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

67 results

Time (local)	Label
2013-07-03 10:41:25	ga_ls8c_ard_3-0-0_103081_2013-07-03_final
2014-01-31 11:52:17	ga_ls8c_ard_3-0-0_115075_2014-01-31_final
2014-02-21 10:34:03	ga_ls8c_ard_3-0-0_102081_2014-02-21_final
2014-07-23 11:16:59	ga_ls8c_ard_3-0-0_110067_2014-07-23_final
2015-01-02 10:09:57	ga_ls8c_ard_3-0-0_099069_2015-01-02_final
2015-05-21 11:28:55	ga_ls8c_ard_3-0-0_112068_2015-05-21_final
2015-12-24 11:24:38	ga_ls8c_ard_3-0-0_111070_2015-12-24_final
2016-01-11 09:34:31	ga_ls8c_ard_3-0-0_093073_2016-01-11_final
2016-03-26 10:52:31	ga_ls8c_ard_3-0-0_106068_2016-03-26_final
2016-05-23 11:29:53	ga_ls8c_ard_3-0-0_112069_2016-05-23_final
2016-06-06 10:06:37	ga_ls8c_ard_3-0-0_098077_2016-06-06_final
2016-07-14 11:07:53	ga_ls8c_ard_3-0-0_108075_2016-07-14_final
2016-09-10 10:09:57	ga_ls8c_ard_3-0-0_098084_2016-09-10_final
2016-10-30 09:57:43	ga_ls8c_ard_3-0-0_096084_2016-10-30_final
2016-11-11 10:17:14	ga_ls8c_ard_3-0-0_100071_2016-11-11_final
2016-12-17 11:29:44	ga_ls8c_ard_3-0-0_112067_2016-12-17_final
2017-03-01 10:33:07	ga_ls8c_ard_3-0-0_102081_2017-03-01_final
2017-03-11 09:27:38	ga_ls8c_ard_3-0-0_092072_2017-03-10_final
2017-07-26 09:20:00	ga_ls8c_ard_3-0-0_091068_2017-07-25_final
2017-10-06 10:09:47	ga_ls8c_ard_3-0-0_099068_2017-10-06_final
2017-12-25 10:10:07	ga_ls8c_ard_3-0-0_099069_2017-12-25_final
2018-01-20 10:47:25	ga_ls8c_ard_3-0-0_105070_2018-01-20_final
2018-01-30 11:23:12	ga_ls8c_ard_3-0-0_111067_2018-01-30_final
2018-02-03 09:22:45	ga_ls8c_ard_3-0-0_091075_2018-02-02_final
2018-02-20 10:07:07	ga_ls8c_ard_3-0-0_098078_2018-02-20_final
2018-04-11 11:30:02	ga_ls8c_ard_3-0-0_112070_2018-04-11_final
2018-05-24 11:13:01	ga_ls8c_ard_3-1-0_109075_2018-05-24_final
2018-06-29 10:48:50	ga_ls8c_ard_3-0-0_105076_2018-06-29_final
2018-07-30 10:06:37	ga_ls8c_ard_3-0-0_098078_2018-07-30_final
2018-11-21 11:30:36	ga_ls8c_ard_3-0-0_112070_2018-11-21_final
2018-11-26 10:15:26	ga_ls8c_ard_3-0-0_099083_2018-11-26_final
2019-02-02 09:46:10	ga_ls8c_ard_3-0-0_095072_2019-02-02_final
2019-03-18 10:10:19	ga_ls8c_ard_3-1-0_099071_2019-03-18_final
2019-03-20 09:56:45	ga_ls8c_ard_3-1-0_097068_2019-03-20_final
2019-11-14 10:55:56	ga_ls8c_ard_3-1-0_106075_2019-11-14_final
2019-11-26 11:17:26	ga_ls8c_ard_3-1-0_110067_2019-11-26_final
2019-12-09 09:10:50	ga_ls8c_ard_3-1-0_089075_2019-12-08_final
2020-03-05 09:17:26	ga_ls8c_ard_3-1-0_090077_2020-03-04_final
2020-06-07 09:28:13	ga_ls8c_ard_3-1-0_092074_2020-06-06_final
2020-06-12 11:23:42	ga_ls8c_ard_3-1-0_111069_2020-06-12_final
2020-08-20 10:07:24	ga_ls8c_ard_3-1-0_098078_2020-08-20_final
2020-08-26 09:25:59	ga_ls8c_ard_3-1-0_092067_2020-08-25_final
2020-09-17 10:29:07	ga_ls8c_ard_3-1-0_102070_2020-09-17_final
2020-10-11 11:24:14	ga_ls8c_ard_3-1-0_110084_2020-10-11_final
2021-04-08 10:10:28	ga_ls8c_ard_3-2-0_099071_2021-04-08_final
2021-05-11 09:17:26	ga_ls8c_ard_3-2-0_090078_2021-05-10_final
2021-07-13 10:13:02	ga_ls8c_ard_3-2-0_099077_2021-07-13_final
2021-07-18 10:28:00	ga_ls8c_ard_3-2-0_102068_2021-07-18_final
2021-11-17 11:06:17	ga_ls8c_ard_3-2-0_108070_2021-11-17_final
2022-07-06 09:34:41	ga_ls8c_ard_3-2-1_093073_2022-07-06_final
2022-07-22 11:18:02	ga_ls8c_ard_3-2-1_109084_2022-07-22_final
2022-10-15 09:57:29	ga_ls8c_ard_3-2-1_096083_2022-10-15_final
2022-11-19 10:23:36	ga_ls8c_ard_3-2-1_101071_2022-11-19_final
2022-11-27 09:39:47	ga_ls8c_ard_3-2-1_093085_2022-11-27_final
2023-01-23 09:34:36	ga_ls8c_ard_3-2-1_092088_2023-01-23_final
2023-02-02 10:04:32	ga_ls8c_ard_3-2-1_098070_2023-02-02_final
2023-03-07 09:12:07	ga_ls8c_ard_3-2-1_089079_2023-03-06_final
2023-04-14 10:09:53	ga_ls8c_ard_3-2-1_099070_2023-04-14_final
2023-04-15 10:52:44	ga_ls8c_ard_3-2-1_106069_2023-04-15_final
2023-05-10 09:11:27	ga_ls8c_ard_3-2-1_089079_2023-05-09_final
2023-06-25 09:27:11	ga_ls8c_ard_3-2-1_091087_2023-06-24_final
2023-08-18 10:27:26	ga_ls8c_ard_3-2-1_101082_2023-08-18_final
2023-08-31 09:58:10	ga_ls8c_ard_3-2-1_096086_2023-08-31_final
2023-12-27 09:18:05	ga_ls8c_ard_3-2-1_090078_2023-12-26_final
2023-12-30 11:24:15	ga_ls8c_ard_3-2-1_111069_2023-12-30_final
2024-02-19 10:17:22	ga_ls8c_ard_3-2-1_100072_2024-02-19_final
2024-02-23 11:31:31	ga_ls8c_ard_3-2-1_112072_2024-02-23_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