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
2017-03-21 10:03:24	ga_ls8c_ard_3-0-0_098069_2017-03-21_final
2017-03-22 10:46:39	ga_ls8c_ard_3-0-0_105069_2017-03-22_final
2017-03-23 09:51:01	ga_ls8c_ard_3-0-0_096069_2017-03-23_final
2017-03-23 11:29:54	ga_ls8c_ard_3-0-0_112069_2017-03-23_final
2017-03-24 10:34:16	ga_ls8c_ard_3-0-0_103069_2017-03-24_final
2017-03-25 11:17:32	ga_ls8c_ard_3-0-0_110069_2017-03-25_final
2017-03-26 10:21:54	ga_ls8c_ard_3-0-0_101069_2017-03-26_final
2017-03-27 11:05:09	ga_ls8c_ard_3-0-0_108069_2017-03-27_final
2017-03-28 10:09:32	ga_ls8c_ard_3-0-0_099069_2017-03-28_final
2017-03-29 10:52:47	ga_ls8c_ard_3-0-0_106069_2017-03-29_final
2017-03-30 09:57:09	ga_ls8c_ard_3-0-0_097069_2017-03-30_final
2017-03-31 10:40:25	ga_ls8c_ard_3-0-0_104069_2017-03-31_final
2017-04-08 09:50:55	ga_ls8c_ard_3-0-0_096069_2017-04-08_final
2017-04-08 11:29:48	ga_ls8c_ard_3-0-0_112069_2017-04-08_final
2017-04-09 10:34:10	ga_ls8c_ard_3-0-0_103069_2017-04-09_final
2017-04-10 11:17:25	ga_ls8c_ard_3-0-0_110069_2017-04-10_final
2017-04-11 10:21:47	ga_ls8c_ard_3-0-0_101069_2017-04-11_final
2017-04-22 10:03:08	ga_ls8c_ard_3-0-0_098069_2017-04-22_final
2017-04-23 10:46:23	ga_ls8c_ard_3-0-0_105069_2017-04-23_final
2017-04-26 11:17:15	ga_ls8c_ard_3-0-0_110069_2017-04-26_final
2017-04-27 10:21:36	ga_ls8c_ard_3-0-0_101069_2017-04-27_final
2017-05-08 10:03:05	ga_ls8c_ard_3-0-0_098069_2017-05-08_final
2017-05-09 10:46:22	ga_ls8c_ard_3-0-0_105069_2017-05-09_final
2017-05-09 10:46:46	ga_ls8c_ard_3-0-0_105070_2017-05-09_final
2017-05-10 09:50:45	ga_ls8c_ard_3-0-0_096069_2017-05-10_final
2017-05-10 09:51:09	ga_ls8c_ard_3-0-0_096070_2017-05-10_final
2017-05-10 11:29:38	ga_ls8c_ard_3-0-0_112069_2017-05-10_final
2017-05-10 11:30:02	ga_ls8c_ard_3-0-0_112070_2017-05-10_final
2017-05-11 10:34:02	ga_ls8c_ard_3-0-0_103069_2017-05-11_final
2017-05-11 10:34:26	ga_ls8c_ard_3-0-0_103070_2017-05-11_final
2017-05-12 11:17:18	ga_ls8c_ard_3-0-0_110069_2017-05-12_final
2017-05-12 11:17:42	ga_ls8c_ard_3-0-0_110070_2017-05-12_final
2017-05-13 10:21:42	ga_ls8c_ard_3-0-0_101069_2017-05-13_final
2017-05-13 10:22:05	ga_ls8c_ard_3-0-0_101070_2017-05-13_final
2017-05-24 10:03:17	ga_ls8c_ard_3-0-0_098069_2017-05-24_final
2017-05-24 10:03:40	ga_ls8c_ard_3-0-0_098070_2017-05-24_final
2017-05-25 10:46:33	ga_ls8c_ard_3-0-0_105069_2017-05-25_final
2017-05-25 10:46:57	ga_ls8c_ard_3-0-0_105070_2017-05-25_final
2017-05-30 11:05:08	ga_ls8c_ard_3-0-0_108069_2017-05-30_final
2017-05-30 11:05:32	ga_ls8c_ard_3-0-0_108070_2017-05-30_final
2017-05-31 10:09:31	ga_ls8c_ard_3-0-0_099069_2017-05-31_final
2017-05-31 10:09:55	ga_ls8c_ard_3-0-0_099070_2017-05-31_final
2017-06-04 09:45:14	ga_ls8c_ard_3-0-0_095070_2017-06-04_final
2017-06-04 11:23:43	ga_ls8c_ard_3-0-0_111069_2017-06-04_final
2017-06-04 11:24:07	ga_ls8c_ard_3-0-0_111070_2017-06-04_final
2017-06-05 10:28:06	ga_ls8c_ard_3-0-0_102069_2017-06-05_final
2017-06-05 10:28:30	ga_ls8c_ard_3-0-0_102070_2017-06-05_final
2017-06-06 11:11:22	ga_ls8c_ard_3-0-0_109069_2017-06-06_final
2017-06-06 11:11:46	ga_ls8c_ard_3-0-0_109070_2017-06-06_final
2017-06-07 10:15:45	ga_ls8c_ard_3-0-0_100069_2017-06-07_final
2017-06-07 10:16:09	ga_ls8c_ard_3-1-0_100070_2017-06-07_final
2017-06-09 10:03:25	ga_ls8c_ard_3-0-0_098069_2017-06-09_final
2017-06-09 10:03:49	ga_ls8c_ard_3-0-0_098070_2017-06-09_final
2017-06-10 10:46:41	ga_ls8c_ard_3-0-0_105069_2017-06-10_final
2017-06-10 10:47:05	ga_ls8c_ard_3-0-0_105070_2017-06-10_final
2017-06-11 09:51:04	ga_ls8c_ard_3-0-0_096069_2017-06-11_final
2017-06-11 09:51:28	ga_ls8c_ard_3-0-0_096070_2017-06-11_final
2017-06-12 10:34:20	ga_ls8c_ard_3-0-0_103069_2017-06-12_final
2017-06-13 11:17:36	ga_ls8c_ard_3-0-0_110069_2017-06-13_final
2017-06-14 10:21:59	ga_ls8c_ard_3-0-0_101069_2017-06-14_final
2017-06-14 10:22:23	ga_ls8c_ard_3-0-0_101070_2017-06-14_final
2018-09-16 10:03:22	ga_ls8c_ard_3-0-0_098069_2018-09-16_final
2018-09-16 10:03:46	ga_ls8c_ard_3-0-0_098070_2018-09-16_final
2018-09-17 10:46:38	ga_ls8c_ard_3-0-0_105069_2018-09-17_final
2018-09-17 10:47:02	ga_ls8c_ard_3-0-0_105070_2018-09-17_final
2018-10-20 09:51:15	ga_ls8c_ard_3-0-0_096069_2018-10-20_final
2018-10-20 09:51:39	ga_ls8c_ard_3-0-0_096070_2018-10-20_final
2018-10-20 11:30:08	ga_ls8c_ard_3-0-0_112069_2018-10-20_final
2018-10-20 11:30:32	ga_ls8c_ard_3-0-0_112070_2018-10-20_final
2018-10-21 10:34:31	ga_ls8c_ard_3-0-0_103069_2018-10-21_final
2018-10-22 11:17:47	ga_ls8c_ard_3-0-0_110069_2018-10-22_final
2018-10-22 11:18:11	ga_ls8c_ard_3-0-0_110070_2018-10-22_final
2018-10-23 10:22:10	ga_ls8c_ard_3-0-0_101069_2018-10-23_final
2018-10-23 10:22:34	ga_ls8c_ard_3-0-0_101070_2018-10-23_final
2018-11-07 11:17:50	ga_ls8c_ard_3-0-0_110069_2018-11-07_final
2018-11-08 10:22:13	ga_ls8c_ard_3-0-0_101069_2018-11-08_final
2018-11-08 10:22:37	ga_ls8c_ard_3-0-0_101070_2018-11-08_final
2018-11-30 09:45:31	ga_ls8c_ard_3-0-0_095070_2018-11-30_final
2018-11-30 11:24:01	ga_ls8c_ard_3-0-0_111069_2018-11-30_final
2018-11-30 11:24:24	ga_ls8c_ard_3-0-0_111070_2018-11-30_final
2018-12-01 10:28:23	ga_ls8c_ard_3-0-0_102069_2018-12-01_final
2018-12-01 10:28:47	ga_ls8c_ard_3-0-0_102070_2018-12-01_final
2018-12-02 11:11:39	ga_ls8c_ard_3-0-0_109069_2018-12-02_final
2018-12-03 10:16:01	ga_ls8c_ard_3-0-0_100069_2018-12-03_final
2018-12-16 11:23:58	ga_ls8c_ard_3-0-0_111069_2018-12-16_final
2018-12-16 11:24:22	ga_ls8c_ard_3-0-0_111070_2018-12-16_final
2018-12-17 10:28:20	ga_ls8c_ard_3-0-0_102069_2018-12-17_final
2018-12-17 10:28:44	ga_ls8c_ard_3-0-0_102070_2018-12-17_final
2018-12-18 11:11:36	ga_ls8c_ard_3-0-0_109069_2018-12-18_final
2018-12-19 10:15:59	ga_ls8c_ard_3-0-0_100069_2018-12-19_final
2018-12-23 09:51:16	ga_ls8c_ard_3-0-0_096069_2018-12-23_final
2018-12-23 09:51:40	ga_ls8c_ard_3-0-0_096070_2018-12-23_final
2018-12-23 11:30:09	ga_ls8c_ard_3-0-0_112069_2018-12-23_final
2018-12-23 11:30:33	ga_ls8c_ard_3-0-0_112070_2018-12-23_final
2018-12-24 10:34:32	ga_ls8c_ard_3-0-0_103069_2018-12-24_final
2018-12-25 11:17:47	ga_ls8c_ard_3-0-0_110069_2018-12-25_final
2018-12-26 10:22:10	ga_ls8c_ard_3-0-0_101069_2018-12-26_final
2019-01-06 10:03:37	ga_ls8c_ard_3-0-0_098069_2019-01-06_final
2019-01-06 10:04:01	ga_ls8c_ard_3-0-0_098070_2019-01-06_final
2019-01-07 10:46:52	ga_ls8c_ard_3-0-0_105069_2019-01-07_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