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
2013-03-23 10:55:30	ga_ls8c_ard_3-0-0_106069_2013-03-23_final
2013-09-25 10:15:00	ga_ls8c_ard_3-0-0_099077_2013-09-25_final
2014-01-10 11:32:44	ga_ls8c_ard_3-0-0_112072_2014-01-10_final
2014-02-21 10:29:39	ga_ls8c_ard_3-0-0_102070_2014-02-21_final
2014-03-20 11:51:38	ga_ls8c_ard_3-0-0_115075_2014-03-20_final
2014-05-07 10:13:08	ga_ls8c_ard_3-0-0_099078_2014-05-07_final
2014-07-26 10:13:01	ga_ls8c_ard_3-0-0_099077_2014-07-26_final
2014-12-02 09:16:53	ga_ls8c_ard_3-0-0_090075_2014-12-01_final
2015-03-13 09:39:38	ga_ls8c_ard_3-0-0_093087_2015-03-13_final
2015-03-31 09:22:43	ga_ls8c_ard_3-0-0_091076_2015-03-30_final
2015-04-18 09:09:54	ga_ls8c_ard_3-0-0_089075_2015-04-17_final
2015-08-29 09:28:28	ga_ls8c_ard_3-0-0_092074_2015-08-28_final
2015-12-03 09:28:00	ga_ls8c_ard_3-0-0_092072_2015-12-02_final
2015-12-31 11:30:47	ga_ls8c_ard_3-0-0_112070_2015-12-31_final
2016-01-11 09:34:07	ga_ls8c_ard_3-0-0_093072_2016-01-11_final
2016-02-17 09:50:30	ga_ls8c_ard_3-0-0_096067_2016-02-17_final
2016-03-22 09:39:35	ga_ls8c_ard_3-0-0_094071_2016-03-22_final
2016-03-31 11:14:11	ga_ls8c_ard_3-0-0_109076_2016-03-31_final
2016-05-18 09:40:00	ga_ls8c_ard_3-0-0_093088_2016-05-18_final
2016-08-30 10:27:39	ga_ls8c_ard_3-0-0_101082_2016-08-30_final
2017-01-03 10:35:39	ga_ls8c_ard_3-0-0_103071_2017-01-03_final
2017-01-08 10:58:58	ga_ls8c_ard_3-0-0_106083_2017-01-08_final
2017-02-02 10:47:03	ga_ls8c_ard_3-0-0_105069_2017-02-02_final
2017-05-12 11:17:18	ga_ls8c_ard_3-0-0_110069_2017-05-12_final
2017-05-15 10:08:33	ga_ls8c_ard_3-0-0_099067_2017-05-15_final
2017-07-04 10:03:20	ga_ls8c_ard_3-0-0_097084_2017-07-04_final
2017-11-13 11:13:59	ga_ls8c_ard_3-0-0_109074_2017-11-13_final
2018-01-20 09:10:32	ga_ls8c_ard_3-0-0_089075_2018-01-19_final
2018-02-08 11:17:45	ga_ls8c_ard_3-0-0_110069_2018-02-08_final
2018-05-21 10:44:57	ga_ls8c_ard_3-0-0_104082_2018-05-21_final
2018-06-03 10:11:54	ga_ls8c_ard_3-0-0_099077_2018-06-03_final
2018-11-02 09:22:48	ga_ls8c_ard_3-0-0_091075_2018-11-01_final
2018-11-09 11:05:53	ga_ls8c_ard_3-0-0_108070_2018-11-09_final
2018-12-07 11:31:22	ga_ls8c_ard_3-0-0_112072_2018-12-07_final
2019-03-24 09:34:01	ga_ls8c_ard_3-1-0_093073_2019-03-24_final
2019-04-07 09:45:31	ga_ls8c_ard_3-1-0_095071_2019-04-07_final
2019-10-23 11:31:52	ga_ls8c_ard_3-1-0_112072_2019-10-23_final
2019-11-21 11:01:41	ga_ls8c_ard_3-1-0_107074_2019-11-21_final
2019-11-29 11:51:32	ga_ls8c_ard_3-1-0_115075_2019-11-29_final
2020-02-17 10:12:45	ga_ls8c_ard_3-1-0_099076_2020-02-17_final
2020-06-08 10:09:06	ga_ls8c_ard_3-1-0_099068_2020-06-08_final
2020-06-26 11:42:11	ga_ls8c_ard_3-1-0_113084_2020-06-26_final
2020-09-23 09:51:40	ga_ls8c_ard_3-1-0_096069_2020-09-23_final
2020-10-29 09:28:59	ga_ls8c_ard_3-1-0_092074_2020-10-28_final
2020-11-22 10:22:01	ga_ls8c_ard_3-1-0_100083_2020-11-22_final
2021-01-10 09:20:18	ga_ls8c_ard_3-2-0_091068_2021-01-09_final
2022-02-13 10:19:23	ga_ls8c_ard_3-2-1_100077_2022-02-13_final
2022-04-05 09:10:17	ga_ls8c_ard_3-2-1_089075_2022-04-04_final
2022-08-21 11:25:02	ga_ls8c_ard_3-2-1_111070_2022-08-21_final
2023-04-11 11:19:04	ga_ls8c_ard_3-2-1_110073_2023-04-11_final
2023-08-30 09:16:30	ga_ls8c_ard_3-2-1_089090_2023-08-29_final
2023-09-10 10:33:40	ga_ls8c_ard_3-2-1_102082_2023-09-10_final
2023-10-20 09:40:21	ga_ls8c_ard_3-2-1_094072_2023-10-20_final
2023-11-16 09:23:05	ga_ls8c_ard_3-2-1_091075_2023-11-15_final
2023-11-26 10:04:12	ga_ls8c_ard_3-2-1_097085_2023-11-26_final
2024-01-20 10:07:02	ga_ls8c_ard_3-2-1_098077_2024-01-20_final
2024-02-21 10:07:48	ga_ls8c_ard_3-2-1_098079_2024-02-21_final
2024-04-16 10:15:26	ga_ls8c_ard_3-2-1_099084_2024-04-16_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