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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
2014-02-10 10:47:56	ga_ls8c_ard_3-0-0_105069_2014-02-10_final
2014-06-05 11:18:45	ga_ls8c_ard_3-0-0_110072_2014-06-05_final
2014-08-08 11:23:55	ga_ls8c_ard_3-0-0_110084_2014-08-08_final
2014-10-21 10:19:56	ga_ls8c_ard_3-0-0_100078_2014-10-21_final
2015-01-27 10:03:42	ga_ls8c_ard_3-0-0_098069_2015-01-27_final
2015-02-12 11:41:40	ga_ls8c_ard_3-0-0_114067_2015-02-12_final
2015-07-03 09:31:28	ga_ls8c_ard_3-0-0_093067_2015-07-03_final
2015-07-10 11:19:48	ga_ls8c_ard_3-0-0_110075_2015-07-10_final
2016-06-30 09:16:56	ga_ls8c_ard_3-0-0_090076_2016-06-29_final
2016-08-11 09:58:12	ga_ls8c_ard_3-0-0_096086_2016-08-11_final
2016-12-26 09:51:26	ga_ls8c_ard_3-0-0_095084_2016-12-26_final
2017-02-02 09:16:08	ga_ls8c_ard_3-0-0_089089_2017-02-01_final
2017-05-02 09:06:00	ga_ls8c_ard_3-1-0_088081_2017-05-01_final
2017-06-05 10:33:17	ga_ls8c_ard_3-0-0_102082_2017-06-05_final
2017-06-16 10:13:38	ga_ls8c_ard_3-0-0_099079_2017-06-16_final
2017-06-21 10:33:23	ga_ls8c_ard_3-0-0_102082_2017-06-21_final
2017-07-26 09:28:47	ga_ls8c_ard_3-0-0_091090_2017-07-25_final
2017-08-18 09:33:55	ga_ls8c_ard_3-0-0_092087_2017-08-18_final
2017-08-31 10:39:32	ga_ls8c_ard_3-0-0_103081_2017-08-31_final
2017-10-06 10:10:11	ga_ls8c_ard_3-0-0_099069_2017-10-06_final
2018-01-19 10:03:22	ga_ls8c_ard_3-0-0_098068_2018-01-19_final
2018-01-26 10:11:04	ga_ls8c_ard_3-0-0_099072_2018-01-26_final
2018-03-31 10:12:58	ga_ls8c_ard_3-0-0_099078_2018-03-31_final
2019-04-22 09:05:45	ga_ls8c_ard_3-0-0_088080_2019-04-21_final
2019-08-08 11:11:14	ga_ls8c_ard_3-1-0_108083_2019-08-08_final
2019-10-04 12:37:49	ga_ls8c_ard_3-2-1_123067_2019-10-04_final
2020-01-08 11:00:22	ga_ls8c_ard_3-1-0_107071_2020-01-08_final
2020-02-05 09:47:16	ga_ls8c_ard_3-1-0_095074_2020-02-05_final
2020-02-07 11:14:11	ga_ls8c_ard_3-1-0_109075_2020-02-07_final
2020-02-17 10:10:45	ga_ls8c_ard_3-1-0_099071_2020-02-17_final
2020-04-30 10:02:49	ga_ls8c_ard_3-1-0_098068_2020-04-30_final
2020-07-11 10:55:26	ga_ls8c_ard_3-1-0_106075_2020-07-11_final
2020-07-24 10:26:59	ga_ls8c_ard_3-1-0_101081_2020-07-24_final
2020-11-16 10:55:52	ga_ls8c_ard_3-1-0_106075_2020-11-16_final
2021-04-03 11:32:02	ga_ls8c_ard_3-2-0_112074_2021-04-03_final
2021-06-08 11:19:42	ga_ls8c_ard_3-2-0_110074_2021-06-08_final
2021-07-01 09:45:30	ga_ls8c_ard_3-2-0_095070_2021-07-01_final
2021-07-07 10:49:42	ga_ls8c_ard_3-2-0_105076_2021-07-07_final
2021-07-17 11:24:01	ga_ls8c_ard_3-2-0_111069_2021-07-17_final
2022-05-18 10:33:12	ga_ls8c_ard_3-2-1_102081_2022-05-18_final
2022-06-21 10:17:07	ga_ls8c_ard_3-2-1_100071_2022-06-21_final
2022-07-30 10:23:29	ga_ls8c_ard_3-2-1_101071_2022-07-30_final
2022-10-24 11:24:42	ga_ls8c_ard_3-2-1_111069_2022-10-24_final
2022-10-24 11:25:06	ga_ls8c_ard_3-2-1_111070_2022-10-24_final
2022-11-12 10:17:30	ga_ls8c_ard_3-2-1_100071_2022-11-12_final
2023-01-10 09:57:57	ga_ls8c_ard_3-2-1_097069_2023-01-10_final
2023-03-01 11:24:57	ga_ls8c_ard_3-2-1_111071_2023-03-01_final
2023-03-09 10:39:25	ga_ls8c_ard_3-2-1_103081_2023-03-09_final
2023-05-10 09:10:39	ga_ls8c_ard_3-2-1_089077_2023-05-09_final
2023-06-25 09:28:23	ga_ls8c_ard_3-2-1_091090_2023-06-24_final
2023-10-17 09:12:16	ga_ls8c_ard_3-2-1_089079_2023-10-16_final
2023-11-24 10:10:59	ga_ls8c_ard_3-2-1_099071_2023-11-24_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