-11 11:57:06	ga_ls8c_ard_3-0-0_116074_2015-12-11_final
2015-12-11 11:57:30	ga_ls8c_ard_3-0-0_116075_2015-12-11_final
2015-12-11 11:57:54	ga_ls8c_ard_3-0-0_116076_2015-12-11_final
2015-12-11 11:58:18	ga_ls8c_ard_3-0-0_116077_2015-12-11_final
2015-12-11 11:58:41	ga_ls8c_ard_3-0-0_116078_2015-12-11_final
2018-10-09 11:51:48	ga_ls8c_ard_3-0-0_115077_2018-10-09_final
2018-10-09 11:52:12	ga_ls8c_ard_3-0-0_115078_2018-10-09_final
2018-10-09 11:52:36	ga_ls8c_ard_3-0-0_115079_2018-10-09_final
2018-10-09 11:53:00	ga_ls8c_ard_3-0-0_115080_2018-10-09_final
2018-10-11 11:42:15	ga_ls8c_ard_3-0-0_113084_2018-10-11_final
2018-10-16 11:56:50	ga_ls8c_ard_3-0-0_116074_2018-10-16_final
2018-10-16 11:57:14	ga_ls8c_ard_3-0-0_116075_2018-10-16_final
2018-10-16 11:57:38	ga_ls8c_ard_3-0-0_116076_2018-10-16_final
2018-10-16 11:58:02	ga_ls8c_ard_3-0-0_116077_2018-10-16_final
2018-10-16 11:58:26	ga_ls8c_ard_3-0-0_116078_2018-10-16_final
2018-11-10 11:51:32	ga_ls8c_ard_3-0-0_115076_2018-11-10_final
2018-11-10 11:51:56	ga_ls8c_ard_3-0-0_115077_2018-11-10_final
2018-11-10 11:52:20	ga_ls8c_ard_3-0-0_115078_2018-11-10_final
2018-11-10 11:52:44	ga_ls8c_ard_3-0-0_115079_2018-11-10_final
2018-11-10 11:53:08	ga_ls8c_ard_3-0-0_115080_2018-11-10_final
2018-11-12 11:42:22	ga_ls8c_ard_3-0-0_113084_2018-11-12_final
2018-11-17 11:56:55	ga_ls8c_ard_3-0-0_116074_2018-11-17_final
2018-11-17 11:57:19	ga_ls8c_ard_3-0-0_116075_2018-11-17_final
2018-11-17 11:57:43	ga_ls8c_ard_3-0-0_116076_2018-11-17_final
2018-11-17 11:58:07	ga_ls8c_ard_3-0-0_116077_2018-11-17_final
2018-11-17 11:58:31	ga_ls8c_ard_3-0-0_116078_2018-11-17_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 11:42:18	ga_ls8c_ard_3-0-0_113084_2018-12-14_final
2019-01-13 11:51:51	ga_ls8c_ard_3-0-0_115077_2019-01-13_final
2019-01-13 11:52:15	ga_ls8c_ard_3-0-0_115078_2019-01-13_final
2019-01-13 11:52:39	ga_ls8c_ard_3-0-0_115079_2019-01-13_final
2019-01-13 11:53:03	ga_ls8c_ard_3-0-0_115080_2019-01-13_final
2019-08-18 11:47:34	ga_ls8c_ard_3-1-0_114081_2019-08-18_final
2019-11-04 11:57:22	ga_ls8c_ard_3-1-0_116074_2019-11-04_final
2019-11-04 11:57:46	ga_ls8c_ard_3-1-0_116075_2019-11-04_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
2019-11-06 11:47:48	ga_ls8c_ard_3-1-0_114081_2019-11-06_final
2019-11-20 11:57:19	ga_ls8c_ard_3-1-0_116074_2019-11-20_final
2019-11-20 11:57:43	ga_ls8c_ard_3-1-0_116075_2019-11-20_final
2019-11-20 11:58:06	ga_ls8c_ard_3-1-0_116076_2019-11-20_final
2019-11-20 11:58:30	ga_ls8c_ard_3-1-0_116077_2019-11-20_final
2019-11-20 11:58:54	ga_ls8c_ard_3-1-0_116078_2019-11-20_final
2019-11-22 11:47:44	ga_ls8c_ard_3-1-0_114081_2019-11-22_final
2019-11-29 11:52:19	ga_ls8c_ard_3-1-0_115077_2019-11-29_final
2019-11-29 11:52:43	ga_ls8c_ard_3-1-0_115078_2019-11-29_final
2019-11-29 11:53:07	ga_ls8c_ard_3-1-0_115079_2019-11-29_final
2019-11-29 11:53:31	ga_ls8c_ard_3-1-0_115080_2019-11-29_final
2019-12-01 11:42:45	ga_ls8c_ard_3-1-0_113084_2019-12-01_final
2019-12-06 11:57:18	ga_ls8c_ard_3-1-0_116074_2019-12-06_final
2019-12-06 11:57:42	ga_ls8c_ard_3-1-0_116075_2019-12-06_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
2019-12-08 11:47:44	ga_ls8c_ard_3-1-0_114081_2019-12-08_final
2019-12-24 11:47:41	ga_ls8c_ard_3-1-0_114081_2019-12-24_final
2019-12-31 11:52:14	ga_ls8c_ard_3-1-0_115077_2019-12-31_final
2019-12-31 11:52:38	ga_ls8c_ard_3-1-0_115078_2019-12-31_final
2019-12-31 11:53:02	ga_ls8c_ard_3-1-0_115079_2019-12-31_final
2019-12-31 11:53:26	ga_ls8c_ard_3-1-0_115080_2019-12-31_final
2020-01-07 11:57:11	ga_ls8c_ard_3-1-0_116074_2020-01-07_final
2020-01-07 11:57:35	ga_ls8c_ard_3-1-0_116075_2020-01-07_final
2020-01-07 11:57:59	ga_ls8c_ard_3-1-0_116076_2020-01-07_final
2020-01-07 11:58:23	ga_ls8c_ard_3-1-0_116077_2020-01-07_final
2020-01-07 11:58:47	ga_ls8c_ard_3-1-0_116078_2020-01-07_final
2020-01-16 11:52:10	ga_ls8c_ard_3-1-0_115077_2020-01-16_final
2020-01-16 11:52:34	ga_ls8c_ard_3-1-0_115078_2020-01-16_final
2020-01-16 11:52:58	ga_ls8c_ard_3-1-0_115079_2020-01-16_final
2020-01-16 11:53:22	ga_ls8c_ard_3-1-0_115080_2020-01-16_final
2020-01-23 11:57:08	ga_ls8c_ard_3-1-0_116074_2020-01-23_final
2020-01-23 11:57:32	ga_ls8c_ard_3-1-0_116075_2020-01-23_final
2020-01-23 11:57:55	ga_ls8c_ard_3-1-0_116076_2020-01-23_final
2020-01-23 11:58:19	ga_ls8c_ard_3-1-0_116077_2020-01-23_final
2020-01-23 11:58:43	ga_ls8c_ard_3-1-0_116078_2020-01-23_final
2020-02-01 11:52:05	ga_ls8c_ard_3-1-0_115077_2020-02-01_final
2020-02-01 11:52:29	ga_ls8c_ard_3-1-0_115078_2020-02-01_final
2020-02-01 11:52:53	ga_ls8c_ard_3-1-0_115079_2020-02-01_final
2020-02-01 11:53:17	ga_ls8c_ard_3-1-0_115080_2020-02-01_final
2020-02-08 11:57:02	ga_ls8c_ard_3-1-0_116074_2020-02-08_final
2020-02-08 11:57:26	ga_ls8c_ard_3-1-0_116075_2020-02-08_final
2020-02-08 11:57:50	ga_ls8c_ard_3-1-0_116076_2020-02-08_final
2020-02-08 11:58:14	ga_ls8c_ard_3-1-0_116077_2020-02-08_final
2020-02-08 11:58:38	ga_ls8c_ard_3-1-0_116078_2020-02-08_final
2020-02-17 11:52:02	ga_ls8c_ard_3-1-0_115077_2020-02-17_final
2020-02-17 11:52:26	ga_ls8c_ard_3-1-0_115078_2020-02-17_final
2020-02-17 11:52:50	ga_ls8c_ard_3-1-0_115079_2020-02-17_final
2020-02-17 11:53:14	ga_ls8c_ard_3-1-0_115080_2020-02-17_final
2020-02-24 11:56:59	ga_ls8c_ard_3-1-0_116074_2020-02-24_final
2020-02-24 11:57:23	ga_ls8c_ard_3-1-0_116075_2020-02-24_final
2020-02-24 11:57:47	ga_ls8c_ard_3-1-0_116076_2020-02-24_final
2020-02-24 11:58:11	ga_ls8c_ard_3-1-0_116077_2020-02-24_final
2020-02-24 11:58:35	ga_ls8c_ard_3-1-0_116078_2020-02-24_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