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
2015-02-27 09:28:39	ga_ls8c_ard_3-0-0_091090_2015-02-26_final
2015-04-16 09:28:15	ga_ls8c_ard_3-0-0_091090_2015-04-15_final
2015-05-02 09:28:05	ga_ls8c_ard_3-0-0_091090_2015-05-01_final
2015-05-11 09:21:45	ga_ls8c_ard_3-0-0_090090_2015-05-10_final
2015-05-18 09:27:54	ga_ls8c_ard_3-0-0_091090_2015-05-17_final
2015-06-03 09:28:01	ga_ls8c_ard_3-0-0_091090_2015-06-02_final
2015-06-19 09:28:10	ga_ls8c_ard_3-0-0_091090_2015-06-18_final
2017-03-20 09:28:32	ga_ls8c_ard_3-0-0_091090_2017-03-19_final
2017-03-22 09:16:09	ga_ls8c_ard_3-0-0_089090_2017-03-21_final
2017-04-05 09:28:25	ga_ls8c_ard_3-0-0_091090_2017-04-04_final
2017-04-07 09:16:02	ga_ls8c_ard_3-0-0_089090_2017-04-06_final
2017-04-12 09:34:32	ga_ls8c_ard_3-0-0_092090_2017-04-12_final
2017-04-14 09:22:09	ga_ls8c_ard_3-0-0_090090_2017-04-13_final
2017-04-21 09:28:16	ga_ls8c_ard_3-0-0_091090_2017-04-20_final
2017-04-23 09:15:53	ga_ls8c_ard_3-0-0_089090_2017-04-22_final
2017-04-28 09:33:57	ga_ls8c_ard_3-0-0_092089_2017-04-28_final
2017-04-28 09:34:21	ga_ls8c_ard_3-0-0_092090_2017-04-28_final
2017-05-07 09:28:12	ga_ls8c_ard_3-0-0_091090_2017-05-06_final
2017-05-09 09:15:52	ga_ls8c_ard_3-0-0_089090_2017-05-08_final
2017-05-14 09:34:04	ga_ls8c_ard_3-0-0_092089_2017-05-14_final
2017-05-14 09:34:28	ga_ls8c_ard_3-0-0_092090_2017-05-14_final
2017-05-16 09:21:44	ga_ls8c_ard_3-0-0_090089_2017-05-15_final
2017-05-16 09:22:08	ga_ls8c_ard_3-0-0_090090_2017-05-15_final
2017-05-30 09:34:38	ga_ls8c_ard_3-0-0_092090_2017-05-30_final
2017-06-01 09:21:53	ga_ls8c_ard_3-0-0_090089_2017-05-31_final
2017-06-01 09:22:17	ga_ls8c_ard_3-0-0_090090_2017-05-31_final
2017-06-08 09:28:31	ga_ls8c_ard_3-0-0_091090_2017-06-07_final
2017-06-10 09:15:47	ga_ls8c_ard_3-0-0_089089_2017-06-09_final
2017-06-10 09:16:11	ga_ls8c_ard_3-0-0_089090_2017-06-09_final
2017-06-15 09:34:21	ga_ls8c_ard_3-0-0_092089_2017-06-15_final
2017-06-15 09:34:45	ga_ls8c_ard_3-0-0_092090_2017-06-15_final
2017-06-26 09:15:52	ga_ls8c_ard_3-0-0_089089_2017-06-25_final
2017-06-26 09:16:16	ga_ls8c_ard_3-0-0_089090_2017-06-25_final
2017-07-03 09:22:28	ga_ls8c_ard_3-0-0_090090_2017-07-02_final
2017-07-17 09:34:53	ga_ls8c_ard_3-0-0_092090_2017-07-17_final
2017-07-19 09:22:09	ga_ls8c_ard_3-0-0_090089_2017-07-18_final
2017-07-19 09:22:33	ga_ls8c_ard_3-0-0_090090_2017-07-18_final
2017-07-26 09:28:47	ga_ls8c_ard_3-0-0_091090_2017-07-25_final
2017-07-28 09:16:02	ga_ls8c_ard_3-0-0_089089_2017-07-27_final
2017-07-28 09:16:26	ga_ls8c_ard_3-0-0_089090_2017-07-27_final
2017-08-02 09:34:37	ga_ls8c_ard_3-0-0_092089_2017-08-02_final
2017-08-02 09:35:01	ga_ls8c_ard_3-0-0_092090_2017-08-02_final
2017-08-13 09:16:33	ga_ls8c_ard_3-0-0_089090_2017-08-12_final
2017-08-18 09:35:06	ga_ls8c_ard_3-0-0_092090_2017-08-18_final
2017-08-27 09:28:58	ga_ls8c_ard_3-0-0_091090_2017-08-26_final
2017-08-29 09:16:36	ga_ls8c_ard_3-0-0_089090_2017-08-28_final
2017-09-19 09:35:11	ga_ls8c_ard_3-0-0_092090_2017-09-19_final
2017-09-28 09:29:05	ga_ls8c_ard_3-0-0_091090_2017-09-27_final
2017-10-05 09:35:18	ga_ls8c_ard_3-0-0_092090_2017-10-05_final
2017-10-23 09:22:59	ga_ls8c_ard_3-0-0_090090_2017-10-22_final
2017-10-30 09:29:10	ga_ls8c_ard_3-0-0_091090_2017-10-29_final
2017-11-01 09:16:48	ga_ls8c_ard_3-0-0_089090_2017-10-31_final
2017-11-08 09:22:58	ga_ls8c_ard_3-0-0_090090_2017-11-07_final
2017-11-15 09:29:07	ga_ls8c_ard_3-0-0_091090_2017-11-14_final
2017-11-17 09:16:45	ga_ls8c_ard_3-0-0_089090_2017-11-16_final
2017-11-24 09:22:53	ga_ls8c_ard_3-0-0_090090_2017-11-23_final
2017-12-01 09:29:01	ga_ls8c_ard_3-0-0_091090_2017-11-30_final
2017-12-03 09:16:39	ga_ls8c_ard_3-0-0_089090_2017-12-02_final
2017-12-17 09:29:03	ga_ls8c_ard_3-0-0_091090_2017-12-16_final
2017-12-19 09:16:42	ga_ls8c_ard_3-0-0_089090_2017-12-18_final
2017-12-26 09:22:52	ga_ls8c_ard_3-0-0_090090_2017-12-25_final
2018-01-02 09:29:01	ga_ls8c_ard_3-1-0_091090_2018-01-01_final
2018-01-04 09:16:38	ga_ls8c_ard_3-0-0_089090_2018-01-03_final
2018-01-11 09:22:46	ga_ls8c_ard_3-0-0_090090_2018-01-10_final
2018-01-18 09:28:54	ga_ls8c_ard_3-0-0_091090_2018-01-17_final
2018-01-20 09:16:31	ga_ls8c_ard_3-0-0_089090_2018-01-19_final
2018-01-27 09:22:37	ga_ls8c_ard_3-0-0_090090_2018-01-26_final
2018-02-03 09:28:44	ga_ls8c_ard_3-0-0_091090_2018-02-02_final
2018-02-05 09:16:22	ga_ls8c_ard_3-0-0_089090_2018-02-04_final
2018-02-19 09:28:39	ga_ls8c_ard_3-0-0_091090_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
2018-03-14 09:34:37	ga_ls8c_ard_3-0-0_092090_2018-03-14_final
2018-03-16 09:22:15	ga_ls8c_ard_3-0-0_090090_2018-03-15_final
2018-03-30 09:34:31	ga_ls8c_ard_3-0-0_092090_2018-03-30_final
2018-04-01 09:22:08	ga_ls8c_ard_3-0-0_090090_2018-03-31_final
2018-04-15 09:34:22	ga_ls8c_ard_3-0-0_092090_2018-04-15_final
2018-05-01 09:34:13	ga_ls8c_ard_3-0-0_092090_2018-05-01_final
2018-05-03 09:21:50	ga_ls8c_ard_3-0-0_090090_2018-05-02_final
2018-05-17 09:34:02	ga_ls8c_ard_3-0-0_092090_2018-05-17_final
2018-06-02 09:33:26	ga_ls8c_ard_3-0-0_092089_2018-06-02_final
2018-06-02 09:33:50	ga_ls8c_ard_3-0-0_092090_2018-06-02_final
2018-06-18 09:33:34	ga_ls8c_ard_3-0-0_092089_2018-06-18_final
2018-06-18 09:33:58	ga_ls8c_ard_3-0-0_092090_2018-06-18_final
2018-07-04 09:33:44	ga_ls8c_ard_3-0-0_092089_2018-07-04_final
2018-07-04 09:34:08	ga_ls8c_ard_3-0-0_092090_2018-07-04_final
2018-07-06 09:21:23	ga_ls8c_ard_3-0-0_090089_2018-07-05_final
2018-07-06 09:21:47	ga_ls8c_ard_3-0-0_090090_2018-07-05_final
2019-12-07 09:29:11	ga_ls8c_ard_3-1-0_091090_2019-12-06_final
2019-12-09 09:16:49	ga_ls8c_ard_3-1-0_089090_2019-12-08_final
2019-12-23 09:29:08	ga_ls8c_ard_3-1-0_091090_2019-12-22_final
2020-02-18 09:22:42	ga_ls8c_ard_3-1-0_090090_2020-02-17_final
2020-03-05 09:22:37	ga_ls8c_ard_3-1-0_090090_2020-03-04_final
2020-03-12 09:28:45	ga_ls8c_ard_3-1-0_091090_2020-03-11_final
2020-03-14 09:16:22	ga_ls8c_ard_3-1-0_089090_2020-03-13_final
2020-04-20 09:34:37	ga_ls8c_ard_3-1-0_092090_2020-04-20_final
2020-05-01 09:15:58	ga_ls8c_ard_3-1-0_089090_2020-04-30_final
2020-05-08 09:22:05	ga_ls8c_ard_3-1-0_090090_2020-05-07_final
2020-05-15 09:28:17	ga_ls8c_ard_3-1-0_091090_2020-05-14_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