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

58 results

Time (local)	Label
2013-06-12 10:22:54	ga_ls8c_ard_3-0-0_100081_2013-06-12_final
2013-07-03 10:41:25	ga_ls8c_ard_3-0-0_103081_2013-07-03_final
2014-03-04 10:14:05	ga_ls8c_ard_3-0-0_099078_2014-03-04_final
2014-05-29 09:39:36	ga_ls8c_ard_3-0-0_093087_2014-05-29_final
2014-07-23 11:22:34	ga_ls8c_ard_3-0-0_110081_2014-07-23_final
2014-08-19 09:25:21	ga_ls8c_ard_3-0-0_091081_2014-08-18_final
2015-01-22 09:45:34	ga_ls8c_ard_3-0-0_095070_2015-01-22_final
2015-04-16 09:21:28	ga_ls8c_ard_3-0-0_091073_2015-04-15_final
2015-05-14 11:23:30	ga_ls8c_ard_3-0-0_111070_2015-05-14_final
2015-06-15 09:44:53	ga_ls8c_ard_3-0-0_095070_2015-06-15_final
2016-02-16 09:10:27	ga_ls8c_ard_3-0-0_089075_2016-02-15_final
2016-02-23 10:52:41	ga_ls8c_ard_3-0-0_106068_2016-02-23_final
2016-02-24 11:35:33	ga_ls8c_ard_3-0-0_113067_2016-02-24_final
2016-07-03 11:23:57	ga_ls8c_ard_3-0-0_111069_2016-07-03_final
2016-11-13 10:10:04	ga_ls8c_ard_3-0-0_098084_2016-11-13_final
2016-12-10 11:24:47	ga_ls8c_ard_3-0-0_111070_2016-12-10_final
2016-12-18 10:36:06	ga_ls8c_ard_3-0-0_103072_2016-12-18_final
2017-01-27 09:46:29	ga_ls8c_ard_3-0-0_095072_2017-01-27_final
2017-06-20 11:23:49	ga_ls8c_ard_3-0-0_111069_2017-06-20_final
2017-07-02 10:13:42	ga_ls8c_ard_3-0-0_099079_2017-07-02_final
2017-07-15 11:23:43	ga_ls8c_ard_3-0-0_110084_2017-07-15_final
2018-04-29 09:39:01	ga_ls8c_ard_3-0-0_094071_2018-04-29_final
2018-05-24 09:30:57	ga_ls8c_ard_3-0-0_093067_2018-05-24_final
2018-07-31 09:09:24	ga_ls8c_ard_3-0-0_089074_2018-07-30_final
2018-10-09 10:12:55	ga_ls8c_ard_3-0-0_099077_2018-10-09_final
2018-10-19 09:11:59	ga_ls8c_ard_3-0-0_089079_2018-10-18_final
2019-02-14 10:09:40	ga_ls8c_ard_3-0-0_099069_2019-02-14_final
2019-03-09 10:20:56	ga_ls8c_ard_3-1-0_100082_2019-03-09_final
2019-05-08 10:45:30	ga_ls8c_ard_3-0-0_104082_2019-05-08_final
2019-06-29 10:18:00	ga_ls8c_ard_3-1-0_100074_2019-06-29_final
2019-07-09 10:52:19	ga_ls8c_ard_3-1-0_106067_2019-07-09_final
2019-07-12 09:51:32	ga_ls8c_ard_3-1-0_095085_2019-07-12_final
2019-08-28 09:06:31	ga_ls8c_ard_3-1-0_088080_2019-08-27_final
2019-08-28 09:07:19	ga_ls8c_ard_3-1-0_088082_2019-08-27_final
2019-09-10 10:10:34	ga_ls8c_ard_3-1-0_099070_2019-09-10_final
2019-10-06 09:10:53	ga_ls8c_ard_3-1-0_089075_2019-10-05_final
2020-03-14 09:16:22	ga_ls8c_ard_3-1-0_089090_2020-03-13_final
2020-04-08 09:05:59	ga_ls8c_ard_3-1-0_088080_2020-04-07_final
2020-07-30 11:24:02	ga_ls8c_ard_3-1-0_111069_2020-07-30_final
2021-02-22 10:42:28	ga_ls8c_ard_3-2-0_104073_2021-02-22_final
2021-03-23 10:09:44	ga_ls8c_ard_3-2-0_099069_2021-03-23_final
2021-08-06 09:20:11	ga_ls8c_ard_3-2-0_091068_2021-08-05_final
2022-02-22 10:10:45	ga_ls8c_ard_3-2-1_099071_2022-02-22_final
2022-04-15 11:23:32	ga_ls8c_ard_3-2-1_111068_2022-04-15_final
2022-04-27 10:12:53	ga_ls8c_ard_3-2-1_099077_2022-04-27_final
2022-08-21 11:25:02	ga_ls8c_ard_3-2-1_111070_2022-08-21_final
2022-10-13 10:07:50	ga_ls8c_ard_3-2-1_098078_2022-10-13_final
2022-11-05 11:51:51	ga_ls8c_ard_3-2-1_115075_2022-11-05_final
2022-11-22 10:53:20	ga_ls8c_ard_3-2-1_106068_2022-11-22_final
2023-04-21 10:19:13	ga_ls8c_ard_3-2-1_100078_2023-04-21_final
2023-04-25 11:30:59	ga_ls8c_ard_3-2-1_112072_2023-04-25_final
2023-06-01 10:13:13	ga_ls8c_ard_3-2-1_099079_2023-06-01_final
2023-07-08 10:32:56	ga_ls8c_ard_3-2-1_102081_2023-07-08_final
2023-09-05 10:13:05	ga_ls8c_ard_3-2-1_099077_2023-09-05_final
2023-09-23 10:00:50	ga_ls8c_ard_3-2-1_097077_2023-09-23_final
2023-10-15 09:26:38	ga_ls8c_ard_3-2-1_091084_2023-10-14_final
2023-10-15 09:26:38	ga_ls8c_ard_3-2-1_091084_2023-10-14_nrt
2023-12-10 10:13:39	ga_ls8c_ard_3-2-1_099078_2023-12-10_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