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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

62 results

Time (local)	Label
2013-05-21 09:24:19	ga_ls8c_ard_3-0-0_090089_2013-05-20_final
2013-09-10 10:58:47	ga_ls8c_ard_3-0-0_106078_2013-09-10_final
2014-04-06 09:22:27	ga_ls8c_ard_3-0-0_090089_2014-04-05_final
2015-01-19 09:22:17	ga_ls8c_ard_3-0-0_090089_2015-01-18_final
2015-02-01 10:25:50	ga_ls8c_ard_3-0-0_101078_2015-02-01_final
2015-04-09 10:56:09	ga_ls8c_ard_3-0-0_106078_2015-04-09_final
2015-04-25 10:56:06	ga_ls8c_ard_3-0-0_106078_2015-04-25_final
2015-05-25 09:34:07	ga_ls8c_ard_3-0-0_092090_2015-05-25_final
2015-06-12 09:21:33	ga_ls8c_ard_3-0-0_090089_2015-06-11_final
2015-06-26 09:34:22	ga_ls8c_ard_3-0-0_092090_2015-06-26_final
2015-08-15 10:56:29	ga_ls8c_ard_3-0-0_106078_2015-08-15_final
2015-10-16 09:35:03	ga_ls8c_ard_3-0-0_092090_2015-10-16_final
2015-10-31 10:25:59	ga_ls8c_ard_3-0-0_101078_2015-10-31_final
2016-03-08 09:34:55	ga_ls8c_ard_3-0-0_092090_2016-03-08_final
2016-03-10 10:56:39	ga_ls8c_ard_3-0-0_106078_2016-03-10_final
2016-04-11 10:56:23	ga_ls8c_ard_3-0-0_106078_2016-04-11_final
2016-06-12 09:34:44	ga_ls8c_ard_3-0-0_092090_2016-06-12_final
2016-07-16 10:56:44	ga_ls8c_ard_3-0-0_106078_2016-07-16_final
2016-07-30 09:35:04	ga_ls8c_ard_3-0-0_092090_2016-07-30_final
2016-10-04 10:57:03	ga_ls8c_ard_3-0-0_106078_2016-10-04_final
2016-11-19 09:35:23	ga_ls8c_ard_3-0-0_092090_2016-11-19_final
2017-02-07 09:35:02	ga_ls8c_ard_3-0-0_092090_2017-02-07_final
2017-03-13 10:56:31	ga_ls8c_ard_3-0-0_106078_2017-03-13_final
2017-03-29 10:56:22	ga_ls8c_ard_3-0-0_106078_2017-03-29_final
2017-07-17 09:34:53	ga_ls8c_ard_3-0-0_092090_2017-07-17_final
2017-08-02 09:35:01	ga_ls8c_ard_3-0-0_092090_2017-08-02_final
2017-09-05 09:22:24	ga_ls8c_ard_3-0-0_090089_2017-09-04_final
2017-12-07 10:26:01	ga_ls8c_ard_3-0-0_101078_2017-12-07_final
2018-02-12 09:22:07	ga_ls8c_ard_3-0-0_090089_2018-02-11_final
2018-02-12 10:56:36	ga_ls8c_ard_3-0-0_106078_2018-02-12_final
2018-04-30 10:25:03	ga_ls8c_ard_3-0-0_101078_2018-04-30_final
2018-05-01 09:34:13	ga_ls8c_ard_3-0-0_092090_2018-05-01_final
2018-05-19 10:55:45	ga_ls8c_ard_3-0-0_106078_2018-05-19_final
2018-06-29 09:13:33	ga_ls8c_ard_3-0-0_089085_2018-06-28_final
2018-07-22 10:55:59	ga_ls8c_ard_3-0-0_106078_2018-07-22_final
2018-08-07 10:56:08	ga_ls8c_ard_3-0-0_106078_2018-08-07_final
2018-10-10 10:56:35	ga_ls8c_ard_3-0-0_106078_2018-10-10_final
2019-01-05 11:02:50	ga_ls8c_ard_3-0-0_107078_2019-01-05_final
2019-01-28 09:30:02	ga_ls8c_ard_3-0-0_092078_2019-01-28_final
2019-01-28 09:31:14	ga_ls8c_ard_3-0-0_092081_2019-01-28_final
2019-02-10 10:35:12	ga_ls8c_ard_3-0-0_103071_2019-02-10_final
2019-02-12 10:25:38	ga_ls8c_ard_3-0-0_101078_2019-02-12_final
2019-02-13 09:30:00	ga_ls8c_ard_3-0-0_092078_2019-02-13_final
2019-02-14 10:12:52	ga_ls8c_ard_3-0-0_099077_2019-02-14_final
2019-02-15 09:22:02	ga_ls8c_ard_3-0-0_090089_2019-02-14_final
2019-02-24 09:16:13	ga_ls8c_ard_3-0-0_089090_2019-02-23_final
2019-03-01 09:34:44	ga_ls8c_ard_3-0-0_092090_2019-03-01_final
2019-03-05 10:44:53	ga_ls8c_ard_3-0-0_104080_2019-03-05_final
2019-04-21 10:00:35	ga_ls8c_ard_3-0-0_097078_2019-04-21_final
2019-04-24 10:31:03	ga_ls8c_ard_3-0-0_102077_2019-04-24_final
2019-04-27 11:00:45	ga_ls8c_ard_3-0-0_107074_2019-04-27_final
2019-04-29 09:15:55	ga_ls8c_ard_3-0-0_089090_2019-04-28_final
2019-05-03 10:25:19	ga_ls8c_ard_3-0-0_101078_2019-05-03_final
2019-05-21 10:15:57	ga_ls8c_ard_3-0-0_099085_2019-05-21_final
2019-05-21 11:52:26	ga_ls8c_ard_3-0-0_115079_2019-05-21_final
2019-05-22 09:21:08	ga_ls8c_ard_3-0-0_090087_2019-05-21_final
2019-05-26 10:28:09	ga_ls8c_ard_3-0-0_102069_2019-05-26_final
2019-05-27 11:15:48	ga_ls8c_ard_3-0-0_109080_2019-05-27_final
2019-05-28 10:16:12	ga_ls8c_ard_3-0-0_100070_2019-05-28_final
2019-06-01 11:32:47	ga_ls8c_ard_3-0-0_112076_2019-06-01_final
2019-06-05 09:31:13	ga_ls8c_ard_3-0-0_092081_2019-06-05_final
2019-06-08 10:02:08	ga_ls8c_ard_3-0-0_097081_2019-06-08_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