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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

66 results

Time (local)	Label
2013-05-04 10:15:43	ga_ls8c_ard_3-0-0_099079_2013-05-04_final
2013-05-23 09:09:10	ga_ls8c_ard_3-0-0_088082_2013-05-22_final
2014-02-09 10:10:40	ga_ls8c_ard_3-0-0_098084_2014-02-09_final
2014-05-14 10:19:16	ga_ls8c_ard_3-0-0_100078_2014-05-14_final
2015-02-10 10:19:34	ga_ls8c_ard_3-0-0_100078_2015-02-10_final
2015-02-24 10:28:40	ga_ls8c_ard_3-0-0_102070_2015-02-24_final
2015-03-07 10:09:14	ga_ls8c_ard_3-0-0_099068_2015-03-07_final
2015-06-12 10:52:03	ga_ls8c_ard_3-0-0_106068_2015-06-12_final
2015-10-21 11:24:09	ga_ls8c_ard_3-0-0_111069_2015-10-21_final
2015-11-22 09:52:32	ga_ls8c_ard_3-0-0_095087_2015-11-22_final
2016-01-25 11:24:10	ga_ls8c_ard_3-0-0_111069_2016-01-25_final
2016-04-01 10:18:57	ga_ls8c_ard_3-0-0_100077_2016-04-01_final
2016-06-30 10:52:14	ga_ls8c_ard_3-0-0_106067_2016-06-30_final
2016-07-03 11:25:33	ga_ls8c_ard_3-0-0_111073_2016-07-03_final
2017-05-21 09:33:32	ga_ls8c_ard_3-0-0_093072_2017-05-21_final
2017-07-13 11:31:16	ga_ls8c_ard_3-0-0_112072_2017-07-13_final
2017-10-16 09:12:48	ga_ls8c_ard_3-0-0_089080_2017-10-15_final
2018-01-20 10:47:25	ga_ls8c_ard_3-0-0_105070_2018-01-20_final
2018-03-03 11:23:47	ga_ls8c_ard_3-0-0_111069_2018-03-03_final
2018-04-11 11:30:02	ga_ls8c_ard_3-0-0_112070_2018-04-11_final
2018-04-27 11:31:28	ga_ls8c_ard_3-0-0_112074_2018-04-27_final
2018-05-28 09:10:58	ga_ls8c_ard_3-0-0_089079_2018-05-27_final
2018-06-30 09:49:38	ga_ls8c_ard_3-0-0_096067_2018-06-30_final
2018-07-16 11:29:03	ga_ls8c_ard_3-0-0_112068_2018-07-16_final
2018-07-29 09:20:57	ga_ls8c_ard_3-0-0_091072_2018-07-28_final
2018-09-02 09:50:09	ga_ls8c_ard_3-0-0_096067_2018-09-02_final
2018-10-19 10:52:03	ga_ls8c_ard_3-0-0_105082_2018-10-19_final
2018-11-20 10:48:56	ga_ls8c_ard_3-0-0_105074_2018-11-20_final
2019-01-24 11:32:04	ga_ls8c_ard_3-0-0_112074_2019-01-24_final
2019-02-14 10:12:52	ga_ls8c_ard_3-0-0_099077_2019-02-14_final
2019-04-20 10:52:13	ga_ls8c_ard_3-0-0_106068_2019-04-20_final
2019-06-16 09:11:33	ga_ls8c_ard_3-1-0_089078_2019-06-15_final
2019-07-24 11:51:12	ga_ls8c_ard_3-1-0_115075_2019-07-24_final
2019-08-06 11:18:24	ga_ls8c_ard_3-1-0_110070_2019-08-06_final
2019-11-22 10:10:03	ga_ls8c_ard_3-1-0_098084_2019-11-22_final
2019-11-23 10:49:19	ga_ls8c_ard_3-1-0_105074_2019-11-23_final
2020-01-14 10:23:16	ga_ls8c_ard_3-1-0_101071_2020-01-14_final
2020-01-23 10:17:27	ga_ls8c_ard_3-1-0_100072_2020-01-23_final
2020-02-17 10:10:21	ga_ls8c_ard_3-1-0_099070_2020-02-17_final
2020-03-01 11:18:16	ga_ls8c_ard_3-1-0_110070_2020-03-01_final
2020-03-14 10:49:40	ga_ls8c_ard_3-1-0_105076_2020-03-14_final
2020-04-06 10:53:15	ga_ls8c_ard_3-1-0_106070_2020-04-06_final
2020-04-30 10:02:49	ga_ls8c_ard_3-1-0_098068_2020-04-30_final
2020-07-11 10:55:50	ga_ls8c_ard_3-1-0_106076_2020-07-11_final
2020-08-31 09:45:45	ga_ls8c_ard_3-1-0_095070_2020-08-31_final
2020-10-21 11:58:55	ga_ls8c_ard_3-1-0_116078_2020-10-21_final
2021-03-09 11:37:34	ga_ls8c_ard_3-2-0_113072_2021-03-09_final
2021-03-23 10:12:56	ga_ls8c_ard_3-2-0_099077_2021-03-23_final
2021-06-06 09:57:57	ga_ls8c_ard_3-2-0_096086_2021-06-06_final
2021-06-06 11:31:15	ga_ls8c_ard_3-2-0_112072_2021-06-06_final
2021-08-18 11:24:15	ga_ls8c_ard_3-2-0_111069_2021-08-18_final
2021-09-04 10:33:30	ga_ls8c_ard_3-2-0_102081_2021-09-04_final
2021-10-27 09:10:57	ga_ls8c_ard_3-2-0_089075_2021-10-26_final
2021-12-04 10:13:29	ga_ls8c_ard_3-2-0_099077_2021-12-04_final
2022-01-13 09:22:19	ga_ls8c_ard_3-2-1_091073_2022-01-12_final
2022-02-14 09:21:46	ga_ls8c_ard_3-2-1_091072_2022-02-13_final
2022-04-18 10:16:44	ga_ls8c_ard_3-2-1_100071_2022-04-18_final
2022-07-04 11:23:56	ga_ls8c_ard_3-2-1_111068_2022-07-04_final
2022-07-20 11:23:58	ga_ls8c_ard_3-2-1_111068_2022-07-20_final
2023-04-27 09:39:44	ga_ls8c_ard_3-2-1_094072_2023-04-27_final
2023-07-31 10:39:16	ga_ls8c_ard_3-2-1_103081_2023-07-31_final
2023-09-04 09:27:50	ga_ls8c_ard_3-2-1_092072_2023-09-03_final
2023-09-29 09:23:00	ga_ls8c_ard_3-2-1_091075_2023-09-28_final
2023-11-23 09:28:07	ga_ls8c_ard_3-2-1_092072_2023-11-22_final
2024-02-21 10:07:00	ga_ls8c_ard_3-2-1_098077_2024-02-21_final
2024-03-26 11:31:06	ga_ls8c_ard_3-2-1_112072_2024-03-26_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