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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

62 results

Time (local)	Label
2013-04-01 10:09:15	ga_ls8c_ard_3-0-0_099071_2013-04-01_final
2013-05-06 10:05:46	ga_ls8c_ard_3-0-0_097085_2013-05-06_final
2013-09-05 10:39:52	ga_ls8c_ard_3-0-0_103077_2013-09-05_final
2014-03-03 09:34:50	ga_ls8c_ard_3-0-0_092088_2014-03-03_final
2014-05-27 09:51:56	ga_ls8c_ard_3-0-0_095087_2014-05-27_final
2014-06-12 11:23:47	ga_ls8c_ard_3-0-0_111069_2014-06-12_final
2014-06-21 09:39:56	ga_ls8c_ard_3-0-0_094072_2014-06-21_final
2014-12-25 09:23:47	ga_ls8c_ard_3-0-0_091077_2014-12-24_final
2015-01-03 10:54:49	ga_ls8c_ard_3-0-0_106073_2015-01-03_final
2015-05-05 11:29:49	ga_ls8c_ard_3-0-0_112070_2015-05-05_final
2015-05-14 09:50:12	ga_ls8c_ard_3-0-0_095084_2015-05-14_final
2015-07-24 11:31:52	ga_ls8c_ard_3-0-0_112074_2015-07-24_final
2015-12-29 10:07:04	ga_ls8c_ard_3-0-0_098077_2015-12-29_final
2016-01-17 10:35:56	ga_ls8c_ard_3-0-0_103072_2016-01-17_final
2016-02-13 10:20:03	ga_ls8c_ard_3-0-0_100079_2016-02-13_final
2016-03-05 10:39:43	ga_ls8c_ard_3-0-0_103082_2016-03-05_final
2016-04-09 09:33:52	ga_ls8c_ard_3-0-0_092088_2016-04-09_final
2016-04-28 09:57:07	ga_ls8c_ard_3-0-0_097069_2016-04-28_final
2016-05-02 09:40:03	ga_ls8c_ard_3-0-0_093088_2016-05-02_final
2016-05-19 10:19:17	ga_ls8c_ard_3-0-0_100078_2016-05-19_final
2016-09-09 09:23:06	ga_ls8c_ard_3-0-0_091075_2016-09-08_final
2017-03-14 11:42:10	ga_ls8c_ard_3-0-0_113084_2017-03-14_final
2017-07-10 09:21:53	ga_ls8c_ard_3-0-0_091073_2017-07-09_final
2017-09-23 10:46:12	ga_ls8c_ard_3-0-0_104082_2017-09-23_final
2018-02-13 11:37:28	ga_ls8c_ard_3-0-0_113072_2018-02-13_final
2018-02-21 10:46:47	ga_ls8c_ard_3-0-0_105069_2018-02-21_final
2018-04-11 11:28:50	ga_ls8c_ard_3-0-0_112067_2018-04-11_final
2018-04-11 11:30:02	ga_ls8c_ard_3-0-0_112070_2018-04-11_final
2018-06-26 10:18:18	ga_ls8c_ard_3-0-0_100077_2018-06-26_final
2018-06-30 11:31:19	ga_ls8c_ard_3-0-0_112074_2018-06-30_final
2018-08-27 10:33:11	ga_ls8c_ard_3-0-0_102082_2018-08-27_final
2018-09-18 09:57:00	ga_ls8c_ard_3-0-0_096084_2018-09-18_final
2018-12-29 09:20:58	ga_ls8c_ard_3-0-0_090086_2018-12-28_final
2019-04-13 10:49:17	ga_ls8c_ard_3-1-0_105076_2019-04-13_final
2019-04-20 09:16:08	ga_ls8c_ard_3-0-0_090075_2019-04-19_final
2019-05-25 09:47:40	ga_ls8c_ard_3-0-0_095076_2019-05-25_final
2019-05-31 10:46:20	ga_ls8c_ard_3-0-0_105068_2019-05-31_final
2019-07-09 10:54:19	ga_ls8c_ard_3-1-0_106072_2019-07-09_final
2019-09-04 10:49:37	ga_ls8c_ard_3-1-0_105075_2019-09-04_final
2020-02-11 09:14:33	ga_ls8c_ard_3-1-0_089085_2020-02-10_final
2020-03-01 09:39:47	ga_ls8c_ard_3-1-0_094071_2020-03-01_final
2020-03-15 11:35:43	ga_ls8c_ard_3-1-0_112083_2020-03-15_final
2020-03-24 09:46:11	ga_ls8c_ard_3-1-0_095072_2020-03-24_final
2020-07-23 09:40:08	ga_ls8c_ard_3-1-0_094072_2020-07-23_final
2020-07-28 11:35:35	ga_ls8c_ard_3-1-0_113067_2020-07-28_final
2021-02-16 11:17:11	ga_ls8c_ard_3-2-0_110067_2021-02-16_final
2021-04-17 10:03:49	ga_ls8c_ard_3-2-0_098070_2021-04-17_final
2021-06-16 10:27:55	ga_ls8c_ard_3-2-0_102068_2021-06-16_final
2021-08-29 09:28:52	ga_ls8c_ard_3-2-0_092074_2021-08-28_final
2021-11-29 09:57:44	ga_ls8c_ard_3-2-0_096084_2021-11-29_final
2022-01-06 10:54:14	ga_ls8c_ard_3-2-1_106071_2022-01-06_final
2022-11-29 09:23:03	ga_ls8c_ard_3-2-1_091074_2022-11-28_final
2023-01-08 10:09:08	ga_ls8c_ard_3-2-1_099066_2023-01-08_final
2023-01-24 10:09:53	ga_ls8c_ard_3-2-1_099068_2023-01-24_final
2023-01-26 11:38:49	ga_ls8c_ard_3-2-1_113074_2023-01-26_final
2023-06-23 09:38:42	ga_ls8c_ard_3-2-1_093085_2023-06-23_final
2023-06-27 10:51:45	ga_ls8c_ard_3-2-1_105082_2023-06-27_final
2023-08-20 10:10:42	ga_ls8c_ard_3-2-1_099071_2023-08-20_final
2023-09-01 10:37:50	ga_ls8c_ard_3-2-1_103077_2023-09-01_final
2024-01-01 09:34:10	ga_ls8c_ard_3-2-1_093072_2024-01-01_final
2024-01-02 10:19:01	ga_ls8c_ard_3-2-1_100076_2024-01-02_final
2024-01-23 10:35:54	ga_ls8c_ard_3-2-1_103072_2024-01-23_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