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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

63 results

Time (local)	Label
2013-09-22 11:25:01	ga_ls8c_ard_3-0-0_110082_2013-09-22_final
2013-10-06 09:59:16	ga_ls8c_ard_3-0-0_096084_2013-10-06_final
2014-06-12 11:23:47	ga_ls8c_ard_3-0-0_111069_2014-06-12_final
2014-08-24 09:45:53	ga_ls8c_ard_3-0-0_094086_2014-08-24_final
2014-11-13 10:23:19	ga_ls8c_ard_3-0-0_101071_2014-11-13_final
2015-02-20 09:16:31	ga_ls8c_ard_3-0-0_090075_2015-02-19_final
2015-08-06 09:27:17	ga_ls8c_ard_3-0-0_091087_2015-08-05_final
2015-11-25 10:19:27	ga_ls8c_ard_3-0-0_100077_2015-11-25_final
2016-01-14 11:47:30	ga_ls8c_ard_3-0-0_114081_2016-01-14_final
2016-03-03 09:10:25	ga_ls8c_ard_3-0-0_089075_2016-03-02_final
2016-03-08 09:27:44	ga_ls8c_ard_3-0-0_092072_2016-03-07_final
2016-09-17 11:51:26	ga_ls8c_ard_3-0-0_115075_2016-09-17_final
2016-11-26 09:34:23	ga_ls8c_ard_3-0-0_093072_2016-11-26_final
2017-01-08 10:53:23	ga_ls8c_ard_3-0-0_106069_2017-01-08_final
2017-01-30 10:19:45	ga_ls8c_ard_3-0-0_100078_2017-01-30_final
2017-02-12 11:24:02	ga_ls8c_ard_3-0-0_111069_2017-02-12_final
2017-02-15 10:19:38	ga_ls8c_ard_3-0-0_100078_2017-02-15_final
2017-02-23 09:34:09	ga_ls8c_ard_3-0-0_092088_2017-02-23_final
2017-04-30 10:54:52	ga_ls8c_ard_3-0-0_106075_2017-04-30_final
2017-08-27 09:26:58	ga_ls8c_ard_3-0-0_091085_2017-08-26_final
2017-09-20 10:09:41	ga_ls8c_ard_3-0-0_099068_2017-09-20_final
2017-11-18 09:58:00	ga_ls8c_ard_3-0-0_096085_2017-11-18_final
2018-04-27 11:31:28	ga_ls8c_ard_3-0-0_112074_2018-04-27_final
2018-05-03 10:55:08	ga_ls8c_ard_3-0-0_106076_2018-05-03_final
2018-05-12 09:10:46	ga_ls8c_ard_3-0-0_089078_2018-05-11_final
2018-07-05 10:12:12	ga_ls8c_ard_3-0-0_099077_2018-07-05_final
2019-01-01 09:45:53	ga_ls8c_ard_3-0-0_095071_2019-01-01_final
2019-01-21 09:22:18	ga_ls8c_ard_3-0-0_091074_2019-01-20_final
2019-01-23 09:09:55	ga_ls8c_ard_3-0-0_089074_2019-01-22_final
2019-03-08 11:13:46	ga_ls8c_ard_3-1-0_109075_2019-03-08_final
2019-05-15 09:15:41	ga_ls8c_ard_3-0-0_089089_2019-05-14_final
2019-12-12 09:40:08	ga_ls8c_ard_3-1-0_094071_2019-12-12_final
2019-12-15 10:13:25	ga_ls8c_ard_3-2-0_099077_2019-12-15_final
2020-01-06 09:35:50	ga_ls8c_ard_3-1-0_093076_2020-01-06_final
2020-02-03 11:38:31	ga_ls8c_ard_3-1-0_113074_2020-02-03_final
2020-08-06 11:29:50	ga_ls8c_ard_3-1-0_112068_2020-08-06_final
2020-09-04 09:23:27	ga_ls8c_ard_3-1-0_091076_2020-09-03_final
2021-01-09 11:58:01	ga_ls8c_ard_3-2-0_116076_2021-01-09_final
2021-03-01 10:46:36	ga_ls8c_ard_3-2-0_105068_2021-03-01_final
2021-06-11 11:52:13	ga_ls8c_ard_3-2-0_115078_2021-06-11_final
2021-06-12 10:55:24	ga_ls8c_ard_3-2-0_106075_2021-06-12_final
2021-09-03 09:46:38	ga_ls8c_ard_3-2-0_095072_2021-09-03_final
2021-10-10 10:05:21	ga_ls8c_ard_3-2-0_098072_2021-10-10_final
2021-11-10 09:23:16	ga_ls8c_ard_3-2-0_091075_2021-11-09_final
2022-02-15 10:03:49	ga_ls8c_ard_3-2-1_098069_2022-02-15_final
2022-02-22 10:09:09	ga_ls8c_ard_3-2-1_099067_2022-02-22_final
2022-03-07 11:23:54	ga_ls8c_ard_3-2-1_110084_2022-03-07_final
2022-03-30 11:24:14	ga_ls8c_ard_3-2-1_111070_2022-03-30_final
2022-05-01 11:24:16	ga_ls8c_ard_3-2-1_111070_2022-05-01_final
2022-11-04 09:34:30	ga_ls8c_ard_3-2-1_092087_2022-11-04_final
2023-01-30 09:39:13	ga_ls8c_ard_3-2-1_093084_2023-01-30_final
2023-03-29 10:09:44	ga_ls8c_ard_3-2-1_099069_2023-03-29_final
2023-04-04 11:14:39	ga_ls8c_ard_3-2-1_109077_2023-04-04_final
2023-04-15 10:52:44	ga_ls8c_ard_3-2-1_106069_2023-04-15_final
2023-04-30 11:51:05	ga_ls8c_ard_3-2-1_115076_2023-04-30_final
2023-07-02 09:28:17	ga_ls8c_ard_3-2-1_092074_2023-07-01_final
2023-07-30 09:55:12	ga_ls8c_ard_3-2-1_096079_2023-07-30_final
2023-09-05 10:09:54	ga_ls8c_ard_3-2-1_099069_2023-09-05_final
2023-10-25 11:37:50	ga_ls8c_ard_3-2-1_113072_2023-10-25_final
2024-02-06 09:16:12	ga_ls8c_ard_3-2-1_089089_2024-02-05_final
2024-02-08 10:35:57	ga_ls8c_ard_3-2-1_103072_2024-02-08_final
2024-02-27 11:11:33	ga_ls8c_ard_3-2-1_108084_2024-02-27_final
2024-03-03 11:24:26	ga_ls8c_ard_3-2-1_111070_2024-03-03_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