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
2015-09-09 09:16:23	ga_ls8c_ard_3-0-0_089090_2015-09-08_final
2015-09-25 09:16:30	ga_ls8c_ard_3-0-0_089090_2015-09-24_final
2015-10-18 09:22:43	ga_ls8c_ard_3-0-0_090090_2015-10-17_final
2015-12-03 09:35:11	ga_ls8c_ard_3-0-0_092090_2015-12-03_final
2015-12-05 09:22:49	ga_ls8c_ard_3-0-0_090090_2015-12-04_final
2015-12-05 09:23:13	ga_ls8c_ard_3-0-0_090091_2015-12-04_final
2015-12-12 09:28:59	ga_ls8c_ard_3-0-0_091090_2015-12-11_final
2015-12-12 09:29:23	ga_ls8c_ard_3-0-0_091091_2015-12-11_final
2015-12-14 09:16:38	ga_ls8c_ard_3-0-0_089090_2015-12-13_final
2015-12-30 09:16:37	ga_ls8c_ard_3-0-0_089090_2015-12-29_final
2016-01-04 09:35:08	ga_ls8c_ard_3-0-0_092090_2016-01-04_final
2016-01-06 09:22:45	ga_ls8c_ard_3-0-0_090090_2016-01-05_final
2016-01-06 09:23:09	ga_ls8c_ard_3-0-0_090091_2016-01-05_final
2016-01-22 09:22:46	ga_ls8c_ard_3-0-0_090090_2016-01-21_final
2016-01-22 09:23:10	ga_ls8c_ard_3-0-0_090091_2016-01-21_final
2016-02-05 09:35:05	ga_ls8c_ard_3-0-0_092090_2016-02-05_final
2016-02-07 09:22:42	ga_ls8c_ard_3-0-0_090090_2016-02-06_final
2016-02-07 09:23:06	ga_ls8c_ard_3-0-0_090091_2016-02-06_final
2016-03-17 09:28:41	ga_ls8c_ard_3-0-0_091090_2016-03-16_final
2016-03-17 09:29:05	ga_ls8c_ard_3-0-0_091091_2016-03-16_final
2016-03-19 09:16:18	ga_ls8c_ard_3-0-0_089090_2016-03-18_final
2016-04-04 09:16:09	ga_ls8c_ard_3-0-0_089090_2016-04-03_final
2016-04-11 09:22:18	ga_ls8c_ard_3-0-0_090090_2016-04-10_final
2016-04-11 09:22:42	ga_ls8c_ard_3-0-0_090091_2016-04-10_final
2016-06-30 09:22:31	ga_ls8c_ard_3-0-0_090090_2016-06-29_final
2016-06-30 09:22:55	ga_ls8c_ard_3-0-0_090091_2016-06-29_final
2016-07-16 09:22:39	ga_ls8c_ard_3-0-0_090090_2016-07-15_final
2016-07-16 09:23:03	ga_ls8c_ard_3-0-0_090091_2016-07-15_final
2018-02-03 09:28:44	ga_ls8c_ard_3-0-0_091090_2018-02-02_final
2018-02-03 09:29:08	ga_ls8c_ard_3-0-0_091091_2018-02-02_final
2018-02-12 09:22:31	ga_ls8c_ard_3-0-0_090090_2018-02-11_final
2018-02-12 09:22:55	ga_ls8c_ard_3-0-0_090091_2018-02-11_final
2018-02-19 09:29:03	ga_ls8c_ard_3-0-0_091091_2018-02-18_final
2018-02-21 09:16:16	ga_ls8c_ard_3-0-0_089090_2018-02-20_final
2018-02-26 09:34:47	ga_ls8c_ard_3-0-0_092090_2018-02-26_final
2018-02-28 09:22:24	ga_ls8c_ard_3-0-0_090090_2018-02-27_final
2018-02-28 09:22:48	ga_ls8c_ard_3-0-0_090091_2018-02-27_final
2018-03-07 09:28:55	ga_ls8c_ard_3-0-0_091091_2018-03-06_final
2018-03-16 09:22:39	ga_ls8c_ard_3-0-0_090091_2018-03-15_final
2018-03-23 09:28:23	ga_ls8c_ard_3-0-0_091090_2018-03-22_final
2018-03-23 09:28:47	ga_ls8c_ard_3-0-0_091091_2018-03-22_final
2018-03-25 09:16:00	ga_ls8c_ard_3-0-0_089090_2018-03-24_final
2018-04-01 09:22:08	ga_ls8c_ard_3-0-0_090090_2018-03-31_final
2018-04-01 09:22:32	ga_ls8c_ard_3-0-0_090091_2018-03-31_final
2018-04-08 09:28:39	ga_ls8c_ard_3-0-0_091091_2018-04-07_final
2018-04-17 09:22:23	ga_ls8c_ard_3-0-0_090091_2018-04-16_final
2018-04-24 09:28:06	ga_ls8c_ard_3-0-0_091090_2018-04-23_final
2018-04-24 09:28:30	ga_ls8c_ard_3-0-0_091091_2018-04-23_final
2018-05-10 09:27:56	ga_ls8c_ard_3-0-0_091090_2018-05-09_final
2018-05-10 09:28:20	ga_ls8c_ard_3-0-0_091091_2018-05-09_final
2018-05-12 09:15:33	ga_ls8c_ard_3-0-0_089090_2018-05-11_final
2018-05-19 09:22:03	ga_ls8c_ard_3-0-0_090091_2018-05-18_final
2018-05-26 09:28:08	ga_ls8c_ard_3-0-0_091091_2018-05-25_final
2018-06-02 09:33:50	ga_ls8c_ard_3-0-0_092090_2018-06-02_final
2018-06-04 09:21:28	ga_ls8c_ard_3-0-0_090090_2018-06-03_final
2018-06-04 09:21:52	ga_ls8c_ard_3-0-0_090091_2018-06-03_final
2018-06-11 09:27:42	ga_ls8c_ard_3-0-0_091090_2018-06-10_final
2018-06-11 09:28:06	ga_ls8c_ard_3-0-0_091091_2018-06-10_final
2018-06-27 09:27:53	ga_ls8c_ard_3-0-0_091090_2018-06-26_final
2018-06-27 09:28:17	ga_ls8c_ard_3-0-0_091091_2018-06-26_final
2018-06-29 09:15:33	ga_ls8c_ard_3-0-0_089090_2018-06-28_final
2018-07-13 09:28:01	ga_ls8c_ard_3-0-0_091090_2018-07-12_final
2018-07-13 09:28:25	ga_ls8c_ard_3-0-0_091091_2018-07-12_final
2018-07-15 09:15:40	ga_ls8c_ard_3-0-0_089090_2018-07-14_final
2018-07-29 09:28:08	ga_ls8c_ard_3-0-0_091090_2018-07-28_final
2018-07-29 09:28:32	ga_ls8c_ard_3-0-0_091091_2018-07-28_final
2018-08-05 09:34:23	ga_ls8c_ard_3-0-0_092090_2018-08-05_final
2018-08-07 09:22:03	ga_ls8c_ard_3-0-0_090090_2018-08-06_final
2018-08-07 09:22:27	ga_ls8c_ard_3-0-0_090091_2018-08-06_final
2018-08-14 09:28:17	ga_ls8c_ard_3-0-0_091090_2018-08-13_final
2018-08-14 09:28:41	ga_ls8c_ard_3-0-0_091091_2018-08-13_final
2018-08-16 09:15:57	ga_ls8c_ard_3-0-0_089090_2018-08-15_final
2018-08-21 09:34:32	ga_ls8c_ard_3-0-0_092090_2018-08-21_final
2018-08-23 09:22:11	ga_ls8c_ard_3-0-0_090090_2018-08-22_final
2018-08-23 09:22:35	ga_ls8c_ard_3-0-0_090091_2018-08-22_final
2018-09-06 09:34:38	ga_ls8c_ard_3-0-0_092090_2018-09-06_final
2018-09-08 09:22:17	ga_ls8c_ard_3-0-0_090090_2018-09-07_final
2018-09-08 09:22:41	ga_ls8c_ard_3-0-0_090091_2018-09-07_final
2020-06-23 09:34:46	ga_ls8c_ard_3-1-0_092090_2020-06-23_final
2020-07-11 09:22:32	ga_ls8c_ard_3-1-0_090090_2020-07-10_final
2020-07-11 09:22:56	ga_ls8c_ard_3-1-0_090091_2020-07-10_final
2020-07-18 09:28:45	ga_ls8c_ard_3-1-0_091090_2020-07-17_final
2020-07-18 09:29:09	ga_ls8c_ard_3-1-0_091091_2020-07-17_final
2020-07-20 09:16:24	ga_ls8c_ard_3-1-0_089090_2020-07-19_final
2020-07-25 09:34:58	ga_ls8c_ard_3-1-0_092090_2020-07-25_final
2020-08-03 09:28:49	ga_ls8c_ard_3-1-0_091090_2020-08-02_final
2020-08-03 09:29:13	ga_ls8c_ard_3-1-0_091091_2020-08-02_final
2020-08-10 09:35:01	ga_ls8c_ard_3-1-0_092090_2020-08-10_final
2020-08-12 09:22:40	ga_ls8c_ard_3-1-0_090090_2020-08-11_final
2020-08-12 09:23:04	ga_ls8c_ard_3-1-0_090091_2020-08-11_final
2020-08-21 09:16:34	ga_ls8c_ard_3-1-0_089090_2020-08-20_final
2020-08-26 09:35:09	ga_ls8c_ard_3-1-0_092090_2020-08-26_final
2020-08-28 09:22:49	ga_ls8c_ard_3-1-0_090090_2020-08-27_final
2020-08-28 09:23:13	ga_ls8c_ard_3-1-0_090091_2020-08-27_final
2020-09-11 09:35:16	ga_ls8c_ard_3-1-0_092090_2020-09-11_final
2020-09-13 09:22:55	ga_ls8c_ard_3-1-0_090090_2020-09-12_final
2020-09-13 09:23:19	ga_ls8c_ard_3-1-0_090091_2020-09-12_final
2020-09-22 09:16:47	ga_ls8c_ard_3-1-0_089090_2020-09-21_final
2020-09-27 09:35:21	ga_ls8c_ard_3-1-0_092090_2020-09-27_final
2020-09-29 09:23:00	ga_ls8c_ard_3-1-0_090090_2020-09-28_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