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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

60 results

Time (local)	Label
2013-09-01 12:39:30	ga_ls8c_ard_3-2-1_123067_2013-09-01_final
2013-12-06 12:39:04	ga_ls8c_ard_3-2-1_123067_2013-12-06_final
2013-12-22 12:38:55	ga_ls8c_ard_3-2-1_123067_2013-12-22_final
2014-10-22 12:37:41	ga_ls8c_ard_3-2-1_123067_2014-10-22_final
2015-09-23 12:37:26	ga_ls8c_ard_3-2-1_123067_2015-09-23_final
2015-11-26 12:37:37	ga_ls8c_ard_3-2-1_123067_2015-11-26_final
2016-10-27 12:37:48	ga_ls8c_ard_3-2-1_123067_2016-10-27_final
2016-11-28 12:37:48	ga_ls8c_ard_3-2-1_123067_2016-11-28_final
2017-09-28 12:37:40	ga_ls8c_ard_3-2-1_123067_2017-09-28_final
2017-10-14 12:37:45	ga_ls8c_ard_3-2-1_123067_2017-10-14_final
2017-10-30 12:37:45	ga_ls8c_ard_3-2-1_123067_2017-10-30_final
2017-11-15 12:37:42	ga_ls8c_ard_3-2-1_123067_2017-11-15_final
2017-12-17 12:37:38	ga_ls8c_ard_3-2-1_123067_2017-12-17_final
2018-10-17 12:37:18	ga_ls8c_ard_3-2-1_123067_2018-10-17_final
2018-11-02 12:37:22	ga_ls8c_ard_3-2-1_123067_2018-11-02_final
2018-11-18 12:37:24	ga_ls8c_ard_3-2-1_123067_2018-11-18_final
2020-04-29 12:36:56	ga_ls8c_ard_3-2-1_123067_2020-04-29_final
2020-05-15 12:36:52	ga_ls8c_ard_3-2-1_123067_2020-05-15_final
2020-06-16 12:37:07	ga_ls8c_ard_3-2-1_123067_2020-06-16_final
2020-07-02 12:37:15	ga_ls8c_ard_3-2-1_123067_2020-07-02_final
2020-09-20 12:37:44	ga_ls8c_ard_3-2-1_123067_2020-09-20_final
2020-10-06 12:37:47	ga_ls8c_ard_3-2-1_123067_2020-10-06_final
2021-04-16 12:37:08	ga_ls8c_ard_3-2-1_123067_2021-04-16_final
2021-05-02 12:36:59	ga_ls8c_ard_3-2-1_123067_2021-05-02_final
2021-05-18 12:37:04	ga_ls8c_ard_3-2-1_123067_2021-05-18_final
2021-06-03 12:37:13	ga_ls8c_ard_3-2-1_123067_2021-06-03_final
2021-06-19 12:37:19	ga_ls8c_ard_3-2-1_123067_2021-06-19_final
2021-07-05 12:37:22	ga_ls8c_ard_3-2-1_123067_2021-07-05_final
2022-05-05 12:37:18	ga_ls8c_ard_3-2-1_123067_2022-05-05_final
2022-05-21 12:37:24	ga_ls8c_ard_3-2-1_123067_2022-05-21_final
2022-06-06 12:37:31	ga_ls8c_ard_3-2-1_123067_2022-06-06_final
2022-07-08 12:37:42	ga_ls8c_ard_3-2-1_123067_2022-07-08_final
2022-07-24 12:37:48	ga_ls8c_ard_3-2-1_123067_2022-07-24_final
2022-08-25 12:38:00	ga_ls8c_ard_3-2-1_123067_2022-08-25_final
2022-09-10 12:38:03	ga_ls8c_ard_3-2-1_123067_2022-09-10_final
2022-09-26 12:38:06	ga_ls8c_ard_3-2-1_123067_2022-09-26_final
2022-10-28 12:38:05	ga_ls8c_ard_3-2-1_123067_2022-10-28_final
2022-11-13 12:38:02	ga_ls8c_ard_3-2-1_123067_2022-11-13_final
2022-11-29 12:38:01	ga_ls8c_ard_3-2-1_123067_2022-11-29_final
2022-12-15 12:37:57	ga_ls8c_ard_3-2-1_123067_2022-12-15_final
2023-02-17 12:37:41	ga_ls8c_ard_3-2-1_123067_2023-02-17_final
2023-05-08 12:36:50	ga_ls8c_ard_3-2-1_123067_2023-05-08_final
2023-05-24 12:36:46	ga_ls8c_ard_3-2-1_123067_2023-05-24_final
2023-06-09 12:36:52	ga_ls8c_ard_3-2-1_123067_2023-06-09_final
2023-07-11 12:37:09	ga_ls8c_ard_3-2-1_123067_2023-07-11_final
2023-07-27 12:37:15	ga_ls8c_ard_3-2-1_123067_2023-07-27_final
2023-08-12 12:37:20	ga_ls8c_ard_3-2-1_123067_2023-08-12_final
2023-08-28 12:37:27	ga_ls8c_ard_3-2-1_123067_2023-08-28_final
2023-09-13 12:37:30	ga_ls8c_ard_3-2-1_123067_2023-09-13_final
2023-09-29 12:37:35	ga_ls8c_ard_3-2-1_123067_2023-09-29_final
2023-10-15 12:37:37	ga_ls8c_ard_3-2-1_123067_2023-10-15_final
2023-10-31 12:37:40	ga_ls8c_ard_3-2-1_123067_2023-10-31_final
2023-11-16 12:37:40	ga_ls8c_ard_3-2-1_123067_2023-11-16_final
2023-12-02 12:37:38	ga_ls8c_ard_3-2-1_123067_2023-12-02_final
2023-12-18 12:37:40	ga_ls8c_ard_3-2-1_123067_2023-12-18_final
2024-01-19 12:37:34	ga_ls8c_ard_3-2-1_123067_2024-01-19_final
2024-02-04 12:37:33	ga_ls8c_ard_3-2-1_123067_2024-02-04_final
2024-03-07 12:37:19	ga_ls8c_ard_3-2-1_123067_2024-03-07_final
2024-04-08 12:37:03	ga_ls8c_ard_3-2-1_123067_2024-04-08_final
2024-04-24 12:36:55	ga_ls8c_ard_3-2-1_123067_2024-04-24_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