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
2014-12-01 11:52:36	ga_ls8c_ard_3-0-0_115078_2014-12-01_final
2014-12-01 11:53:00	ga_ls8c_ard_3-0-0_115079_2014-12-01_final
2014-12-01 11:53:24	ga_ls8c_ard_3-0-0_115080_2014-12-01_final
2015-04-08 11:51:47	ga_ls8c_ard_3-0-0_115078_2015-04-08_final
2015-04-08 11:52:11	ga_ls8c_ard_3-0-0_115079_2015-04-08_final
2015-04-08 11:52:35	ga_ls8c_ard_3-0-0_115080_2015-04-08_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
2018-10-09 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
2018-11-01 11:56:54	ga_ls8c_ard_3-0-0_116074_2018-11-01_final
2018-11-01 11:57:18	ga_ls8c_ard_3-0-0_116075_2018-11-01_final
2018-11-01 11:57:42	ga_ls8c_ard_3-0-0_116076_2018-11-01_final
2018-11-01 11:58:06	ga_ls8c_ard_3-0-0_116077_2018-11-01_final
2018-11-01 11:58:30	ga_ls8c_ard_3-0-0_116078_2018-11-01_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
2019-01-04 11:56:51	ga_ls8c_ard_3-0-0_116074_2019-01-04_final
2019-01-20 11:56:48	ga_ls8c_ard_3-0-0_116074_2019-01-20_final
2019-01-20 11:57:12	ga_ls8c_ard_3-0-0_116075_2019-01-20_final
2019-01-20 11:57:36	ga_ls8c_ard_3-0-0_116076_2019-01-20_final
2019-01-20 11:58:00	ga_ls8c_ard_3-0-0_116077_2019-01-20_final
2019-01-20 11:58:24	ga_ls8c_ard_3-0-0_116078_2019-01-20_final
2019-06-22 11:51:52	ga_ls8c_ard_3-1-0_115077_2019-06-22_final
2019-06-22 11:52:16	ga_ls8c_ard_3-1-0_115078_2019-06-22_final
2019-06-22 11:52:40	ga_ls8c_ard_3-1-0_115079_2019-06-22_final
2019-06-22 11:53:04	ga_ls8c_ard_3-1-0_115080_2019-06-22_final
2019-06-29 11:56:53	ga_ls8c_ard_3-1-0_116074_2019-06-29_final
2019-06-29 11:57:17	ga_ls8c_ard_3-1-0_116075_2019-06-29_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
2019-07-08 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
2019-07-15 11:56:56	ga_ls8c_ard_3-1-0_116074_2019-07-15_final
2019-07-15 11:57:20	ga_ls8c_ard_3-1-0_116075_2019-07-15_final
2019-07-15 11:57:44	ga_ls8c_ard_3-1-0_116076_2019-07-15_final
2019-07-15 11:58:08	ga_ls8c_ard_3-1-0_116077_2019-07-15_final
2019-07-15 11:58:32	ga_ls8c_ard_3-1-0_116078_2019-07-15_final
2019-07-24 11:52:24	ga_ls8c_ard_3-1-0_115078_2019-07-24_final
2019-07-24 11:52:48	ga_ls8c_ard_3-1-0_115079_2019-07-24_final
2019-07-24 11:53:12	ga_ls8c_ard_3-1-0_115080_2019-07-24_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
2019-08-16 11:57:08	ga_ls8c_ard_3-1-0_116074_2019-08-16_final
2019-08-16 11:57:31	ga_ls8c_ard_3-1-0_116075_2019-08-16_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 11:52:35	ga_ls8c_ard_3-1-0_115078_2019-08-25_final
2019-08-25 11:52:59	ga_ls8c_ard_3-1-0_115079_2019-08-25_final
2019-08-25 11:53:23	ga_ls8c_ard_3-1-0_115080_2019-08-25_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
2019-09-26 11:52:44	ga_ls8c_ard_3-1-0_115078_2019-09-26_final
2019-09-26 11:53:08	ga_ls8c_ard_3-1-0_115079_2019-09-26_final
2019-09-26 11:53:32	ga_ls8c_ard_3-1-0_115080_2019-09-26_final
2019-10-03 11:57:21	ga_ls8c_ard_3-1-0_116074_2019-10-03_final
2019-10-03 11:57:45	ga_ls8c_ard_3-1-0_116075_2019-10-03_final
2019-10-03 11:58:09	ga_ls8c_ard_3-1-0_116076_2019-10-03_final
2019-10-03 11:58:33	ga_ls8c_ard_3-1-0_116077_2019-10-03_final
2019-10-03 11:58:57	ga_ls8c_ard_3-1-0_116078_2019-10-03_final
2019-10-12 11:52:47	ga_ls8c_ard_3-1-0_115078_2019-10-12_final
2019-10-12 11:53:11	ga_ls8c_ard_3-1-0_115079_2019-10-12_final
2019-10-12 11:53:35	ga_ls8c_ard_3-1-0_115080_2019-10-12_final
2022-03-26 11:52:12	ga_ls8c_ard_3-2-1_115078_2022-03-26_final
2022-03-26 11:52:36	ga_ls8c_ard_3-2-1_115079_2022-03-26_final
2022-03-26 11:53:00	ga_ls8c_ard_3-2-1_115080_2022-03-26_final
2022-04-02 11:57:07	ga_ls8c_ard_3-2-1_116075_2022-04-02_final
2022-04-02 11:57:31	ga_ls8c_ard_3-2-1_116076_2022-04-02_final
2022-04-02 11:57:55	ga_ls8c_ard_3-2-1_116077_2022-04-02_final
2022-04-02 11:58:19	ga_ls8c_ard_3-2-1_116078_2022-04-02_final
2022-04-11 11:51:49	ga_ls8c_ard_3-2-1_115077_2022-04-11_final
2022-04-11 11:52:13	ga_ls8c_ard_3-2-1_115078_2022-04-11_final
2022-04-11 11:52:37	ga_ls8c_ard_3-2-1_115079_2022-04-11_final
2022-04-11 11:53:01	ga_ls8c_ard_3-2-1_115080_2022-04-11_final
2022-04-18 11:57:13	ga_ls8c_ard_3-2-1_116075_2022-04-18_final
2022-04-18 11:57:37	ga_ls8c_ard_3-2-1_116076_2022-04-18_final
2022-04-18 11:58:01	ga_ls8c_ard_3-2-1_116077_2022-04-18_final
2022-04-18 11:58:25	ga_ls8c_ard_3-2-1_116078_2022-04-18_final
2022-04-20 11:47:15	ga_ls8c_ard_3-2-1_114081_2022-04-20_final
2022-04-27 11:51:46	ga_ls8c_ard_3-2-1_115077_2022-04-27_final
2022-04-27 11:52:10	ga_ls8c_ard_3-2-1_115078_2022-04-27_final
2022-04-27 11:52:34	ga_ls8c_ard_3-2-1_115079_2022-04-27_final
2022-04-27 11:52:58	ga_ls8c_ard_3-2-1_115080_2022-04-27_final
2022-05-04 11:57:13	ga_ls8c_ard_3-2-1_116075_2022-05-04_final
2022-05-04 11:57:37	ga_ls8c_ard_3-2-1_116076_2022-05-04_final
2022-05-04 11:58:01	ga_ls8c_ard_3-2-1_116077_2022-05-04_final
2022-05-04 11:58:25	ga_ls8c_ard_3-2-1_116078_2022-05-04_final
2022-05-13 11:51:55	ga_ls8c_ard_3-2-1_115077_2022-05-13_final
2022-05-13 11:52:19	ga_ls8c_ard_3-2-1_115078_2022-05-13_final
2022-05-13 11:52:43	ga_ls8c_ard_3-2-1_115079_2022-05-13_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