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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
2014-02-26 10:52:54	ga_ls8c_ard_3-0-0_105082_2014-02-26_final
2014-06-08 10:13:11	ga_ls8c_ard_3-0-0_099078_2014-06-08_final
2014-10-20 09:33:53	ga_ls8c_ard_3-0-0_093071_2014-10-20_final
2015-01-17 09:27:53	ga_ls8c_ard_3-0-0_092072_2015-01-16_final
2015-03-16 10:09:43	ga_ls8c_ard_3-0-0_098085_2015-03-16_final
2015-07-23 09:09:43	ga_ls8c_ard_3-0-0_089074_2015-07-22_final
2015-10-05 11:24:31	ga_ls8c_ard_3-0-0_111070_2015-10-05_final
2016-03-20 11:30:27	ga_ls8c_ard_3-0-0_112070_2016-03-20_final
2016-07-15 10:13:28	ga_ls8c_ard_3-0-0_099078_2016-07-15_final
2016-07-16 09:21:27	ga_ls8c_ard_3-0-0_090087_2016-07-15_final
2016-10-10 10:19:36	ga_ls8c_ard_3-0-0_100077_2016-10-10_final
2016-12-05 09:28:11	ga_ls8c_ard_3-0-0_092072_2016-12-04_final
2016-12-17 11:30:56	ga_ls8c_ard_3-0-0_112070_2016-12-17_final
2017-03-20 09:21:21	ga_ls8c_ard_3-0-0_091072_2017-03-19_final
2017-03-22 10:46:15	ga_ls8c_ard_3-0-0_105068_2017-03-22_final
2017-04-12 09:27:21	ga_ls8c_ard_3-0-0_092072_2017-04-11_final
2017-05-31 10:13:07	ga_ls8c_ard_3-0-0_099078_2017-05-31_final
2017-08-27 09:22:58	ga_ls8c_ard_3-0-0_091075_2017-08-26_final
2017-11-20 11:17:20	ga_ls8c_ard_3-0-0_110067_2017-11-20_final
2018-01-07 09:40:20	ga_ls8c_ard_3-0-0_094072_2018-01-07_final
2018-06-02 09:33:50	ga_ls8c_ard_3-0-0_092090_2018-06-02_final
2018-09-07 10:13:06	ga_ls8c_ard_3-0-0_099078_2018-09-07_final
2018-09-20 09:39:52	ga_ls8c_ard_3-0-0_094072_2018-09-20_final
2018-10-17 09:25:31	ga_ls8c_ard_3-0-0_091082_2018-10-16_final
2019-03-03 09:16:46	ga_ls8c_ard_3-0-0_090076_2019-03-02_final
2019-03-28 09:10:05	ga_ls8c_ard_3-1-0_089075_2019-03-27_final
2019-05-21 10:12:45	ga_ls8c_ard_3-0-0_099077_2019-05-21_final
2019-08-08 09:33:33	ga_ls8c_ard_3-1-0_092086_2019-08-08_final
2019-11-23 09:14:02	ga_ls8c_ard_3-1-0_089083_2019-11-22_final
2019-12-07 09:23:12	ga_ls8c_ard_3-1-0_091075_2019-12-06_final
2020-01-17 09:20:51	ga_ls8c_ard_3-1-0_090085_2020-01-16_final
2020-02-05 11:25:45	ga_ls8c_ard_3-1-0_111073_2020-02-05_final
2020-09-28 10:13:49	ga_ls8c_ard_3-1-0_099078_2020-09-28_final
2020-10-25 09:51:43	ga_ls8c_ard_3-1-0_096069_2020-10-25_final
2021-05-09 09:34:10	ga_ls8c_ard_3-2-0_092089_2021-05-09_final
2021-05-10 10:13:03	ga_ls8c_ard_3-2-0_099078_2021-05-10_final
2021-05-25 09:34:20	ga_ls8c_ard_3-2-0_092089_2021-05-25_final
2021-09-15 10:13:24	ga_ls8c_ard_3-2-0_099077_2021-09-15_final
2022-04-02 10:19:02	ga_ls8c_ard_3-2-1_100077_2022-04-02_final
2022-04-11 10:10:09	ga_ls8c_ard_3-2-1_099070_2022-04-11_final
2022-07-08 09:28:19	ga_ls8c_ard_3-2-1_091088_2022-07-07_final
2022-10-12 09:22:36	ga_ls8c_ard_3-2-1_091073_2022-10-11_final
2023-06-25 09:27:11	ga_ls8c_ard_3-2-1_091087_2023-06-24_final
2023-06-29 10:37:01	ga_ls8c_ard_3-2-1_103076_2023-06-29_final
2023-08-06 11:38:18	ga_ls8c_ard_3-2-1_113074_2023-08-06_final
2023-10-11 11:24:15	ga_ls8c_ard_3-2-1_111069_2023-10-11_final
2023-12-07 09:39:54	ga_ls8c_ard_3-2-1_094071_2023-12-07_final
2024-01-04 10:04:14	ga_ls8c_ard_3-2-1_098070_2024-01-04_final
2024-02-11 09:28:46	ga_ls8c_ard_3-2-1_092074_2024-02-10_final
2024-02-12 10:13:13	ga_ls8c_ard_3-2-1_099077_2024-02-12_final
2024-02-12 10:13:37	ga_ls8c_ard_3-2-1_099078_2024-02-12_final
2024-03-17 09:58:10	ga_ls8c_ard_3-2-1_097071_2024-03-17_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