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
2013-11-29 09:22:42	ga_ls8c_ard_3-0-0_090086_2013-11-28_final
2014-06-12 11:25:47	ga_ls8c_ard_3-0-0_111074_2014-06-12_final
2014-09-18 09:33:46	ga_ls8c_ard_3-0-0_093071_2014-09-18_final
2014-10-25 11:29:41	ga_ls8c_ard_3-0-0_112067_2014-10-25_final
2015-02-07 09:52:18	ga_ls8c_ard_3-0-0_095087_2015-02-07_final
2015-02-21 11:35:28	ga_ls8c_ard_3-0-0_113067_2015-02-21_final
2015-06-25 10:27:12	ga_ls8c_ard_3-0-0_101083_2015-06-25_final
2015-12-02 10:25:38	ga_ls8c_ard_3-0-0_101077_2015-12-02_final
2015-12-25 10:33:00	ga_ls8c_ard_3-0-0_102080_2015-12-25_final
2016-01-15 09:14:12	ga_ls8c_ard_3-0-0_089084_2016-01-14_final
2016-04-11 10:52:24	ga_ls8c_ard_3-0-0_106068_2016-04-11_final
2016-10-12 10:04:51	ga_ls8c_ard_3-1-0_098071_2016-10-12_final
2016-10-22 10:40:47	ga_ls8c_ard_3-0-0_104068_2016-10-22_final
2016-11-08 11:24:25	ga_ls8c_ard_3-0-0_111069_2016-11-08_final
2016-11-13 10:10:04	ga_ls8c_ard_3-0-0_098084_2016-11-13_final
2017-02-01 10:03:47	ga_ls8c_ard_3-0-0_098069_2017-02-01_final
2017-04-10 11:19:25	ga_ls8c_ard_3-0-0_110074_2017-04-10_final
2017-06-04 09:44:02	ga_ls8c_ard_3-0-0_095067_2017-06-04_final
2017-07-28 09:14:51	ga_ls8c_ard_3-0-0_089086_2017-07-27_final
2018-02-22 09:51:57	ga_ls8c_ard_3-0-0_096071_2018-02-22_final
2018-04-10 10:48:22	ga_ls8c_ard_3-0-0_105074_2018-04-10_final
2018-04-29 11:19:05	ga_ls8c_ard_3-0-0_110074_2018-04-29_final
2018-05-09 10:18:47	ga_ls8c_ard_3-0-0_100078_2018-05-09_final
2018-07-31 09:09:24	ga_ls8c_ard_3-0-0_089074_2018-07-30_final
2018-09-01 10:48:57	ga_ls8c_ard_3-0-0_105075_2018-09-01_final
2018-10-09 11:52:12	ga_ls8c_ard_3-0-0_115078_2018-10-09_final
2018-12-13 09:22:33	ga_ls8c_ard_3-0-0_090090_2018-12-12_final
2019-04-18 09:34:05	ga_ls8c_ard_3-1-0_092089_2019-04-18_final
2019-04-20 09:17:19	ga_ls8c_ard_3-0-0_090078_2019-04-19_final
2019-05-20 09:33:52	ga_ls8c_ard_3-0-0_092088_2019-05-20_final
2019-06-16 10:48:50	ga_ls8c_ard_3-1-0_105074_2019-06-16_final
2020-03-05 09:16:38	ga_ls8c_ard_3-1-0_090075_2020-03-04_final
2020-05-27 11:23:57	ga_ls8c_ard_3-1-0_111070_2020-05-27_final
2020-09-18 11:17:11	ga_ls8c_ard_3-1-0_109082_2020-09-18_final
2021-02-13 09:11:24	ga_ls8c_ard_3-2-0_089077_2021-02-12_final
2021-06-22 11:29:20	ga_ls8c_ard_3-2-0_112067_2021-06-22_final
2021-07-12 11:09:27	ga_ls8c_ard_3-2-0_108079_2021-07-12_final
2021-08-14 10:13:16	ga_ls8c_ard_3-2-0_099077_2021-08-14_final
2021-12-30 10:47:16	ga_ls8c_ard_3-2-1_105069_2021-12-30_final
2022-03-02 11:03:46	ga_ls8c_ard_3-2-1_107080_2022-03-02_final
2022-05-26 11:19:50	ga_ls8c_ard_3-2-1_110074_2022-05-26_final
2022-05-31 09:57:56	ga_ls8c_ard_3-2-1_097070_2022-05-31_final
2022-06-22 09:21:54	ga_ls8c_ard_3-2-1_091072_2022-06-21_final
2022-08-13 10:40:21	ga_ls8c_ard_3-2-1_103082_2022-08-13_final
2022-08-30 11:20:02	ga_ls8c_ard_3-2-1_110073_2022-08-30_final
2022-11-27 09:40:11	ga_ls8c_ard_3-2-1_093086_2022-11-27_final
2022-11-29 11:02:19	ga_ls8c_ard_3-2-1_107075_2022-11-29_final
2023-04-01 10:43:24	ga_ls8c_ard_3-2-1_104076_2023-04-01_final
2023-05-26 10:45:55	ga_ls8c_ard_3-2-1_105068_2023-05-26_final
2023-05-27 11:31:35	ga_ls8c_ard_3-2-1_112074_2023-05-27_final
2023-06-19 09:58:14	ga_ls8c_ard_3-2-1_097072_2023-06-19_final
2023-08-01 11:20:09	ga_ls8c_ard_3-2-1_110075_2023-08-01_final
2023-08-20 10:08:42	ga_ls8c_ard_3-2-1_099066_2023-08-20_final
2023-09-29 09:28:59	ga_ls8c_ard_3-2-1_091090_2023-09-28_final
2023-11-23 11:08:12	ga_ls8c_ard_3-2-1_108075_2023-11-23_final
2024-01-28 10:55:36	ga_ls8c_ard_3-2-1_106075_2024-01-28_final
2024-01-31 11:25:44	ga_ls8c_ard_3-2-1_111073_2024-01-31_final
2024-03-12 11:19:45	ga_ls8c_ard_3-2-1_110074_2024-03-12_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