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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

63 results

Time (local)	Label
2013-05-22 09:59:12	ga_ls8c_ard_3-0-0_097068_2013-05-22_final
2013-12-31 09:18:30	ga_ls8c_ard_3-0-0_090076_2013-12-30_final
2015-04-06 10:25:15	ga_ls8c_ard_3-0-0_101078_2015-04-06_final
2015-05-29 10:45:05	ga_ls8c_ard_3-0-0_104082_2015-05-29_final
2015-10-07 09:34:04	ga_ls8c_ard_3-0-0_093072_2015-10-07_final
2015-10-28 09:50:41	ga_ls8c_ard_3-0-0_096067_2015-10-28_final
2015-11-08 11:17:02	ga_ls8c_ard_3-0-0_109082_2015-11-08_final
2015-12-12 09:20:12	ga_ls8c_ard_3-0-0_091068_2015-12-11_final
2015-12-24 09:46:56	ga_ls8c_ard_3-0-0_095073_2015-12-24_final
2016-01-31 10:52:15	ga_ls8c_ard_3-0-0_105082_2016-01-31_final
2016-03-11 09:57:50	ga_ls8c_ard_3-1-0_097070_2016-03-11_final
2016-06-13 10:10:25	ga_ls8c_ard_3-0-0_099071_2016-06-13_final
2016-06-17 11:25:23	ga_ls8c_ard_3-0-0_111073_2016-06-17_final
2016-10-23 09:44:45	ga_ls8c_ard_3-0-0_095067_2016-10-23_final
2016-11-03 09:29:00	ga_ls8c_ard_3-0-0_092074_2016-11-02_final
2016-11-10 09:34:22	ga_ls8c_ard_3-0-0_093072_2016-11-10_final
2017-02-12 09:45:33	ga_ls8c_ard_3-0-0_095070_2017-02-12_final
2017-04-08 09:50:07	ga_ls8c_ard_3-0-0_096067_2017-04-08_final
2017-04-14 09:16:34	ga_ls8c_ard_3-0-0_090076_2017-04-13_final
2017-04-22 10:09:31	ga_ls8c_ard_3-0-0_098085_2017-04-22_final
2017-05-25 10:50:08	ga_ls8c_ard_3-0-0_105078_2017-05-25_final
2017-08-16 11:22:45	ga_ls8c_ard_3-0-0_110081_2017-08-16_final
2017-09-24 11:29:52	ga_ls8c_ard_3-0-0_111083_2017-09-24_final
2018-08-26 11:24:00	ga_ls8c_ard_3-0-0_111070_2018-08-26_final
2018-09-01 10:51:45	ga_ls8c_ard_3-0-0_105082_2018-09-01_final
2019-01-11 10:27:20	ga_ls8c_ard_3-0-0_101082_2019-01-11_final
2019-01-23 09:10:19	ga_ls8c_ard_3-0-0_089075_2019-01-22_final
2019-03-18 10:13:06	ga_ls8c_ard_3-1-0_099078_2019-03-18_final
2019-05-27 11:13:25	ga_ls8c_ard_3-0-0_109074_2019-05-27_final
2019-11-30 10:52:43	ga_ls8c_ard_3-1-0_106067_2019-11-30_final
2019-12-29 10:26:07	ga_ls8c_ard_3-1-0_101078_2019-12-29_final
2020-03-19 11:07:46	ga_ls8c_ard_3-1-0_108075_2020-03-19_final
2020-04-10 10:32:53	ga_ls8c_ard_3-1-0_102081_2020-04-10_final
2020-06-14 11:13:22	ga_ls8c_ard_3-1-0_109074_2020-06-14_final
2020-07-11 09:20:08	ga_ls8c_ard_3-1-0_090084_2020-07-10_final
2020-09-18 11:17:35	ga_ls8c_ard_3-1-0_109083_2020-09-18_final
2020-09-23 09:51:40	ga_ls8c_ard_3-1-0_096069_2020-09-23_final
2020-11-17 11:42:20	ga_ls8c_ard_3-1-0_113083_2020-11-17_final
2020-12-18 10:54:20	ga_ls8c_ard_3-2-0_106071_2020-12-18_final
2021-03-15 09:19:56	ga_ls8c_ard_3-2-0_091068_2021-03-14_final
2021-07-21 11:05:19	ga_ls8c_ard_3-2-0_107084_2021-07-21_final
2021-12-19 09:28:59	ga_ls8c_ard_3-2-1_092074_2021-12-18_final
2022-01-04 09:28:54	ga_ls8c_ard_3-2-1_092074_2022-01-03_final
2022-01-15 09:10:44	ga_ls8c_ard_3-2-1_089075_2022-01-14_final
2022-02-23 09:20:43	ga_ls8c_ard_3-2-1_090085_2022-02-22_final
2022-03-02 09:22:54	ga_ls8c_ard_3-2-1_091075_2022-03-01_final
2022-04-20 10:02:22	ga_ls8c_ard_3-2-1_098066_2022-04-20_final
2022-05-03 11:14:20	ga_ls8c_ard_3-2-1_109076_2022-05-03_final
2022-07-02 11:37:54	ga_ls8c_ard_3-2-1_113072_2022-07-02_final
2022-08-10 10:07:26	ga_ls8c_ard_3-2-1_098077_2022-08-10_final
2022-09-09 10:19:53	ga_ls8c_ard_3-2-1_100077_2022-09-09_final
2022-10-10 11:14:16	ga_ls8c_ard_3-2-1_109074_2022-10-10_final
2022-11-25 11:25:50	ga_ls8c_ard_3-2-1_111072_2022-11-25_final
2023-01-21 09:40:09	ga_ls8c_ard_3-2-1_094071_2023-01-21_final
2023-01-23 09:29:00	ga_ls8c_ard_3-2-1_092074_2023-01-22_final
2023-02-09 10:10:40	ga_ls8c_ard_3-2-1_099070_2023-02-09_final
2023-02-09 10:13:52	ga_ls8c_ard_3-2-1_099078_2023-02-09_final
2023-02-19 09:16:18	ga_ls8c_ard_3-2-1_089089_2023-02-18_final
2023-03-05 09:21:43	ga_ls8c_ard_3-2-1_091072_2023-03-04_final
2023-04-02 11:23:51	ga_ls8c_ard_3-2-1_111069_2023-04-02_final
2023-05-10 09:11:27	ga_ls8c_ard_3-2-1_089079_2023-05-09_final
2023-10-20 09:39:58	ga_ls8c_ard_3-2-1_094071_2023-10-20_final
2024-02-28 10:12:19	ga_ls8c_ard_3-2-1_099075_2024-02-28_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