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
2013-03-31 09:31:51	ga_ls8c_ard_3-0-0_092074_2013-03-31_final
2014-01-31 11:53:53	ga_ls8c_ard_3-0-0_115079_2014-01-31_final
2014-06-28 09:44:08	ga_ls8c_ard_3-0-0_095067_2014-06-28_final
2014-08-02 10:19:41	ga_ls8c_ard_3-0-0_100078_2014-08-02_final
2015-02-07 09:44:19	ga_ls8c_ard_3-0-0_095067_2015-02-07_final
2015-07-21 09:28:27	ga_ls8c_ard_3-0-0_091090_2015-07-20_final
2015-09-25 09:10:31	ga_ls8c_ard_3-0-0_089075_2015-09-24_final
2015-11-06 09:44:31	ga_ls8c_ard_3-0-0_095067_2015-11-06_final
2016-02-17 11:30:35	ga_ls8c_ard_3-0-0_112070_2016-02-17_final
2016-03-18 10:04:21	ga_ls8c_ard_3-1-0_098071_2016-03-18_final
2016-09-08 10:19:55	ga_ls8c_ard_3-0-0_100078_2016-09-08_final
2016-10-18 09:28:12	ga_ls8c_ard_3-0-0_092072_2016-10-17_final
2016-12-31 10:09:58	ga_ls8c_ard_3-0-0_098084_2016-12-31_final
2017-01-02 11:31:41	ga_ls8c_ard_3-0-0_112072_2017-01-02_final
2017-05-03 09:43:41	ga_ls8c_ard_3-0-0_095067_2017-05-03_final
2018-01-14 09:44:28	ga_ls8c_ard_3-0-0_095067_2018-01-14_final
2018-02-15 09:44:13	ga_ls8c_ard_3-0-0_095067_2018-02-15_final
2018-04-16 10:12:25	ga_ls8c_ard_3-0-0_099077_2018-04-16_final
2018-05-29 11:30:18	ga_ls8c_ard_3-0-0_112072_2018-05-29_final
2018-07-25 09:43:38	ga_ls8c_ard_3-0-0_095067_2018-07-25_final
2018-11-03 10:02:28	ga_ls8c_ard_3-2-1_098066_2018-11-03_final
2018-11-21 09:50:31	ga_ls8c_ard_3-0-0_096067_2018-11-21_final
2018-12-05 11:41:44	ga_ls8c_ard_3-0-0_114067_2018-12-05_final
2019-03-18 10:10:19	ga_ls8c_ard_3-1-0_099071_2019-03-18_final
2019-03-27 10:04:06	ga_ls8c_ard_3-1-0_098071_2019-03-27_final
2019-06-21 09:34:30	ga_ls8c_ard_3-1-0_092089_2019-06-21_final
2019-07-14 11:14:28	ga_ls8c_ard_3-1-0_109076_2019-07-14_final
2019-07-24 10:09:55	ga_ls8c_ard_3-1-0_099069_2019-07-24_final
2019-10-23 09:51:47	ga_ls8c_ard_3-1-0_096069_2019-10-23_final
2019-11-06 10:02:56	ga_ls8c_ard_3-2-1_098066_2019-11-06_final
2020-02-02 09:17:11	ga_ls8c_ard_3-1-0_090076_2020-02-01_final
2020-06-07 11:07:30	ga_ls8c_ard_3-1-0_108075_2020-06-07_final
2020-08-27 10:13:14	ga_ls8c_ard_3-1-0_099077_2020-08-27_final
2020-12-26 11:42:09	ga_ls8c_ard_3-2-0_114067_2020-12-26_final
2021-04-08 10:12:51	ga_ls8c_ard_3-2-0_099077_2021-04-08_final
2021-04-12 09:44:07	ga_ls8c_ard_3-2-0_095067_2021-04-12_final
2021-09-05 09:39:53	ga_ls8c_ard_3-2-0_093086_2021-09-05_final
2021-11-02 11:53:13	ga_ls8c_ard_3-2-0_115079_2021-11-02_final
2021-11-26 09:20:26	ga_ls8c_ard_3-2-0_091068_2021-11-25_final
2021-12-09 10:33:37	ga_ls8c_ard_3-2-1_102081_2021-12-09_final
2021-12-10 09:34:24	ga_ls8c_ard_3-2-1_093072_2021-12-10_final
2022-01-20 09:28:03	ga_ls8c_ard_3-2-1_092072_2022-01-19_final
2022-02-10 11:24:12	ga_ls8c_ard_3-2-1_111069_2022-02-10_final
2022-05-07 10:49:40	ga_ls8c_ard_3-2-1_105076_2022-05-07_final
2022-07-04 11:24:20	ga_ls8c_ard_3-2-1_111069_2022-07-04_final
2022-10-09 10:33:49	ga_ls8c_ard_3-2-1_102081_2022-10-09_final
2022-11-11 09:39:26	ga_ls8c_ard_3-2-1_093084_2022-11-11_final
2022-11-15 09:11:52	ga_ls8c_ard_3-2-1_089077_2022-11-14_final
2022-12-14 10:17:24	ga_ls8c_ard_3-2-1_100071_2022-12-14_final
2023-01-12 09:47:10	ga_ls8c_ard_3-2-1_095073_2023-01-12_final
2023-02-09 10:13:52	ga_ls8c_ard_3-2-1_099078_2023-02-09_final
2023-03-08 11:31:27	ga_ls8c_ard_3-2-1_112072_2023-03-08_final
2023-10-04 09:40:21	ga_ls8c_ard_3-2-1_094072_2023-10-04_final
2023-10-18 09:53:08	ga_ls8c_ard_3-2-1_096073_2023-10-18_final
2023-12-25 09:28:52	ga_ls8c_ard_3-2-1_092074_2023-12-24_final
2024-02-17 10:28:08	ga_ls8c_ard_3-2-1_102068_2024-02-17_final
2024-02-21 10:03:48	ga_ls8c_ard_3-2-1_098069_2024-02-21_final
2024-03-15 10:10:33	ga_ls8c_ard_3-2-1_099071_2024-03-15_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