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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

53 results

Time (local)	Label
2013-09-09 10:15:08	ga_ls8c_ard_3-0-0_099077_2013-09-09_final
2014-01-21 11:12:52	ga_ls8c_ard_3-0-0_109069_2014-01-21_final
2014-02-20 11:24:53	ga_ls8c_ard_3-0-0_111069_2014-02-20_final
2014-08-16 10:33:19	ga_ls8c_ard_3-0-0_102081_2014-08-16_final
2014-10-03 10:33:26	ga_ls8c_ard_3-0-0_102081_2014-10-03_final
2014-11-07 09:20:19	ga_ls8c_ard_3-0-0_091068_2014-11-06_final
2014-12-22 10:33:23	ga_ls8c_ard_3-0-0_102081_2014-12-22_final
2015-04-07 09:27:14	ga_ls8c_ard_3-0-0_092072_2015-04-06_final
2015-06-19 09:19:24	ga_ls8c_ard_3-0-0_091068_2015-06-18_final
2015-09-24 10:09:43	ga_ls8c_ard_3-0-0_098084_2015-09-24_final
2016-02-26 11:24:23	ga_ls8c_ard_3-0-0_111070_2016-02-26_final
2016-06-22 10:07:30	ga_ls8c_ard_3-0-0_098079_2016-06-22_final
2016-08-14 10:25:32	ga_ls8c_ard_3-0-0_101077_2016-08-14_final
2016-09-22 10:30:42	ga_ls8c_ard_3-0-0_102074_2016-09-22_final
2016-10-25 09:34:47	ga_ls8c_ard_3-0-0_093073_2016-10-25_final
2017-04-21 09:24:16	ga_ls8c_ard_3-0-0_091080_2017-04-20_final
2017-09-27 10:21:54	ga_ls8c_ard_3-0-0_100083_2017-09-27_final
2017-09-30 10:50:02	ga_ls8c_ard_3-0-0_105076_2017-09-30_final
2017-12-25 11:52:59	ga_ls8c_ard_3-0-0_115079_2017-12-25_final
2018-02-11 10:09:22	ga_ls8c_ard_3-0-0_099068_2018-02-11_final
2018-04-04 11:23:55	ga_ls8c_ard_3-0-0_111070_2018-04-04_final
2018-05-01 11:06:43	ga_ls8c_ard_3-0-0_108074_2018-05-01_final
2018-05-12 09:11:10	ga_ls8c_ard_3-0-0_089079_2018-05-11_final
2018-07-15 09:10:53	ga_ls8c_ard_3-0-0_089078_2018-07-14_final
2018-10-15 11:13:58	ga_ls8c_ard_3-1-0_109075_2018-10-15_final
2019-01-22 10:09:08	ga_ls8c_ard_3-0-0_098083_2019-01-22_final
2019-02-23 10:03:51	ga_ls8c_ard_3-0-0_098070_2019-02-23_final
2019-04-19 10:12:57	ga_ls8c_ard_3-1-0_099078_2019-04-19_final
2019-07-17 10:02:54	ga_ls8c_ard_3-1-0_098067_2019-07-17_final
2019-08-24 09:34:01	ga_ls8c_ard_3-1-0_092087_2019-08-24_final
2020-01-17 09:17:16	ga_ls8c_ard_3-1-0_090076_2020-01-16_final
2020-07-25 11:07:28	ga_ls8c_ard_3-1-0_108074_2020-07-25_final
2020-09-25 11:24:11	ga_ls8c_ard_3-1-0_110084_2020-09-25_final
2020-10-24 09:11:39	ga_ls8c_ard_3-1-0_089077_2020-10-23_final
2021-01-04 10:04:13	ga_ls8c_ard_3-2-0_097085_2021-01-04_final
2021-02-19 10:08:47	ga_ls8c_ard_3-2-1_099066_2021-02-19_final
2021-05-28 11:35:22	ga_ls8c_ard_3-2-0_113067_2021-05-28_final
2021-06-13 09:57:00	ga_ls8c_ard_3-2-0_097068_2021-06-13_final
2021-09-13 10:28:09	ga_ls8c_ard_3-2-0_101083_2021-09-13_final
2022-01-05 10:13:46	ga_ls8c_ard_3-2-1_099078_2022-01-05_final
2022-02-11 10:33:22	ga_ls8c_ard_3-2-1_102081_2022-02-11_final
2022-08-02 10:56:01	ga_ls8c_ard_3-2-1_106075_2022-08-02_final
2022-08-21 11:25:02	ga_ls8c_ard_3-2-1_111070_2022-08-21_final
2022-10-20 10:10:30	ga_ls8c_ard_3-2-1_099069_2022-10-20_final
2022-12-29 11:14:32	ga_ls8c_ard_3-2-1_109075_2022-12-29_final
2023-02-04 09:57:45	ga_ls8c_ard_3-2-1_096084_2023-02-04_final
2023-03-07 09:10:31	ga_ls8c_ard_3-2-1_089075_2023-03-06_final
2023-06-01 10:13:13	ga_ls8c_ard_3-2-1_099079_2023-06-01_final
2023-06-08 10:19:06	ga_ls8c_ard_3-2-1_100078_2023-06-08_final
2023-08-08 11:23:57	ga_ls8c_ard_3-2-1_111069_2023-08-08_final
2023-11-21 11:20:09	ga_ls8c_ard_3-2-1_110074_2023-11-21_final
2023-12-10 10:15:15	ga_ls8c_ard_3-2-1_099082_2023-12-10_final
2024-01-31 11:24:33	ga_ls8c_ard_3-2-1_111070_2024-01-31_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