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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
2013-05-22 10:05:35	ga_ls8c_ard_3-0-0_097084_2013-05-22_final
2013-08-19 11:32:18	ga_ls8c_ard_3-0-0_112069_2013-08-19_final
2013-12-31 09:22:54	ga_ls8c_ard_3-0-0_090087_2013-12-30_final
2014-07-09 09:27:42	ga_ls8c_ard_3-0-0_092072_2014-07-08_final
2014-11-13 10:25:19	ga_ls8c_ard_3-0-0_101076_2014-11-13_final
2015-04-02 09:10:43	ga_ls8c_ard_3-0-0_089077_2015-04-01_final
2015-05-05 11:29:49	ga_ls8c_ard_3-0-0_112070_2015-05-05_final
2015-06-12 09:15:58	ga_ls8c_ard_3-0-0_090075_2015-06-11_final
2015-12-15 09:58:18	ga_ls8c_ard_3-0-0_096086_2015-12-15_final
2016-01-18 11:18:00	ga_ls8c_ard_3-0-0_110069_2016-01-18_final
2016-08-04 09:44:26	ga_ls8c_ard_3-0-0_095067_2016-08-04_final
2016-10-18 09:29:24	ga_ls8c_ard_3-0-0_092075_2016-10-17_final
2016-11-21 09:22:14	ga_ls8c_ard_3-0-0_090088_2016-11-20_final
2017-07-12 10:49:12	ga_ls8c_ard_3-0-0_105075_2017-07-12_final
2017-08-10 10:19:19	ga_ls8c_ard_3-0-0_100077_2017-08-10_final
2017-10-25 10:40:44	ga_ls8c_ard_3-0-0_104068_2017-10-25_final
2017-11-17 10:46:51	ga_ls8c_ard_3-0-0_105068_2017-11-17_final
2018-01-18 09:23:18	ga_ls8c_ard_3-0-0_091076_2018-01-17_final
2018-03-08 10:02:59	ga_ls8c_ard_3-0-0_098068_2018-03-08_final
2018-03-12 11:16:43	ga_ls8c_ard_3-0-0_110067_2018-03-12_final
2018-11-26 11:52:44	ga_ls8c_ard_3-0-0_115079_2018-11-26_final
2018-12-18 09:35:07	ga_ls8c_ard_3-0-0_093075_2018-12-18_final
2019-02-08 10:46:46	ga_ls8c_ard_3-0-0_105069_2019-02-08_final
2019-03-11 10:09:45	ga_ls8c_ard_3-1-0_098085_2019-03-11_final
2019-03-27 10:03:19	ga_ls8c_ard_3-1-0_098069_2019-03-27_final
2019-04-20 10:55:24	ga_ls8c_ard_3-0-0_106076_2019-04-20_final
2019-05-04 11:06:59	ga_ls8c_ard_3-1-0_108074_2019-05-04_final
2019-07-12 09:44:21	ga_ls8c_ard_3-1-0_095067_2019-07-12_final
2019-08-03 09:11:23	ga_ls8c_ard_3-1-0_089077_2019-08-02_final
2019-10-09 11:20:41	ga_ls8c_ard_3-1-0_110075_2019-10-09_final
2020-07-16 11:14:24	ga_ls8c_ard_3-1-0_109076_2020-07-16_final
2020-08-22 11:34:44	ga_ls8c_ard_3-1-0_112080_2020-08-22_final
2020-12-08 10:19:39	ga_ls8c_ard_3-1-0_100077_2020-12-08_final
2021-01-07 10:33:30	ga_ls8c_ard_3-2-0_102081_2021-01-07_final
2021-01-31 11:18:26	ga_ls8c_ard_3-2-0_110070_2021-01-31_final
2021-05-28 09:56:29	ga_ls8c_ard_3-2-0_097067_2021-05-28_final
2021-07-29 10:08:46	ga_ls8c_ard_3-2-1_099066_2021-07-29_final
2022-04-10 11:09:45	ga_ls8c_ard_3-2-1_108080_2022-04-10_final
2022-04-11 10:09:45	ga_ls8c_ard_3-2-1_099069_2022-04-11_final
2022-04-15 11:25:08	ga_ls8c_ard_3-2-1_111072_2022-04-15_final
2022-06-29 11:08:11	ga_ls8c_ard_3-2-1_108075_2022-06-29_final
2022-07-11 09:57:36	ga_ls8c_ard_3-2-1_096084_2022-07-11_final
2022-10-05 09:18:30	ga_ls8c_ard_3-2-1_090078_2022-10-04_final
2023-01-24 10:10:17	ga_ls8c_ard_3-2-1_099069_2023-01-24_final
2023-07-11 09:28:34	ga_ls8c_ard_3-2-1_091090_2023-07-10_final
2023-07-25 11:14:17	ga_ls8c_ard_3-2-1_109076_2023-07-25_final
2023-12-19 10:09:57	ga_ls8c_ard_3-2-1_098084_2023-12-19_final
2024-01-23 10:35:54	ga_ls8c_ard_3-2-1_103072_2024-01-23_final
2024-01-23 10:35:54	ga_ls8c_ard_3-2-1_103072_2024-01-23_nrt
2024-02-12 10:08:50	ga_ls8c_ard_3-2-1_099066_2024-02-12_final
2024-03-15 10:10:33	ga_ls8c_ard_3-2-1_099071_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years