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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

51 results

Time (local)	Label
2014-02-05 10:34:16	ga_ls8c_ard_3-0-0_102081_2014-02-05_final
2014-02-22 11:12:30	ga_ls8c_ard_3-0-0_109069_2014-02-22_final
2015-02-18 09:28:28	ga_ls8c_ard_3-0-0_092074_2015-02-17_final
2015-02-19 10:13:20	ga_ls8c_ard_3-0-0_099078_2015-02-19_final
2015-10-28 11:31:58	ga_ls8c_ard_3-0-0_112073_2015-10-28_final
2015-12-12 09:21:48	ga_ls8c_ard_3-0-0_091072_2015-12-11_final
2016-07-04 10:33:32	ga_ls8c_ard_3-0-0_102082_2016-07-04_final
2016-10-27 09:27:37	ga_ls8c_ard_3-0-0_091086_2016-10-26_final
2016-12-24 11:37:53	ga_ls8c_ard_3-0-0_113072_2016-12-24_final
2017-01-02 09:51:36	ga_ls8c_ard_3-0-0_096069_2017-01-02_final
2017-01-23 10:09:38	ga_ls8c_ard_3-0-0_099068_2017-01-23_final
2017-03-16 09:44:07	ga_ls8c_ard_3-0-0_095067_2017-03-16_final
2017-03-19 10:19:23	ga_ls8c_ard_3-0-0_100078_2017-03-19_final
2017-06-04 09:45:14	ga_ls8c_ard_3-0-0_095070_2017-06-04_final
2018-03-12 09:39:25	ga_ls8c_ard_3-0-0_094071_2018-03-12_final
2018-04-17 09:16:24	ga_ls8c_ard_3-0-0_090076_2018-04-16_final
2018-07-21 10:13:07	ga_ls8c_ard_3-0-0_099079_2018-07-21_final
2018-09-29 09:33:46	ga_ls8c_ard_3-0-0_093072_2018-09-29_final
2018-10-04 09:50:21	ga_ls8c_ard_3-0-0_096067_2018-10-04_final
2018-12-16 09:44:17	ga_ls8c_ard_3-0-0_095067_2018-12-16_final
2019-03-22 09:43:59	ga_ls8c_ard_3-1-0_095067_2019-03-22_final
2019-04-20 09:16:32	ga_ls8c_ard_3-0-0_090076_2019-04-19_final
2019-08-26 10:52:58	ga_ls8c_ard_3-1-0_106068_2019-08-26_final
2019-12-15 10:10:37	ga_ls8c_ard_3-2-0_099070_2019-12-15_final
2020-03-20 10:12:56	ga_ls8c_ard_3-1-0_099077_2020-03-20_final
2020-05-27 11:25:09	ga_ls8c_ard_3-1-0_111073_2020-05-27_final
2020-06-18 10:48:41	ga_ls8c_ard_3-1-0_105074_2020-06-18_final
2020-08-28 10:55:42	ga_ls8c_ard_3-1-0_106075_2020-08-28_final
2020-09-04 09:22:15	ga_ls8c_ard_3-1-0_091073_2020-09-03_final
2020-09-22 10:49:41	ga_ls8c_ard_3-1-0_105075_2020-09-22_final
2020-12-01 10:13:28	ga_ls8c_ard_3-1-0_099077_2020-12-01_final
2021-01-28 10:52:20	ga_ls8c_ard_3-2-0_105082_2021-01-28_final
2021-02-20 09:21:56	ga_ls8c_ard_3-2-0_090088_2021-02-19_final
2021-08-08 10:49:30	ga_ls8c_ard_3-2-0_105075_2021-08-08_final
2021-12-13 10:03:42	ga_ls8c_ard_3-2-1_098068_2021-12-13_final
2022-01-21 10:09:19	ga_ls8c_ard_3-2-1_099067_2022-01-21_final
2022-02-07 10:54:31	ga_ls8c_ard_3-2-1_106072_2022-02-07_final
2022-03-13 09:07:05	ga_ls8c_ard_3-2-1_088082_2022-03-12_final
2022-03-16 09:33:34	ga_ls8c_ard_3-2-1_093071_2022-03-16_final
2022-05-01 11:23:29	ga_ls8c_ard_3-2-1_111068_2022-05-01_final
2022-05-20 10:16:51	ga_ls8c_ard_3-2-1_100071_2022-05-20_final
2022-08-18 10:56:07	ga_ls8c_ard_3-2-1_106075_2022-08-18_final
2022-09-10 09:27:52	ga_ls8c_ard_3-2-1_091086_2022-09-09_final
2022-10-07 09:07:19	ga_ls8c_ard_3-2-1_088081_2022-10-06_final
2022-10-12 09:22:36	ga_ls8c_ard_3-2-1_091073_2022-10-11_final
2022-11-02 11:24:32	ga_ls8c_ard_3-2-1_110084_2022-11-02_final
2023-05-13 11:17:12	ga_ls8c_ard_3-2-1_110069_2023-05-13_final
2023-12-27 09:20:53	ga_ls8c_ard_3-2-1_090085_2023-12-26_final
2024-01-23 10:39:06	ga_ls8c_ard_3-2-1_103080_2024-01-23_final
2024-02-09 09:40:44	ga_ls8c_ard_3-2-1_094073_2024-02-09_final
2024-03-15 10:10:57	ga_ls8c_ard_3-2-1_099072_2024-03-15_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