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

58 results

Time (local)	Label
2013-06-13 09:25:16	ga_ls8c_ard_3-0-0_091076_2013-06-12_final
2013-07-07 10:15:54	ga_ls8c_ard_3-0-0_099079_2013-07-07_final
2013-10-01 09:40:43	ga_ls8c_ard_3-0-0_093084_2013-10-01_final
2013-10-13 10:03:02	ga_ls8c_ard_3-0-0_097078_2013-10-13_final
2013-12-29 09:29:41	ga_ls8c_ard_3-0-0_092073_2013-12-28_final
2014-06-12 09:50:29	ga_ls8c_ard_3-0-0_095083_2014-06-12_final
2014-07-19 10:03:13	ga_ls8c_ard_3-0-0_098068_2014-07-19_final
2015-04-06 10:26:51	ga_ls8c_ard_3-0-0_101082_2015-04-06_final
2015-05-30 09:45:05	ga_ls8c_ard_3-0-0_095071_2015-05-30_final
2015-06-06 09:50:35	ga_ls8c_ard_3-0-0_096069_2015-06-06_final
2015-09-08 10:09:36	ga_ls8c_ard_3-0-0_098084_2015-09-08_final
2015-12-15 09:51:31	ga_ls8c_ard_3-0-0_096069_2015-12-15_final
2016-01-04 09:28:45	ga_ls8c_ard_3-0-0_092074_2016-01-03_final
2016-01-14 11:41:55	ga_ls8c_ard_3-0-0_114067_2016-01-14_final
2016-06-14 10:57:16	ga_ls8c_ard_3-0-0_106080_2016-06-14_final
2016-07-23 11:03:45	ga_ls8c_ard_3-0-0_107080_2016-07-23_final
2016-09-27 09:15:08	ga_ls8c_ard_3-0-0_089086_2016-09-26_final
2017-05-29 10:22:40	ga_ls8c_ard_3-0-0_101071_2017-05-29_final
2017-10-07 10:55:27	ga_ls8c_ard_3-0-0_106074_2017-10-07_final
2017-12-17 09:21:52	ga_ls8c_ard_3-0-0_091072_2017-12-16_final
2018-04-20 11:23:21	ga_ls8c_ard_3-0-0_111069_2018-04-20_final
2018-05-03 10:55:08	ga_ls8c_ard_3-0-0_106076_2018-05-03_final
2018-05-06 09:45:31	ga_ls8c_ard_3-0-0_095072_2018-05-06_final
2018-05-15 09:45:14	ga_ls8c_ard_3-0-0_094087_2018-05-15_final
2018-06-09 09:36:27	ga_ls8c_ard_3-0-0_093081_2018-06-09_final
2018-07-18 09:39:01	ga_ls8c_ard_3-0-0_094071_2018-07-18_final
2018-09-01 09:09:40	ga_ls8c_ard_3-0-0_089074_2018-08-31_final
2018-09-11 09:45:37	ga_ls8c_ard_3-0-0_095071_2018-09-11_final
2018-09-24 10:55:15	ga_ls8c_ard_3-0-0_106075_2018-09-24_final
2018-10-04 09:50:21	ga_ls8c_ard_3-0-0_096067_2018-10-04_final
2019-02-18 11:23:49	ga_ls8c_ard_3-0-0_111069_2019-02-18_final
2019-03-05 09:06:48	ga_ls8c_ard_3-0-0_088082_2019-03-04_final
2019-05-04 11:06:59	ga_ls8c_ard_3-1-0_108074_2019-05-04_final
2019-06-23 10:55:27	ga_ls8c_ard_3-1-0_106075_2019-06-23_final
2019-08-10 09:16:48	ga_ls8c_ard_3-1-0_090075_2019-08-09_final
2019-10-05 11:46:59	ga_ls8c_ard_3-1-0_114079_2019-10-05_final
2020-05-17 09:10:44	ga_ls8c_ard_3-1-0_089077_2020-05-16_final
2020-07-27 10:55:31	ga_ls8c_ard_3-1-0_106075_2020-07-27_final
2020-08-27 11:51:19	ga_ls8c_ard_3-1-0_115075_2020-08-27_final
2020-09-02 09:33:48	ga_ls8c_ard_3-1-0_093071_2020-09-02_final
2021-03-27 11:23:53	ga_ls8c_ard_3-2-0_111069_2021-03-27_final
2021-07-23 10:49:47	ga_ls8c_ard_3-2-0_105076_2021-07-23_final
2021-09-26 11:29:48	ga_ls8c_ard_3-2-0_112067_2021-09-26_final
2021-12-25 10:30:21	ga_ls8c_ard_3-2-1_102073_2021-12-25_final
2022-03-16 09:33:34	ga_ls8c_ard_3-2-1_093071_2022-03-16_final
2022-04-21 10:52:01	ga_ls8c_ard_3-2-1_105082_2022-04-21_final
2022-05-08 09:52:03	ga_ls8c_ard_3-2-1_096071_2022-05-08_final
2022-05-19 09:34:23	ga_ls8c_ard_3-2-1_093073_2022-05-19_final
2022-06-24 10:50:02	ga_ls8c_ard_3-2-1_105076_2022-06-24_final
2022-07-17 09:22:07	ga_ls8c_ard_3-2-1_090088_2022-07-16_final
2022-09-17 09:33:41	ga_ls8c_ard_3-2-1_092085_2022-09-17_final
2022-10-19 09:32:49	ga_ls8c_ard_3-2-1_092083_2022-10-19_final
2023-04-25 11:30:59	ga_ls8c_ard_3-2-1_112072_2023-04-25_final
2023-06-05 11:28:38	ga_ls8c_ard_3-2-1_111082_2023-06-05_final
2023-06-27 09:14:27	ga_ls8c_ard_3-2-1_089086_2023-06-26_final
2023-12-20 09:16:20	ga_ls8c_ard_3-2-1_089089_2023-12-19_final
2024-01-23 10:35:54	ga_ls8c_ard_3-2-1_103072_2024-01-23_final
2024-04-01 09:16:42	ga_ls8c_ard_3-2-1_090076_2024-03-31_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