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
2013-08-29 10:35:18	ga_ls8c_ard_3-0-0_102081_2013-08-29_final
2013-11-16 11:26:59	ga_ls8c_ard_3-0-0_111072_2013-11-16_final
2014-03-21 09:19:54	ga_ls8c_ard_3-0-0_090082_2014-03-20_final
2014-03-21 09:22:42	ga_ls8c_ard_3-0-0_090089_2014-03-20_final
2014-04-27 09:34:15	ga_ls8c_ard_3-0-0_093073_2014-04-27_final
2014-07-22 10:35:43	ga_ls8c_ard_3-0-0_103072_2014-07-22_final
2014-10-20 09:33:53	ga_ls8c_ard_3-0-0_093071_2014-10-20_final
2014-12-21 11:24:37	ga_ls8c_ard_3-0-0_111070_2014-12-21_final
2015-01-17 09:33:52	ga_ls8c_ard_3-0-0_092087_2015-01-17_final
2015-02-25 09:39:50	ga_ls8c_ard_3-0-0_093087_2015-02-25_final
2015-03-11 11:22:56	ga_ls8c_ard_3-0-0_111067_2015-03-11_final
2015-04-02 09:09:31	ga_ls8c_ard_3-0-0_089074_2015-04-01_final
2015-07-22 11:44:13	ga_ls8c_ard_3-0-0_114074_2015-07-22_final
2015-08-26 10:36:26	ga_ls8c_ard_3-0-0_103074_2015-08-26_final
2016-03-14 10:29:54	ga_ls8c_ard_3-0-0_102073_2016-03-14_final
2016-04-03 10:09:47	ga_ls8c_ard_3-0-0_098085_2016-04-03_final
2016-04-09 09:27:29	ga_ls8c_ard_3-0-0_092072_2016-04-08_final
2016-07-30 09:27:52	ga_ls8c_ard_3-0-0_092072_2016-07-29_final
2016-09-11 10:52:49	ga_ls8c_ard_3-0-0_105083_2016-09-11_final
2016-12-15 10:07:37	ga_ls8c_ard_3-0-0_098078_2016-12-15_final
2017-01-28 10:29:44	ga_ls8c_ard_3-0-0_102072_2017-01-28_final
2018-01-04 10:47:33	ga_ls8c_ard_3-0-0_105070_2018-01-04_final
2018-02-03 09:21:33	ga_ls8c_ard_3-0-0_091072_2018-02-02_final
2018-02-27 11:50:56	ga_ls8c_ard_3-0-0_115075_2018-02-27_final
2018-03-10 11:31:05	ga_ls8c_ard_3-0-0_112072_2018-03-10_final
2018-03-13 10:25:28	ga_ls8c_ard_3-0-0_101078_2018-03-13_final
2018-06-21 09:56:31	ga_ls8c_ard_3-0-0_097069_2018-06-21_final
2018-09-24 10:52:28	ga_ls8c_ard_3-0-0_106068_2018-09-24_final
2019-01-04 10:19:10	ga_ls8c_ard_3-0-0_100077_2019-01-04_final
2019-01-27 10:27:16	ga_ls8c_ard_3-0-0_101082_2019-01-27_final
2019-02-15 09:22:26	ga_ls8c_ard_3-0-0_090090_2019-02-14_final
2019-02-25 11:30:22	ga_ls8c_ard_3-0-0_112070_2019-02-25_final
2019-03-31 09:39:22	ga_ls8c_ard_3-1-0_094071_2019-03-31_final
2019-10-16 11:24:29	ga_ls8c_ard_3-1-0_111069_2019-10-16_final
2019-10-19 10:19:42	ga_ls8c_ard_3-1-0_100077_2019-10-19_final
2019-10-29 09:17:06	ga_ls8c_ard_3-1-0_090075_2019-10-28_final
2019-11-07 09:10:54	ga_ls8c_ard_3-1-0_089075_2019-11-06_final
2019-12-31 10:13:45	ga_ls8c_ard_3-1-0_099078_2019-12-31_final
2020-02-06 10:29:19	ga_ls8c_ard_3-1-0_102071_2020-02-06_final
2020-05-27 11:23:33	ga_ls8c_ard_3-1-0_111069_2020-05-27_final
2020-07-14 09:46:40	ga_ls8c_ard_3-1-0_095073_2020-07-14_final
2020-08-01 11:13:40	ga_ls8c_ard_3-1-0_109074_2020-08-01_final
2020-09-27 09:28:10	ga_ls8c_ard_3-1-0_092072_2020-09-26_final
2020-12-11 09:16:28	ga_ls8c_ard_3-1-0_089089_2020-12-10_final
2020-12-29 10:34:57	ga_ls8c_ard_3-2-0_103069_2020-12-29_final
2021-02-17 10:27:56	ga_ls8c_ard_3-2-0_101083_2021-02-17_final
2021-07-23 09:14:05	ga_ls8c_ard_3-2-0_089084_2021-07-22_final
2021-08-05 10:18:59	ga_ls8c_ard_3-2-0_100076_2021-08-05_final
2021-11-07 10:29:16	ga_ls8c_ard_3-2-0_102070_2021-11-07_final
2021-12-10 11:18:04	ga_ls8c_ard_3-2-1_109084_2021-12-10_final
2022-01-14 10:03:34	ga_ls8c_ard_3-2-1_098068_2022-01-14_final
2022-03-23 11:23:44	ga_ls8c_ard_3-2-1_110084_2022-03-23_final
2022-07-27 11:31:50	ga_ls8c_ard_3-2-1_112072_2022-07-27_final
2022-08-18 09:20:49	ga_ls8c_ard_3-2-1_090084_2022-08-17_final
2022-10-13 10:04:39	ga_ls8c_ard_3-2-1_098070_2022-10-13_final
2022-10-17 11:18:27	ga_ls8c_ard_3-2-1_110069_2022-10-17_final
2022-10-21 09:17:41	ga_ls8c_ard_3-2-1_090076_2022-10-20_final
2023-03-12 09:31:02	ga_ls8c_ard_3-2-1_092080_2023-03-12_final
2023-06-26 10:08:52	ga_ls8c_ard_3-2-1_098083_2023-06-26_final
2023-09-04 11:11:31	ga_ls8c_ard_3-2-1_108084_2023-09-04_final
2023-09-21 10:10:00	ga_ls8c_ard_3-2-1_099069_2023-09-21_final
2023-10-13 09:34:37	ga_ls8c_ard_3-2-1_093073_2023-10-13_final
2023-11-25 10:53:26	ga_ls8c_ard_3-2-1_106069_2023-11-25_final
2024-01-17 11:13:27	ga_ls8c_ard_3-2-1_109073_2024-01-17_final
2024-02-06 09:14:13	ga_ls8c_ard_3-2-1_089084_2024-02-05_final
2024-03-18 10:40:37	ga_ls8c_ard_3-2-1_104069_2024-03-18_final
2024-03-19 09:46:35	ga_ls8c_ard_3-2-1_095073_2024-03-19_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