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
2013-04-01 10:08:03	ga_ls8c_ard_3-0-0_099068_2013-04-01_final
2013-07-24 10:54:45	ga_ls8c_ard_3-0-0_106068_2013-07-24_final
2013-07-25 11:37:38	ga_ls8c_ard_3-0-0_113067_2013-07-25_final
2013-08-01 10:04:57	ga_ls8c_ard_3-0-0_098067_2013-08-01_final
2013-08-01 10:05:21	ga_ls8c_ard_3-0-0_098068_2013-08-01_final
2013-08-02 10:48:37	ga_ls8c_ard_3-0-0_105068_2013-08-02_final
2013-08-04 10:36:15	ga_ls8c_ard_3-0-0_103068_2013-08-04_final
2013-08-05 09:40:14	ga_ls8c_ard_3-0-0_094067_2013-08-05_final
2013-08-09 10:54:48	ga_ls8c_ard_3-0-0_106068_2013-08-09_final
2013-08-10 11:37:40	ga_ls8c_ard_3-0-0_113067_2013-08-10_final
2013-10-31 11:25:25	ga_ls8c_ard_3-0-0_111068_2013-10-31_final
2017-08-29 10:46:19	ga_ls8c_ard_3-0-0_105067_2017-08-29_final
2017-08-30 09:50:41	ga_ls8c_ard_3-0-0_096067_2017-08-30_final
2017-08-30 09:51:05	ga_ls8c_ard_3-0-0_096068_2017-08-30_final
2018-03-02 10:40:07	ga_ls8c_ard_3-0-0_104068_2018-03-02_final
2018-03-03 11:23:23	ga_ls8c_ard_3-0-0_111068_2018-03-03_final
2018-03-04 10:27:45	ga_ls8c_ard_3-0-0_102068_2018-03-04_final
2018-03-05 09:31:43	ga_ls8c_ard_3-0-0_093067_2018-03-05_final
2018-03-05 09:32:07	ga_ls8c_ard_3-0-0_093068_2018-03-05_final
2018-03-11 10:33:51	ga_ls8c_ard_3-0-0_103068_2018-03-11_final
2018-03-12 09:37:50	ga_ls8c_ard_3-0-0_094067_2018-03-12_final
2018-03-12 11:16:43	ga_ls8c_ard_3-0-0_110067_2018-03-12_final
2018-03-12 11:17:07	ga_ls8c_ard_3-0-0_110068_2018-03-12_final
2018-03-13 10:21:29	ga_ls8c_ard_3-0-0_101068_2018-03-13_final
2018-03-14 09:25:51	ga_ls8c_ard_3-0-0_092068_2018-03-13_final
2018-03-14 11:04:44	ga_ls8c_ard_3-0-0_108068_2018-03-14_final
2018-03-15 10:09:06	ga_ls8c_ard_3-0-0_099068_2018-03-15_final
2018-03-16 10:52:21	ga_ls8c_ard_3-0-0_106068_2018-03-16_final
2018-03-17 09:56:43	ga_ls8c_ard_3-0-0_097068_2018-03-17_final
2018-03-18 10:39:59	ga_ls8c_ard_3-0-0_104068_2018-03-18_final
2018-03-19 11:23:14	ga_ls8c_ard_3-0-0_111068_2018-03-19_final
2018-03-20 10:27:36	ga_ls8c_ard_3-0-0_102068_2018-03-20_final
2018-03-21 09:31:59	ga_ls8c_ard_3-0-0_093068_2018-03-21_final
2018-04-19 10:39:42	ga_ls8c_ard_3-0-0_104068_2018-04-19_final
2018-04-20 11:22:57	ga_ls8c_ard_3-0-0_111068_2018-04-20_final
2018-04-21 10:27:19	ga_ls8c_ard_3-0-0_102068_2018-04-21_final
2018-04-22 09:31:42	ga_ls8c_ard_3-0-0_093068_2018-04-22_final
2018-06-03 10:08:19	ga_ls8c_ard_3-0-0_099068_2018-06-03_final
2018-06-04 10:51:10	ga_ls8c_ard_3-0-0_106067_2018-06-04_final
2018-06-04 10:51:34	ga_ls8c_ard_3-0-0_106068_2018-06-04_final
2018-06-05 09:55:33	ga_ls8c_ard_3-0-0_097067_2018-06-05_final
2018-06-05 09:55:57	ga_ls8c_ard_3-0-0_097068_2018-06-05_final
2018-06-06 10:38:48	ga_ls8c_ard_3-0-0_104067_2018-06-06_final
2018-06-06 10:39:12	ga_ls8c_ard_3-0-0_104068_2018-06-06_final
2018-06-07 09:43:12	ga_ls8c_ard_3-0-0_095067_2018-06-07_final
2018-06-07 11:22:05	ga_ls8c_ard_3-0-0_111067_2018-06-07_final
2018-06-07 11:22:29	ga_ls8c_ard_3-0-0_111068_2018-06-07_final
2018-06-08 10:26:28	ga_ls8c_ard_3-0-0_102067_2018-06-08_final
2018-06-08 10:26:52	ga_ls8c_ard_3-0-0_102068_2018-06-08_final
2018-06-09 09:30:52	ga_ls8c_ard_3-0-0_093067_2018-06-09_final
2018-06-09 09:31:16	ga_ls8c_ard_3-0-0_093068_2018-06-09_final
2018-06-19 10:08:04	ga_ls8c_ard_3-0-0_099067_2018-06-19_final
2018-06-19 10:08:28	ga_ls8c_ard_3-0-0_099068_2018-06-19_final
2018-06-20 10:51:20	ga_ls8c_ard_3-0-0_106067_2018-06-20_final
2018-06-20 10:51:44	ga_ls8c_ard_3-0-0_106068_2018-06-20_final
2018-06-21 09:56:07	ga_ls8c_ard_3-0-0_097068_2018-06-21_final
2018-06-21 11:34:37	ga_ls8c_ard_3-0-0_113067_2018-06-21_final
2018-07-05 10:08:13	ga_ls8c_ard_3-0-0_099067_2018-07-05_final
2018-07-05 10:08:37	ga_ls8c_ard_3-0-0_099068_2018-07-05_final
2018-07-06 10:51:29	ga_ls8c_ard_3-0-0_106067_2018-07-06_final
2018-07-06 10:51:53	ga_ls8c_ard_3-0-0_106068_2018-07-06_final
2018-07-07 09:55:52	ga_ls8c_ard_3-0-0_097067_2018-07-07_final
2018-07-07 09:56:16	ga_ls8c_ard_3-0-0_097068_2018-07-07_final
2018-07-07 11:34:46	ga_ls8c_ard_3-0-0_113067_2018-07-07_final
2019-07-21 11:17:05	ga_ls8c_ard_3-1-0_110067_2019-07-21_final
2019-07-21 11:17:29	ga_ls8c_ard_3-1-0_110068_2019-07-21_final
2019-07-22 10:21:52	ga_ls8c_ard_3-1-0_101068_2019-07-22_final
2019-07-23 09:25:51	ga_ls8c_ard_3-1-0_092067_2019-07-22_final
2019-07-23 09:26:15	ga_ls8c_ard_3-1-0_092068_2019-07-22_final
2019-07-23 11:04:44	ga_ls8c_ard_3-1-0_108067_2019-07-23_final
2019-07-23 11:05:08	ga_ls8c_ard_3-1-0_108068_2019-07-23_final
2019-07-24 10:09:07	ga_ls8c_ard_3-1-0_099067_2019-07-24_final
2019-07-24 10:09:31	ga_ls8c_ard_3-1-0_099068_2019-07-24_final
2019-07-25 10:52:24	ga_ls8c_ard_3-1-0_106067_2019-07-25_final
2019-07-25 10:52:47	ga_ls8c_ard_3-1-0_106068_2019-07-25_final
2019-08-17 10:58:43	ga_ls8c_ard_3-1-0_107067_2019-08-17_final
2019-08-17 10:59:07	ga_ls8c_ard_3-1-0_107068_2019-08-17_final
2019-08-18 10:03:06	ga_ls8c_ard_3-1-0_098067_2019-08-18_final
2019-08-18 10:03:30	ga_ls8c_ard_3-1-0_098068_2019-08-18_final
2019-08-18 11:41:59	ga_ls8c_ard_3-1-0_114067_2019-08-18_final
2019-08-19 10:46:22	ga_ls8c_ard_3-1-0_105067_2019-08-19_final
2019-08-19 10:46:46	ga_ls8c_ard_3-1-0_105068_2019-08-19_final
2019-08-20 09:50:45	ga_ls8c_ard_3-1-0_096067_2019-08-20_final
2019-08-20 09:51:09	ga_ls8c_ard_3-1-0_096068_2019-08-20_final
2019-08-20 11:29:38	ga_ls8c_ard_3-1-0_112067_2019-08-20_final
2019-08-20 11:30:02	ga_ls8c_ard_3-1-0_112068_2019-08-20_final
2019-10-12 10:09:55	ga_ls8c_ard_3-1-0_099068_2019-10-12_final
2019-10-13 10:52:47	ga_ls8c_ard_3-1-0_106067_2019-10-13_final
2019-10-13 10:53:11	ga_ls8c_ard_3-1-0_106068_2019-10-13_final
2019-11-18 10:28:00	ga_ls8c_ard_3-1-0_102067_2019-11-18_final
2019-11-18 10:28:24	ga_ls8c_ard_3-1-0_102068_2019-11-18_final
2019-11-19 09:32:47	ga_ls8c_ard_3-1-0_093068_2019-11-19_final
2019-11-19 11:11:40	ga_ls8c_ard_3-1-0_109068_2019-11-19_final
2019-11-20 10:16:02	ga_ls8c_ard_3-1-0_100068_2019-11-20_final
2019-11-21 09:20:24	ga_ls8c_ard_3-1-0_091068_2019-11-20_final
2019-11-21 10:58:53	ga_ls8c_ard_3-1-0_107067_2019-11-21_final
2019-11-21 10:59:17	ga_ls8c_ard_3-1-0_107068_2019-11-21_final
2019-11-29 10:09:51	ga_ls8c_ard_3-1-0_099068_2019-11-29_final
2019-11-30 10:52:43	ga_ls8c_ard_3-1-0_106067_2019-11-30_final
2019-11-30 10:53:07	ga_ls8c_ard_3-1-0_106068_2019-11-30_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