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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
2014-01-21 11:14:28	ga_ls8c_ard_3-0-0_109073_2014-01-21_final
2014-01-31 11:53:53	ga_ls8c_ard_3-0-0_115079_2014-01-31_final
2014-02-25 10:04:52	ga_ls8c_ard_3-0-0_098070_2014-02-25_final
2014-05-17 10:49:20	ga_ls8c_ard_3-0-0_105076_2014-05-17_final
2014-09-27 09:26:22	ga_ls8c_ard_3-0-0_092068_2014-09-26_final
2014-10-22 09:20:19	ga_ls8c_ard_3-0-0_091068_2014-10-21_final
2014-12-04 09:07:18	ga_ls8c_ard_3-0-0_088082_2014-12-03_final
2015-01-15 09:39:51	ga_ls8c_ard_3-0-0_094071_2015-01-15_final
2015-03-01 09:11:29	ga_ls8c_ard_3-0-0_089078_2015-02-28_final
2015-06-08 09:45:02	ga_ls8c_ard_3-0-0_094086_2015-06-08_final
2015-09-22 10:21:40	ga_ls8c_ard_3-0-0_100083_2015-09-22_final
2015-12-03 09:34:47	ga_ls8c_ard_3-0-0_092089_2015-12-03_final
2016-03-15 11:11:34	ga_ls8c_ard_3-0-0_109069_2016-03-15_final
2016-06-28 09:34:28	ga_ls8c_ard_3-0-0_092089_2016-06-28_final
2016-08-12 10:39:28	ga_ls8c_ard_3-0-0_103081_2016-08-12_final
2016-10-30 09:55:44	ga_ls8c_ard_3-0-0_096079_2016-10-30_final
2017-10-14 09:20:22	ga_ls8c_ard_3-0-0_091068_2017-10-13_final
2017-12-15 11:13:54	ga_ls8c_ard_3-0-0_109074_2017-12-15_final
2018-03-12 11:17:30	ga_ls8c_ard_3-0-0_110069_2018-03-12_final
2018-04-29 09:39:25	ga_ls8c_ard_3-0-0_094072_2018-04-29_final
2018-05-15 09:39:14	ga_ls8c_ard_3-0-0_094072_2018-05-15_final
2018-08-19 11:19:22	ga_ls8c_ard_3-0-0_110074_2018-08-19_final
2018-11-12 11:42:22	ga_ls8c_ard_3-0-0_113084_2018-11-12_final
2018-12-11 09:31:20	ga_ls8c_ard_3-0-0_092081_2018-12-11_final
2018-12-29 09:20:58	ga_ls8c_ard_3-0-0_090086_2018-12-28_final
2019-04-13 10:49:17	ga_ls8c_ard_3-1-0_105076_2019-04-13_final
2019-04-14 11:30:56	ga_ls8c_ard_3-1-0_112072_2019-04-14_final
2019-06-30 09:21:35	ga_ls8c_ard_3-1-0_091072_2019-06-29_final
2019-08-28 09:07:19	ga_ls8c_ard_3-1-0_088082_2019-08-27_final
2019-12-16 10:53:29	ga_ls8c_ard_3-2-0_106069_2019-12-16_final
2020-02-17 10:10:45	ga_ls8c_ard_3-1-0_099071_2020-02-17_final
2020-07-20 10:48:54	ga_ls8c_ard_3-1-0_105074_2020-07-20_final
2020-07-27 10:55:31	ga_ls8c_ard_3-1-0_106075_2020-07-27_final
2020-11-17 09:57:52	ga_ls8c_ard_3-1-0_097069_2020-11-17_final
2021-04-16 09:28:33	ga_ls8c_ard_3-2-0_091090_2021-04-15_final
2021-04-30 11:13:41	ga_ls8c_ard_3-2-0_109075_2021-04-30_final
2021-06-24 09:38:06	ga_ls8c_ard_3-2-0_094067_2021-06-24_final
2021-11-18 10:10:39	ga_ls8c_ard_3-2-0_099070_2021-11-18_final
2021-11-18 10:11:03	ga_ls8c_ard_3-2-0_099071_2021-11-18_final
2022-02-13 10:17:24	ga_ls8c_ard_3-2-1_100072_2022-02-13_final
2022-06-13 09:33:36	ga_ls8c_ard_3-2-1_092086_2022-06-13_final
2022-07-10 10:50:02	ga_ls8c_ard_3-2-1_105076_2022-07-10_final
2022-07-20 11:28:46	ga_ls8c_ard_3-2-1_111080_2022-07-20_final
2022-08-28 09:52:43	ga_ls8c_ard_3-2-1_096071_2022-08-28_final
2022-10-22 11:38:14	ga_ls8c_ard_3-2-1_113072_2022-10-22_final
2022-10-27 10:19:56	ga_ls8c_ard_3-2-1_100077_2022-10-27_final
2023-01-15 10:19:37	ga_ls8c_ard_3-2-1_100077_2023-01-15_final
2023-02-09 10:09:52	ga_ls8c_ard_3-2-1_099068_2023-02-09_final
2023-11-18 09:12:20	ga_ls8c_ard_3-2-1_089079_2023-11-17_final
2023-11-21 09:40:28	ga_ls8c_ard_3-2-1_094072_2023-11-21_final
2024-01-18 10:17:25	ga_ls8c_ard_3-2-1_100072_2024-01-18_final
2024-02-22 09:12:10	ga_ls8c_ard_3-2-1_089079_2024-02-21_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