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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
2013-04-22 09:48:35	ga_ls8c_ard_3-0-0_095073_2013-04-22_final
2013-06-12 10:23:18	ga_ls8c_ard_3-0-0_100082_2013-06-12_final
2013-07-01 09:15:17	ga_ls8c_ard_3-0-0_089082_2013-06-30_final
2013-09-02 10:09:23	ga_ls8c_ard_3-0-0_098078_2013-09-02_final
2013-12-06 09:29:41	ga_ls8c_ard_3-0-0_091088_2013-12-05_final
2014-06-17 10:07:03	ga_ls8c_ard_3-0-0_098078_2014-06-17_final
2015-01-02 10:09:57	ga_ls8c_ard_3-0-0_099069_2015-01-02_final
2015-01-08 09:33:42	ga_ls8c_ard_3-0-0_093071_2015-01-08_final
2015-04-08 10:12:30	ga_ls8c_ard_3-0-0_099077_2015-04-08_final
2015-06-28 09:16:51	ga_ls8c_ard_3-0-0_090077_2015-06-27_final
2016-02-06 10:13:32	ga_ls8c_ard_3-0-0_099078_2016-02-06_final
2016-02-20 10:25:22	ga_ls8c_ard_3-0-0_101077_2016-02-20_final
2016-03-11 09:59:01	ga_ls8c_ard_3-0-0_097073_2016-03-11_final
2016-05-11 09:33:48	ga_ls8c_ard_3-0-0_092088_2016-05-11_final
2016-07-30 11:05:58	ga_ls8c_ard_3-0-0_108070_2016-07-30_final
2016-09-21 09:46:14	ga_ls8c_ard_3-0-0_095071_2016-09-21_final
2016-12-05 11:07:52	ga_ls8c_ard_3-0-0_108074_2016-12-05_final
2016-12-13 10:19:35	ga_ls8c_ard_3-0-0_100077_2016-12-13_final
2016-12-29 10:19:56	ga_ls8c_ard_3-0-0_100078_2016-12-29_final
2017-01-24 10:54:06	ga_ls8c_ard_3-0-0_106071_2017-01-24_final
2017-02-01 10:03:23	ga_ls8c_ard_3-0-0_098068_2017-02-01_final
2017-03-28 10:09:08	ga_ls8c_ard_3-0-0_099068_2017-03-28_final
2017-07-06 09:46:36	ga_ls8c_ard_3-0-0_095073_2017-07-06_final
2017-10-29 10:20:00	ga_ls8c_ard_3-0-0_100078_2017-10-29_final
2017-11-06 09:32:56	ga_ls8c_ard_3-0-0_092084_2017-11-06_final
2017-11-08 09:17:23	ga_ls8c_ard_3-0-0_090076_2017-11-07_final
2017-11-20 11:17:20	ga_ls8c_ard_3-0-0_110067_2017-11-20_final
2017-12-27 11:35:50	ga_ls8c_ard_3-0-0_113067_2017-12-27_final
2018-01-14 11:25:45	ga_ls8c_ard_3-0-0_111073_2018-01-14_final
2018-02-06 09:51:38	ga_ls8c_ard_3-0-0_096070_2018-02-06_final
2018-05-07 10:32:22	ga_ls8c_ard_3-0-0_102081_2018-05-07_final
2018-05-24 09:39:20	ga_ls8c_ard_3-0-0_093088_2018-05-24_final
2018-07-05 11:50:18	ga_ls8c_ard_3-0-0_115075_2018-07-05_final
2019-01-06 10:07:12	ga_ls8c_ard_3-0-0_098078_2019-01-06_final
2019-01-24 11:34:51	ga_ls8c_ard_3-0-0_112081_2019-01-24_final
2019-02-14 10:12:52	ga_ls8c_ard_3-0-0_099077_2019-02-14_final
2019-04-22 09:05:45	ga_ls8c_ard_3-0-0_088080_2019-04-21_final
2019-06-24 09:56:38	ga_ls8c_ard_3-1-0_097067_2019-06-24_final
2019-06-29 10:21:59	ga_ls8c_ard_3-1-0_100084_2019-06-29_final
2019-08-12 09:06:27	ga_ls8c_ard_3-1-0_088080_2019-08-11_final
2020-02-17 10:10:45	ga_ls8c_ard_3-1-0_099071_2020-02-17_final
2020-05-13 11:13:56	ga_ls8c_ard_3-1-0_109076_2020-05-13_final
2020-05-22 11:07:23	ga_ls8c_ard_3-1-0_108075_2020-05-22_final
2020-06-10 10:01:33	ga_ls8c_ard_3-1-0_097080_2020-06-10_final
2020-10-08 10:49:20	ga_ls8c_ard_3-1-0_105074_2020-10-08_final
2020-10-27 09:45:20	ga_ls8c_ard_3-1-0_094084_2020-10-27_final
2021-02-05 09:58:29	ga_ls8c_ard_3-2-0_097071_2021-02-05_final
2021-02-11 09:21:47	ga_ls8c_ard_3-2-0_091072_2021-02-10_final
2021-04-08 10:12:51	ga_ls8c_ard_3-2-0_099077_2021-04-08_final
2021-12-02 10:25:51	ga_ls8c_ard_3-2-0_101077_2021-12-02_final
2022-01-14 10:03:58	ga_ls8c_ard_3-2-1_098069_2022-01-14_final
2022-03-01 10:16:55	ga_ls8c_ard_3-2-1_100071_2022-03-01_final
2022-12-17 09:10:35	ga_ls8c_ard_3-2-1_089074_2022-12-16_final
2023-01-14 11:12:04	ga_ls8c_ard_3-2-1_109069_2023-01-14_final
2023-01-17 10:04:50	ga_ls8c_ard_3-2-1_098071_2023-01-17_final
2023-02-03 09:10:30	ga_ls8c_ard_3-2-1_089074_2023-02-02_final
2023-02-14 10:33:32	ga_ls8c_ard_3-2-1_102081_2023-02-14_final
2023-05-07 10:19:06	ga_ls8c_ard_3-2-1_100078_2023-05-07_final
2023-05-26 09:11:25	ga_ls8c_ard_3-2-1_089079_2023-05-25_final
2024-02-17 10:28:08	ga_ls8c_ard_3-2-1_102068_2024-02-17_final
2024-03-05 09:33:57	ga_ls8c_ard_3-2-1_093072_2024-03-05_final
2024-03-11 10:35:42	ga_ls8c_ard_3-2-1_103072_2024-03-11_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