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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

60 results

Time (local)	Label
2013-08-07 09:35:28	ga_ls8c_ard_3-0-0_092086_2013-08-07_final
2013-12-23 10:11:11	ga_ls8c_ard_3-0-0_098084_2013-12-23_final
2014-03-07 09:07:42	ga_ls8c_ard_3-0-0_088082_2014-03-06_final
2015-01-22 11:24:27	ga_ls8c_ard_3-0-0_111070_2015-01-22_final
2015-03-13 11:11:20	ga_ls8c_ard_3-0-0_109069_2015-03-13_final
2015-08-09 11:31:07	ga_ls8c_ard_3-0-0_112072_2015-08-09_final
2015-09-03 09:44:13	ga_ls8c_ard_3-0-0_095067_2015-09-03_final
2016-01-09 09:44:28	ga_ls8c_ard_3-0-0_095067_2016-01-09_final
2016-07-28 09:38:14	ga_ls8c_ard_3-0-0_094067_2016-07-28_final
2016-08-06 09:34:04	ga_ls8c_ard_3-0-0_093072_2016-08-06_final
2016-12-10 11:24:47	ga_ls8c_ard_3-0-0_111070_2016-12-10_final
2017-02-20 10:35:46	ga_ls8c_ard_3-0-0_103072_2017-02-20_final
2017-03-11 09:25:38	ga_ls8c_ard_3-0-0_092067_2017-03-10_final
2017-05-30 09:33:50	ga_ls8c_ard_3-0-0_092088_2017-05-30_final
2018-01-14 11:25:45	ga_ls8c_ard_3-0-0_111073_2018-01-14_final
2018-03-07 09:24:55	ga_ls8c_ard_3-0-0_091081_2018-03-06_final
2018-06-30 11:30:31	ga_ls8c_ard_3-0-0_112072_2018-06-30_final
2018-07-05 10:12:12	ga_ls8c_ard_3-0-0_099077_2018-07-05_final
2018-07-29 09:26:32	ga_ls8c_ard_3-0-0_091086_2018-07-28_final
2018-10-19 09:11:59	ga_ls8c_ard_3-0-0_089079_2018-10-18_final
2018-12-04 09:21:35	ga_ls8c_ard_3-0-0_091072_2018-12-03_final
2019-01-01 09:45:53	ga_ls8c_ard_3-0-0_095071_2019-01-01_final
2019-02-11 11:18:04	ga_ls8c_ard_3-0-0_110070_2019-02-11_final
2019-02-15 10:52:32	ga_ls8c_ard_3-0-0_106068_2019-02-15_final
2019-02-15 10:55:19	ga_ls8c_ard_3-0-0_106075_2019-02-15_final
2019-03-06 11:25:20	ga_ls8c_ard_3-0-0_111073_2019-03-06_final
2019-03-29 11:30:13	ga_ls8c_ard_3-1-0_112070_2019-03-29_final
2019-08-22 09:39:59	ga_ls8c_ard_3-1-0_094071_2019-08-22_final
2019-10-03 10:20:04	ga_ls8c_ard_3-1-0_100078_2019-10-03_final
2019-10-29 09:17:30	ga_ls8c_ard_3-1-0_090076_2019-10-28_final
2020-03-25 10:28:14	ga_ls8c_ard_3-1-0_102069_2020-03-25_final
2020-06-19 09:51:04	ga_ls8c_ard_3-1-0_096069_2020-06-19_final
2020-09-27 09:28:10	ga_ls8c_ard_3-1-0_092072_2020-09-26_final
2021-05-21 09:50:14	ga_ls8c_ard_3-2-0_096067_2021-05-21_final
2021-07-12 09:34:09	ga_ls8c_ard_3-2-0_092088_2021-07-12_final
2021-09-02 10:40:40	ga_ls8c_ard_3-2-0_104068_2021-09-02_final
2021-10-13 10:34:40	ga_ls8c_ard_3-2-0_103068_2021-10-13_final
2021-11-25 10:17:39	ga_ls8c_ard_3-2-0_100072_2021-11-25_final
2022-01-06 10:54:14	ga_ls8c_ard_3-2-1_106071_2022-01-06_final
2022-01-24 10:41:48	ga_ls8c_ard_3-2-1_104071_2022-01-24_final
2022-03-25 09:28:28	ga_ls8c_ard_3-2-1_092074_2022-03-24_final
2022-07-24 09:22:25	ga_ls8c_ard_3-2-1_091073_2022-07-23_final
2022-08-14 09:40:44	ga_ls8c_ard_3-2-1_094072_2022-08-14_final
2022-12-06 09:29:13	ga_ls8c_ard_3-2-1_092074_2022-12-05_final
2022-12-27 11:24:06	ga_ls8c_ard_3-2-1_111068_2022-12-27_final
2023-01-21 09:40:09	ga_ls8c_ard_3-2-1_094071_2023-01-21_final
2023-02-25 10:13:34	ga_ls8c_ard_3-2-1_099078_2023-02-25_final
2023-05-10 10:49:08	ga_ls8c_ard_3-2-1_105076_2023-05-10_final
2023-05-22 09:33:44	ga_ls8c_ard_3-2-1_093073_2023-05-22_final
2023-09-15 10:49:04	ga_ls8c_ard_3-2-1_105074_2023-09-15_final
2023-09-18 09:40:18	ga_ls8c_ard_3-2-1_094072_2023-09-18_final
2023-09-25 09:46:06	ga_ls8c_ard_3-2-1_095071_2023-09-25_final
2023-09-25 11:24:11	ga_ls8c_ard_3-2-1_111069_2023-09-25_final
2023-09-29 09:22:36	ga_ls8c_ard_3-2-1_091074_2023-09-28_final
2023-11-05 09:40:25	ga_ls8c_ard_3-2-1_094072_2023-11-05_final
2023-11-25 09:16:57	ga_ls8c_ard_3-2-1_090075_2023-11-24_final
2023-12-26 10:14:07	ga_ls8c_ard_3-2-1_099079_2023-12-26_final
2024-02-20 09:22:09	ga_ls8c_ard_3-2-1_091073_2024-02-19_final
2024-03-09 09:09:59	ga_ls8c_ard_3-2-1_089074_2024-03-08_final
2024-04-07 10:19:18	ga_ls8c_ard_3-2-1_100078_2024-04-07_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