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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

52 results

Time (local)	Label
2013-04-26 09:23:26	ga_ls8c_ard_3-0-0_091072_2013-04-25_final
2013-06-06 09:19:32	ga_ls8c_ard_3-0-0_090077_2013-06-05_final
2013-10-06 09:52:29	ga_ls8c_ard_3-0-0_096067_2013-10-06_final
2013-12-10 10:41:26	ga_ls8c_ard_3-0-0_103082_2013-12-10_final
2013-12-31 09:18:30	ga_ls8c_ard_3-0-0_090076_2013-12-30_final
2014-04-16 11:31:25	ga_ls8c_ard_3-0-0_112072_2014-04-16_final
2015-01-19 09:17:06	ga_ls8c_ard_3-0-0_090076_2015-01-18_final
2015-04-23 09:33:12	ga_ls8c_ard_3-0-0_092087_2015-04-23_final
2015-08-07 10:09:21	ga_ls8c_ard_3-0-0_098084_2015-08-07_final
2015-08-09 09:51:02	ga_ls8c_ard_3-0-0_096069_2015-08-09_final
2016-03-01 09:22:46	ga_ls8c_ard_3-0-0_091075_2016-02-29_final
2016-03-26 10:58:30	ga_ls8c_ard_3-0-0_106083_2016-03-26_final
2016-04-28 09:57:07	ga_ls8c_ard_3-0-0_097069_2016-04-28_final
2016-10-22 10:46:22	ga_ls8c_ard_3-0-0_104082_2016-10-22_final
2016-11-30 09:10:51	ga_ls8c_ard_3-0-0_089075_2016-11-29_final
2017-01-29 09:34:07	ga_ls8c_ard_3-0-0_093072_2017-01-29_final
2017-11-08 09:17:23	ga_ls8c_ard_3-0-0_090076_2017-11-07_final
2017-11-23 10:11:19	ga_ls8c_ard_3-0-0_099072_2017-11-23_final
2018-02-19 11:03:32	ga_ls8c_ard_3-0-0_107080_2018-02-19_final
2018-05-22 11:23:25	ga_ls8c_ard_3-0-0_111070_2018-05-22_final
2018-08-10 09:44:59	ga_ls8c_ard_3-0-0_095070_2018-08-10_final
2019-01-01 09:45:53	ga_ls8c_ard_3-0-0_095071_2019-01-01_final
2019-08-16 10:19:50	ga_ls8c_ard_3-1-0_100078_2019-08-16_final
2019-10-07 11:30:39	ga_ls8c_ard_3-1-0_112069_2019-10-07_final
2019-10-12 10:09:07	ga_ls8c_ard_3-2-1_099066_2019-10-12_final
2019-11-29 10:15:50	ga_ls8c_ard_3-1-0_099083_2019-11-29_final
2019-12-15 10:13:49	ga_ls8c_ard_3-2-0_099078_2019-12-15_final
2020-02-28 11:31:26	ga_ls8c_ard_3-1-0_112072_2020-02-28_final
2020-08-01 09:33:59	ga_ls8c_ard_3-1-0_093072_2020-08-01_final
2020-09-02 09:33:48	ga_ls8c_ard_3-1-0_093071_2020-09-02_final
2020-12-05 11:26:02	ga_ls8c_ard_3-1-0_111073_2020-12-05_final
2021-03-28 10:28:16	ga_ls8c_ard_3-2-0_102069_2021-03-28_final
2021-05-02 09:22:49	ga_ls8c_ard_3-2-0_091076_2021-05-01_final
2021-09-28 09:40:34	ga_ls8c_ard_3-2-0_094072_2021-09-28_final
2021-11-02 10:13:32	ga_ls8c_ard_3-2-0_099077_2021-11-02_final
2022-01-06 09:17:21	ga_ls8c_ard_3-2-1_090076_2022-01-05_final
2022-02-22 10:09:57	ga_ls8c_ard_3-2-1_099069_2022-02-22_final
2022-02-28 09:34:04	ga_ls8c_ard_3-2-1_093072_2022-02-28_final
2022-03-02 09:22:54	ga_ls8c_ard_3-2-1_091075_2022-03-01_final
2022-04-17 11:13:57	ga_ls8c_ard_3-2-1_109075_2022-04-17_final
2022-09-15 09:40:27	ga_ls8c_ard_3-2-1_094071_2022-09-15_final
2022-09-24 11:14:23	ga_ls8c_ard_3-2-1_109074_2022-09-24_final
2022-12-08 09:17:15	ga_ls8c_ard_3-2-1_090075_2022-12-07_final
2023-01-02 10:50:13	ga_ls8c_ard_3-2-1_105076_2023-01-02_final
2023-03-28 09:27:41	ga_ls8c_ard_3-2-1_092072_2023-03-27_final
2023-05-07 10:18:42	ga_ls8c_ard_3-2-1_100077_2023-05-07_final
2023-09-07 11:37:37	ga_ls8c_ard_3-2-1_113072_2023-09-07_final
2023-11-07 09:28:02	ga_ls8c_ard_3-2-1_092072_2023-11-06_final
2023-11-21 09:40:28	ga_ls8c_ard_3-2-1_094072_2023-11-21_final
2024-01-22 09:51:51	ga_ls8c_ard_3-2-1_096070_2024-01-22_final
2024-01-22 09:51:51	ga_ls8c_ard_3-2-1_096070_2024-01-22_nrt
2024-01-26 11:07:33	ga_ls8c_ard_3-2-1_108074_2024-01-26_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