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
2015-08-30 11:51:48	ga_ls8c_ard_3-0-0_115077_2015-08-30_final
2015-08-30 11:52:12	ga_ls8c_ard_3-0-0_115078_2015-08-30_final
2015-09-06 11:56:50	ga_ls8c_ard_3-0-0_116074_2015-09-06_final
2015-09-06 11:57:14	ga_ls8c_ard_3-0-0_116075_2015-09-06_final
2015-09-06 11:57:38	ga_ls8c_ard_3-0-0_116076_2015-09-06_final
2015-09-06 11:58:02	ga_ls8c_ard_3-0-0_116077_2015-09-06_final
2015-09-06 11:58:26	ga_ls8c_ard_3-0-0_116078_2015-09-06_final
2015-11-09 11:57:06	ga_ls8c_ard_3-0-0_116074_2015-11-09_final
2015-11-09 11:57:30	ga_ls8c_ard_3-0-0_116075_2015-11-09_final
2015-11-09 11:57:54	ga_ls8c_ard_3-0-0_116076_2015-11-09_final
2015-11-09 11:58:18	ga_ls8c_ard_3-0-0_116077_2015-11-09_final
2015-11-09 11:58:42	ga_ls8c_ard_3-0-0_116078_2015-11-09_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
2018-09-14 11:56:36	ga_ls8c_ard_3-0-0_116074_2018-09-14_final
2018-09-14 11:57:00	ga_ls8c_ard_3-0-0_116075_2018-09-14_final
2018-09-14 11:57:24	ga_ls8c_ard_3-0-0_116076_2018-09-14_final
2018-09-14 11:57:48	ga_ls8c_ard_3-0-0_116077_2018-09-14_final
2018-09-14 11:58:12	ga_ls8c_ard_3-0-0_116078_2018-09-14_final
2018-09-23 11:51:40	ga_ls8c_ard_3-0-0_115077_2018-09-23_final
2018-09-23 11:52:04	ga_ls8c_ard_3-0-0_115078_2018-09-23_final
2018-09-23 11:52:28	ga_ls8c_ard_3-0-0_115079_2018-09-23_final
2018-09-23 11:52:52	ga_ls8c_ard_3-0-0_115080_2018-09-23_final
2018-10-02 11:47:10	ga_ls8c_ard_3-0-0_114081_2018-10-02_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
2018-10-18 11:47:16	ga_ls8c_ard_3-0-0_114081_2018-10-18_final
2018-10-25 11:51:54	ga_ls8c_ard_3-0-0_115077_2018-10-25_final
2018-10-25 11:52:18	ga_ls8c_ard_3-0-0_115078_2018-10-25_final
2018-10-25 11:52:41	ga_ls8c_ard_3-0-0_115079_2018-10-25_final
2018-10-25 11:53:05	ga_ls8c_ard_3-0-0_115080_2018-10-25_final
2018-10-27 11:42:20	ga_ls8c_ard_3-0-0_113084_2018-10-27_final
2018-11-03 11:47:20	ga_ls8c_ard_3-0-0_114081_2018-11-03_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
2018-11-26 11:51:56	ga_ls8c_ard_3-0-0_115077_2018-11-26_final
2018-11-26 11:52:20	ga_ls8c_ard_3-0-0_115078_2018-11-26_final
2018-11-26 11:52:44	ga_ls8c_ard_3-0-0_115079_2018-11-26_final
2018-11-26 11:53:08	ga_ls8c_ard_3-0-0_115080_2018-11-26_final
2018-11-28 11:42:22	ga_ls8c_ard_3-0-0_113084_2018-11-28_final
2018-12-05 11:47:19	ga_ls8c_ard_3-0-0_114081_2018-12-05_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
2018-12-19 11:56:52	ga_ls8c_ard_3-0-0_116074_2018-12-19_final
2018-12-19 11:57:16	ga_ls8c_ard_3-0-0_116075_2018-12-19_final
2018-12-19 11:57:39	ga_ls8c_ard_3-0-0_116076_2018-12-19_final
2018-12-19 11:58:03	ga_ls8c_ard_3-0-0_116077_2018-12-19_final
2018-12-19 11:58:27	ga_ls8c_ard_3-0-0_116078_2018-12-19_final
2018-12-21 11:47:18	ga_ls8c_ard_3-0-0_114081_2018-12-21_final
2019-02-23 11:47:08	ga_ls8c_ard_3-0-0_114081_2019-02-23_final
2019-03-02 11:51:41	ga_ls8c_ard_3-0-0_115077_2019-03-02_final
2019-03-02 11:52:05	ga_ls8c_ard_3-0-0_115078_2019-03-02_final
2019-03-02 11:52:29	ga_ls8c_ard_3-0-0_115079_2019-03-02_final
2019-03-02 11:52:53	ga_ls8c_ard_3-0-0_115080_2019-03-02_final
2019-04-19 11:51:26	ga_ls8c_ard_3-1-0_115077_2019-04-19_final
2019-04-19 11:51:50	ga_ls8c_ard_3-1-0_115078_2019-04-19_final
2019-04-19 11:52:14	ga_ls8c_ard_3-1-0_115079_2019-04-19_final
2019-04-19 11:52:38	ga_ls8c_ard_3-1-0_115080_2019-04-19_final
2019-06-06 11:51:46	ga_ls8c_ard_3-0-0_115077_2019-06-06_final
2019-06-06 11:52:10	ga_ls8c_ard_3-0-0_115078_2019-06-06_final
2019-06-06 11:52:34	ga_ls8c_ard_3-0-0_115079_2019-06-06_final
2019-06-06 11:52:58	ga_ls8c_ard_3-0-0_115080_2019-06-06_final
2019-06-08 11:42:13	ga_ls8c_ard_3-0-0_113084_2019-06-08_final
2019-06-15 11:47:15	ga_ls8c_ard_3-1-0_114081_2019-06-15_final
2019-07-08 11:51:56	ga_ls8c_ard_3-1-0_115077_2019-07-08_final
2019-07-08 11:52:20	ga_ls8c_ard_3-1-0_115078_2019-07-08_final
2019-07-08 11:52:44	ga_ls8c_ard_3-1-0_115079_2019-07-08_final
2019-07-08 11:53:08	ga_ls8c_ard_3-1-0_115080_2019-07-08_final
2019-07-10 11:42:22	ga_ls8c_ard_3-1-0_113084_2019-07-10_final
2019-08-02 11:47:29	ga_ls8c_ard_3-1-0_114081_2019-08-02_final
2019-08-09 11:52:06	ga_ls8c_ard_3-1-0_115077_2019-08-09_final
2019-08-09 11:52:30	ga_ls8c_ard_3-1-0_115078_2019-08-09_final
2019-08-09 11:52:54	ga_ls8c_ard_3-1-0_115079_2019-08-09_final
2019-08-09 11:53:18	ga_ls8c_ard_3-1-0_115080_2019-08-09_final
2019-08-11 11:42:33	ga_ls8c_ard_3-1-0_113084_2019-08-11_final
2019-09-10 11:52:15	ga_ls8c_ard_3-1-0_115077_2019-09-10_final
2019-09-10 11:52:39	ga_ls8c_ard_3-1-0_115078_2019-09-10_final
2019-09-10 11:53:03	ga_ls8c_ard_3-1-0_115079_2019-09-10_final
2019-09-10 11:53:27	ga_ls8c_ard_3-1-0_115080_2019-09-10_final
2019-09-17 11:57:16	ga_ls8c_ard_3-1-0_116074_2019-09-17_final
2019-09-17 11:57:40	ga_ls8c_ard_3-1-0_116075_2019-09-17_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
2019-09-19 11:47:43	ga_ls8c_ard_3-1-0_114081_2019-09-19_final
2019-10-19 11:57:23	ga_ls8c_ard_3-1-0_116074_2019-10-19_final
2019-10-19 11:57:47	ga_ls8c_ard_3-1-0_116075_2019-10-19_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

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