Search ga_ls8c_ard_3 whole collection

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

57 results

Time (local)	Label
2013-06-18 09:40:10	ga_ls8c_ard_3-0-0_094067_2013-06-18_final
2014-03-05 09:17:40	ga_ls8c_ard_3-0-0_090076_2014-03-04_final
2014-03-31 11:30:54	ga_ls8c_ard_3-0-0_112070_2014-03-31_final
2014-04-25 09:46:15	ga_ls8c_ard_3-0-0_095072_2014-04-25_final
2014-05-27 11:22:50	ga_ls8c_ard_3-0-0_111067_2014-05-27_final
2014-08-26 09:28:44	ga_ls8c_ard_3-0-0_092074_2014-08-25_final
2015-12-27 10:19:26	ga_ls8c_ard_3-0-0_100077_2015-12-27_final
2016-06-23 10:49:34	ga_ls8c_ard_3-0-0_105076_2016-06-23_final
2016-11-15 11:31:00	ga_ls8c_ard_3-0-0_112070_2016-11-15_final
2016-11-19 09:28:12	ga_ls8c_ard_3-0-0_092072_2016-11-18_final
2017-01-24 09:17:12	ga_ls8c_ard_3-0-0_090076_2017-01-23_final
2017-05-14 09:28:05	ga_ls8c_ard_3-0-0_092074_2017-05-13_final
2017-10-05 09:28:07	ga_ls8c_ard_3-0-0_092072_2017-10-04_final
2017-12-18 10:02:44	ga_ls8c_ard_3-2-1_098066_2017-12-18_final
2018-01-07 09:38:21	ga_ls8c_ard_3-0-0_094067_2018-01-07_final
2018-03-03 11:24:11	ga_ls8c_ard_3-0-0_111070_2018-03-03_final
2018-04-15 09:27:59	ga_ls8c_ard_3-0-0_092074_2018-04-14_final
2018-05-17 09:27:39	ga_ls8c_ard_3-0-0_092074_2018-05-16_final
2018-07-02 09:37:17	ga_ls8c_ard_3-0-0_094067_2018-07-02_final
2018-09-13 09:33:15	ga_ls8c_ard_3-0-0_093071_2018-09-13_final
2018-10-26 09:16:59	ga_ls8c_ard_3-0-0_090076_2018-10-25_final
2018-11-03 11:47:20	ga_ls8c_ard_3-0-0_114081_2018-11-03_final
2018-11-23 09:40:09	ga_ls8c_ard_3-0-0_094072_2018-11-23_final
2018-12-25 11:17:47	ga_ls8c_ard_3-0-0_110069_2018-12-25_final
2019-01-08 11:30:08	ga_ls8c_ard_3-0-0_112069_2019-01-08_final
2019-04-12 11:41:19	ga_ls8c_ard_3-1-0_114067_2019-04-12_final
2019-12-02 10:46:20	ga_ls8c_ard_3-1-0_104082_2019-12-02_final
2019-12-19 09:45:53	ga_ls8c_ard_3-2-0_095070_2019-12-19_final
2020-06-05 09:37:46	ga_ls8c_ard_3-1-0_094067_2020-06-05_final
2020-07-25 09:27:47	ga_ls8c_ard_3-1-0_092072_2020-07-24_final
2020-07-25 09:28:35	ga_ls8c_ard_3-1-0_092074_2020-07-24_final
2020-09-18 09:32:42	ga_ls8c_ard_3-1-0_093068_2020-09-18_final
2020-12-01 10:10:17	ga_ls8c_ard_3-1-0_099069_2020-12-01_final
2021-07-11 10:22:36	ga_ls8c_ard_3-2-0_101070_2021-07-11_final
2021-09-19 11:29:58	ga_ls8c_ard_3-2-0_111083_2021-09-19_final
2022-01-13 09:21:55	ga_ls8c_ard_3-2-1_091072_2022-01-12_final
2022-01-13 09:22:19	ga_ls8c_ard_3-2-1_091073_2022-01-12_final
2022-01-14 10:03:58	ga_ls8c_ard_3-2-1_098069_2022-01-14_final
2022-01-15 10:48:02	ga_ls8c_ard_3-2-1_105071_2022-01-15_final
2022-02-28 11:14:09	ga_ls8c_ard_3-2-1_109075_2022-02-28_final
2022-05-19 09:34:23	ga_ls8c_ard_3-2-1_093073_2022-05-19_final
2022-07-08 09:22:19	ga_ls8c_ard_3-2-1_091073_2022-07-07_final
2022-07-31 09:29:04	ga_ls8c_ard_3-2-1_092074_2022-07-30_final
2022-09-26 09:22:20	ga_ls8c_ard_3-2-1_091072_2022-09-25_final
2022-12-04 09:40:47	ga_ls8c_ard_3-2-1_094072_2022-12-04_final
2023-01-12 11:24:27	ga_ls8c_ard_3-2-1_111069_2023-01-12_final
2023-02-17 09:21:55	ga_ls8c_ard_3-2-1_091072_2023-02-16_final
2023-08-19 09:28:37	ga_ls8c_ard_3-2-1_092074_2023-08-18_final
2023-08-27 11:57:47	ga_ls8c_ard_3-2-1_116076_2023-08-27_final
2023-10-03 10:39:34	ga_ls8c_ard_3-2-1_103081_2023-10-03_final
2023-10-15 09:21:51	ga_ls8c_ard_3-2-1_091072_2023-10-14_final
2023-10-29 09:34:39	ga_ls8c_ard_3-2-1_093073_2023-10-29_final
2023-11-25 09:22:08	ga_ls8c_ard_3-2-1_090088_2023-11-24_final
2023-12-02 09:22:16	ga_ls8c_ard_3-2-1_091073_2023-12-01_final
2023-12-14 11:24:40	ga_ls8c_ard_3-2-1_111070_2023-12-14_final
2024-03-12 09:39:40	ga_ls8c_ard_3-2-1_094071_2024-03-12_final
2024-04-10 10:52:11	ga_ls8c_ard_3-2-1_105083_2024-04-10_nrt

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