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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
2013-11-08 10:41:35	ga_ls8c_ard_3-0-0_103082_2013-11-08_final
2014-07-26 10:13:25	ga_ls8c_ard_3-0-0_099078_2014-07-26_final
2016-01-25 11:24:10	ga_ls8c_ard_3-0-0_111069_2016-01-25_final
2016-11-16 10:39:46	ga_ls8c_ard_3-0-0_103081_2016-11-16_final
2017-03-03 10:19:08	ga_ls8c_ard_3-0-0_100077_2017-03-03_final
2017-03-11 09:28:26	ga_ls8c_ard_3-1-0_092074_2017-03-10_final
2017-04-08 09:51:18	ga_ls8c_ard_3-0-0_096070_2017-04-08_final
2017-08-10 10:19:43	ga_ls8c_ard_3-0-0_100078_2017-08-10_final
2017-11-23 10:16:07	ga_ls8c_ard_3-0-0_099084_2017-11-23_final
2018-02-04 11:41:42	ga_ls8c_ard_3-0-0_114067_2018-02-04_final
2018-04-23 10:20:56	ga_ls8c_ard_3-0-0_100083_2018-04-23_final
2018-05-06 09:44:43	ga_ls8c_ard_3-0-0_095070_2018-05-06_final
2018-07-21 10:12:19	ga_ls8c_ard_3-0-0_099077_2018-07-21_final
2018-08-17 09:50:50	ga_ls8c_ard_3-0-0_096069_2018-08-17_final
2019-02-19 10:32:59	ga_ls8c_ard_3-0-0_102081_2019-02-19_final
2019-03-04 11:40:06	ga_ls8c_ard_3-0-0_113079_2019-03-04_final
2019-04-09 11:14:01	ga_ls8c_ard_3-1-0_109076_2019-04-09_final
2019-05-26 10:32:56	ga_ls8c_ard_3-0-0_102081_2019-05-26_final
2019-07-14 11:13:40	ga_ls8c_ard_3-1-0_109074_2019-07-14_final
2019-11-26 09:40:09	ga_ls8c_ard_3-1-0_094071_2019-11-26_final
2019-12-06 10:20:01	ga_ls8c_ard_3-1-0_100078_2019-12-06_final
2019-12-09 09:10:50	ga_ls8c_ard_3-1-0_089075_2019-12-08_final
2020-02-21 11:24:30	ga_ls8c_ard_3-1-0_111070_2020-02-21_final
2020-03-25 10:33:01	ga_ls8c_ard_3-1-0_102081_2020-03-25_final
2020-05-23 10:08:58	ga_ls8c_ard_3-1-0_099068_2020-05-23_final
2020-05-28 10:32:43	ga_ls8c_ard_3-1-0_102081_2020-05-28_final
2020-06-05 11:17:27	ga_ls8c_ard_3-1-0_110069_2020-06-05_final
2020-07-16 09:33:55	ga_ls8c_ard_3-1-0_093072_2020-07-16_final
2020-09-22 09:11:36	ga_ls8c_ard_3-1-0_089077_2020-09-21_final
2020-12-03 09:57:31	ga_ls8c_ard_3-1-0_097068_2020-12-03_final
2021-01-01 09:28:56	ga_ls8c_ard_3-2-0_092074_2020-12-31_final
2021-02-04 10:55:18	ga_ls8c_ard_3-2-0_106074_2021-02-04_final
2021-04-15 11:57:05	ga_ls8c_ard_3-2-0_116075_2021-04-15_final
2021-04-15 11:57:29	ga_ls8c_ard_3-2-0_116076_2021-04-15_final
2021-05-10 10:12:39	ga_ls8c_ard_3-2-0_099077_2021-05-10_final
2021-06-08 09:39:37	ga_ls8c_ard_3-2-0_094071_2021-06-08_final
2021-06-08 11:17:42	ga_ls8c_ard_3-2-0_110069_2021-06-08_final
2021-06-15 11:24:19	ga_ls8c_ard_3-2-0_111070_2021-06-15_final
2021-06-27 10:13:00	ga_ls8c_ard_3-2-0_099077_2021-06-27_final
2021-11-02 10:11:09	ga_ls8c_ard_3-2-0_099071_2021-11-02_final
2021-11-02 11:53:13	ga_ls8c_ard_3-2-0_115079_2021-11-02_final
2021-11-04 09:57:35	ga_ls8c_ard_3-2-0_097068_2021-11-04_final
2021-11-27 10:02:54	ga_ls8c_ard_3-2-1_098066_2021-11-27_final
2022-01-04 09:28:07	ga_ls8c_ard_3-2-1_092072_2022-01-03_final
2022-01-05 10:10:58	ga_ls8c_ard_3-2-1_099071_2022-01-05_final
2022-01-29 09:23:01	ga_ls8c_ard_3-2-1_091075_2022-01-28_final
2022-02-07 09:17:37	ga_ls8c_ard_3-2-1_090077_2022-02-06_final
2022-03-23 11:18:09	ga_ls8c_ard_3-2-1_110070_2022-03-23_final
2022-03-27 09:16:53	ga_ls8c_ard_3-2-1_090076_2022-03-26_final
2022-05-13 10:13:26	ga_ls8c_ard_3-2-1_099078_2022-05-13_final
2022-05-14 09:17:01	ga_ls8c_ard_3-2-1_090076_2022-05-13_final
2022-08-22 10:33:48	ga_ls8c_ard_3-2-1_102081_2022-08-22_final
2022-09-10 09:27:52	ga_ls8c_ard_3-2-1_091086_2022-09-09_final
2022-09-17 09:29:18	ga_ls8c_ard_3-2-1_092074_2022-09-16_final
2023-02-03 09:10:30	ga_ls8c_ard_3-2-1_089074_2023-02-02_final
2023-03-05 09:21:43	ga_ls8c_ard_3-2-1_091072_2023-03-04_final
2023-03-07 09:10:31	ga_ls8c_ard_3-2-1_089075_2023-03-06_final
2023-09-20 09:28:44	ga_ls8c_ard_3-2-1_092074_2023-09-19_final
2023-11-15 10:17:06	ga_ls8c_ard_3-2-1_100071_2023-11-15_final
2024-01-11 10:13:38	ga_ls8c_ard_3-2-1_099078_2024-01-11_final
2024-02-02 09:34:31	ga_ls8c_ard_3-2-1_093073_2024-02-02_final
2024-03-14 09:28:30	ga_ls8c_ard_3-2-1_092074_2024-03-13_final
2024-04-24 09:21:08	ga_ls8c_ard_3-2-1_091072_2024-04-23_nrt

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