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
2013-06-25 09:53:55	ga_ls8c_ard_3-0-0_095086_2013-06-25_final
2014-01-24 10:10:52	ga_ls8c_ard_3-0-0_098084_2014-01-24_final
2014-04-12 10:19:21	ga_ls8c_ard_3-0-0_100077_2014-04-12_final
2014-10-08 09:10:43	ga_ls8c_ard_3-0-0_089075_2014-10-07_final
2014-10-14 10:11:45	ga_ls8c_ard_3-0-0_099073_2014-10-14_final
2015-01-08 09:33:42	ga_ls8c_ard_3-0-0_093071_2015-01-08_final
2015-02-10 10:19:10	ga_ls8c_ard_3-0-0_100077_2015-02-10_final
2015-03-23 10:09:52	ga_ls8c_ard_3-0-0_099070_2015-03-23_final
2015-10-21 11:24:33	ga_ls8c_ard_3-0-0_111070_2015-10-21_final
2015-11-11 10:07:26	ga_ls8c_ard_3-0-0_098078_2015-11-11_final
2016-02-21 09:28:33	ga_ls8c_ard_3-0-0_092074_2016-02-20_final
2016-03-17 09:25:29	ga_ls8c_ard_3-0-0_091082_2016-03-16_final
2016-03-25 10:10:04	ga_ls8c_ard_3-0-0_099070_2016-03-25_final
2016-04-13 10:45:13	ga_ls8c_ard_3-0-0_104081_2016-04-13_final
2017-03-04 09:25:30	ga_ls8c_ard_3-0-0_091082_2017-03-03_final
2017-09-08 11:24:12	ga_ls8c_ard_3-0-0_111069_2017-09-08_final
2017-09-10 09:33:45	ga_ls8c_ard_3-0-0_093071_2017-09-10_final
2017-11-11 09:46:40	ga_ls8c_ard_3-0-0_095072_2017-11-11_final
2017-11-17 09:16:21	ga_ls8c_ard_3-0-0_089089_2017-11-16_final
2018-01-21 11:29:28	ga_ls8c_ard_3-0-0_112067_2018-01-21_final
2018-04-16 10:09:14	ga_ls8c_ard_3-0-0_099069_2018-04-16_final
2018-05-06 09:45:31	ga_ls8c_ard_3-0-0_095072_2018-05-06_final
2018-05-28 09:11:45	ga_ls8c_ard_3-0-0_089081_2018-05-27_final
2018-07-01 10:38:29	ga_ls8c_ard_3-0-0_103081_2018-07-01_final
2018-10-02 10:09:53	ga_ls8c_ard_3-0-0_098085_2018-10-02_final
2019-04-19 10:13:21	ga_ls8c_ard_3-1-0_099079_2019-04-19_final
2019-07-03 11:31:23	ga_ls8c_ard_3-1-0_112072_2019-07-03_final
2019-07-26 10:01:34	ga_ls8c_ard_3-1-0_097079_2019-07-26_final
2020-01-20 11:24:15	ga_ls8c_ard_3-1-0_111069_2020-01-20_final
2020-07-21 09:55:17	ga_ls8c_ard_3-1-0_096079_2020-07-21_final
2020-07-25 09:27:47	ga_ls8c_ard_3-1-0_092072_2020-07-24_final
2020-08-04 11:41:47	ga_ls8c_ard_3-1-0_114067_2020-08-04_final
2020-08-10 11:08:43	ga_ls8c_ard_3-1-0_108077_2020-08-10_final
2020-12-14 11:17:28	ga_ls8c_ard_3-1-0_110067_2020-12-14_final
2021-09-03 09:46:38	ga_ls8c_ard_3-2-0_095072_2021-09-03_final
2022-01-15 09:11:56	ga_ls8c_ard_3-2-1_089078_2022-01-14_final
2022-02-03 11:20:26	ga_ls8c_ard_3-2-1_110075_2022-02-03_final
2022-02-12 09:34:32	ga_ls8c_ard_3-2-1_093073_2022-02-12_final
2022-02-16 09:12:11	ga_ls8c_ard_3-2-1_089079_2022-02-15_final
2022-03-04 09:13:43	ga_ls8c_ard_3-2-1_089083_2022-03-03_final
2022-05-05 09:26:19	ga_ls8c_ard_3-2-1_091084_2022-05-04_final
2022-05-30 09:16:39	ga_ls8c_ard_3-2-1_090075_2022-05-29_final
2022-06-20 09:34:39	ga_ls8c_ard_3-2-1_093073_2022-06-20_final
2022-09-24 09:41:05	ga_ls8c_ard_3-2-1_093088_2022-09-24_final
2022-09-25 10:20:21	ga_ls8c_ard_3-2-1_100078_2022-09-25_final
2022-10-24 11:25:06	ga_ls8c_ard_3-2-1_111070_2022-10-24_final
2022-11-06 09:22:31	ga_ls8c_ard_3-2-1_090088_2022-11-05_final
2022-11-20 09:28:23	ga_ls8c_ard_3-2-1_092072_2022-11-19_final
2022-12-13 09:40:08	ga_ls8c_ard_3-2-1_093086_2022-12-13_final
2023-03-01 11:24:09	ga_ls8c_ard_3-2-1_111069_2023-03-01_final
2023-03-03 09:33:41	ga_ls8c_ard_3-2-1_093071_2023-03-03_final
2023-04-12 10:25:26	ga_ls8c_ard_3-2-1_101078_2023-04-12_final
2023-04-25 11:30:59	ga_ls8c_ard_3-2-1_112072_2023-04-25_final
2023-06-29 10:37:25	ga_ls8c_ard_3-2-1_103077_2023-06-29_final
2023-07-07 11:25:45	ga_ls8c_ard_3-2-1_111074_2023-07-07_final
2023-10-02 09:51:55	ga_ls8c_ard_3-2-1_096070_2023-10-02_final
2023-11-08 10:10:53	ga_ls8c_ard_3-2-1_099071_2023-11-08_final
2024-02-08 10:35:57	ga_ls8c_ard_3-2-1_103072_2024-02-08_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