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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
2013-04-27 10:11:29	ga_ls8c_ard_3-0-0_098084_2013-04-27_final
2013-08-24 10:15:10	ga_ls8c_ard_3-0-0_099077_2013-08-24_final
2014-03-16 10:39:56	ga_ls8c_ard_3-0-0_103081_2014-03-16_final
2014-04-21 11:52:18	ga_ls8c_ard_3-0-0_115078_2014-04-21_final
2014-04-27 09:34:15	ga_ls8c_ard_3-0-0_093073_2014-04-27_final
2014-10-01 09:06:29	ga_ls8c_ard_3-0-0_088080_2014-09-30_final
2014-12-17 10:10:27	ga_ls8c_ard_3-0-0_099070_2014-12-17_final
2015-05-05 11:29:49	ga_ls8c_ard_3-0-0_112070_2015-05-05_final
2015-05-21 09:51:14	ga_ls8c_ard_3-0-0_096071_2015-05-21_final
2015-12-15 09:58:18	ga_ls8c_ard_3-0-0_096086_2015-12-15_final
2015-12-19 11:06:05	ga_ls8c_ard_3-0-0_108070_2015-12-19_final
2016-09-10 10:09:33	ga_ls8c_ard_3-0-0_098083_2016-09-10_final
2017-01-30 10:19:22	ga_ls8c_ard_3-0-0_100077_2017-01-30_final
2017-01-30 10:19:45	ga_ls8c_ard_3-0-0_100078_2017-01-30_final
2017-02-14 11:12:28	ga_ls8c_ard_3-0-0_109071_2017-02-14_final
2017-02-17 10:04:28	ga_ls8c_ard_3-0-0_098071_2017-02-17_final
2018-02-17 11:11:31	ga_ls8c_ard_3-0-0_109069_2018-02-17_final
2018-05-29 11:29:30	ga_ls8c_ard_3-0-0_112070_2018-05-29_final
2018-06-24 10:32:15	ga_ls8c_ard_3-0-0_102081_2018-06-24_final
2018-07-30 10:06:37	ga_ls8c_ard_3-0-0_098078_2018-07-30_final
2018-11-12 09:56:42	ga_ls8c_ard_3-0-0_097067_2018-11-12_final
2019-03-26 09:23:15	ga_ls8c_ard_3-1-0_091077_2019-03-25_final
2019-04-16 09:40:29	ga_ls8c_ard_3-1-0_094074_2019-04-16_final
2019-07-17 10:02:54	ga_ls8c_ard_3-1-0_098067_2019-07-17_final
2019-08-28 09:06:31	ga_ls8c_ard_3-1-0_088080_2019-08-27_final
2019-10-08 10:39:49	ga_ls8c_ard_3-1-0_103081_2019-10-08_final
2019-11-15 09:57:07	ga_ls8c_ard_3-1-0_097067_2019-11-15_final
2019-11-23 09:16:49	ga_ls8c_ard_3-1-0_089090_2019-11-22_final
2020-02-05 09:47:16	ga_ls8c_ard_3-1-0_095074_2020-02-05_final
2020-03-17 11:22:32	ga_ls8c_ard_3-1-0_110081_2020-03-17_final
2020-08-20 10:07:24	ga_ls8c_ard_3-1-0_098078_2020-08-20_final
2020-09-22 09:11:36	ga_ls8c_ard_3-1-0_089077_2020-09-21_final
2020-12-11 10:49:21	ga_ls8c_ard_3-1-0_105074_2020-12-11_final
2021-01-28 09:11:27	ga_ls8c_ard_3-2-0_089077_2021-01-27_final
2021-06-29 11:35:33	ga_ls8c_ard_3-2-0_113067_2021-06-29_final
2021-07-13 10:13:02	ga_ls8c_ard_3-2-0_099077_2021-07-13_final
2021-07-25 10:39:26	ga_ls8c_ard_3-2-0_103081_2021-07-25_final
2022-03-02 09:26:29	ga_ls8c_ard_3-2-1_091084_2022-03-01_final
2022-03-03 10:04:10	ga_ls8c_ard_3-2-1_098070_2022-03-03_final
2022-03-24 10:22:55	ga_ls8c_ard_3-2-1_101071_2022-03-24_final
2022-04-21 09:15:56	ga_ls8c_ard_3-2-1_089089_2022-04-20_final
2022-04-29 09:57:43	ga_ls8c_ard_3-2-1_097070_2022-04-29_final
2022-07-05 10:33:30	ga_ls8c_ard_3-2-1_102081_2022-07-05_final
2023-01-16 09:28:22	ga_ls8c_ard_3-2-1_091088_2023-01-15_final
2023-02-18 10:04:46	ga_ls8c_ard_3-2-1_098071_2023-02-18_final
2023-03-13 10:09:54	ga_ls8c_ard_3-2-1_099069_2023-03-13_final
2023-04-07 10:09:23	ga_ls8c_ard_3-2-1_098084_2023-04-07_final
2023-04-14 11:50:46	ga_ls8c_ard_3-2-1_115075_2023-04-14_final
2023-08-20 10:10:18	ga_ls8c_ard_3-2-1_099070_2023-08-20_final
2024-01-21 09:12:12	ga_ls8c_ard_3-2-1_089079_2024-01-20_final
2024-02-07 09:57:28	ga_ls8c_ard_3-2-1_096084_2024-02-07_final
2024-02-08 10:35:57	ga_ls8c_ard_3-2-1_103072_2024-02-08_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