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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

62 results

Time (local)	Label
2013-06-11 09:37:15	ga_ls8c_ard_3-0-0_093075_2013-06-11_final
2013-07-21 10:26:14	ga_ls8c_ard_3-0-0_101074_2013-07-21_final
2013-10-14 10:42:42	ga_ls8c_ard_3-0-0_104069_2013-10-14_final
2013-12-10 10:41:26	ga_ls8c_ard_3-0-0_103082_2013-12-10_final
2014-09-23 11:30:22	ga_ls8c_ard_3-0-0_112069_2014-09-23_final
2014-10-25 11:32:05	ga_ls8c_ard_3-0-0_112073_2014-10-25_final
2015-04-17 11:46:48	ga_ls8c_ard_3-0-0_114081_2015-04-17_final
2015-05-05 09:50:33	ga_ls8c_ard_3-0-0_096069_2015-05-05_final
2015-05-29 10:44:41	ga_ls8c_ard_3-0-0_104081_2015-05-29_final
2015-07-23 09:09:43	ga_ls8c_ard_3-0-0_089074_2015-07-22_final
2015-10-07 09:32:28	ga_ls8c_ard_3-0-0_093068_2015-10-07_final
2015-11-28 09:12:40	ga_ls8c_ard_3-0-0_089080_2015-11-27_final
2016-01-31 10:51:03	ga_ls8c_ard_3-0-0_105079_2016-01-31_final
2016-02-23 10:57:52	ga_ls8c_ard_3-0-0_106081_2016-02-23_final
2016-04-19 11:46:58	ga_ls8c_ard_3-0-0_114081_2016-04-19_final
2016-07-14 09:29:24	ga_ls8c_ard_3-0-0_092076_2016-07-13_final
2016-07-21 09:36:49	ga_ls8c_ard_3-0-0_093079_2016-07-21_final
2016-08-29 11:22:04	ga_ls8c_ard_3-0-0_110079_2016-08-29_final
2016-09-02 10:58:10	ga_ls8c_ard_3-0-0_106081_2016-09-02_final
2016-10-14 11:32:11	ga_ls8c_ard_3-0-0_112073_2016-10-14_final
2016-11-14 09:10:51	ga_ls8c_ard_3-0-0_089075_2016-11-13_final
2016-11-15 11:32:12	ga_ls8c_ard_3-0-0_112073_2016-11-15_final
2016-11-30 09:16:02	ga_ls8c_ard_3-0-0_089088_2016-11-29_final
2016-12-07 12:31:35	ga_ls8c_ard_3-2-1_122067_2016-12-07_final
2016-12-25 10:45:51	ga_ls8c_ard_3-0-0_104081_2016-12-25_final
2017-05-21 09:33:08	ga_ls8c_ard_3-0-0_093071_2017-05-21_final
2017-06-11 09:50:16	ga_ls8c_ard_3-0-0_096067_2017-06-11_final
2017-08-13 09:15:45	ga_ls8c_ard_3-0-0_089088_2017-08-12_final
2017-11-15 11:03:36	ga_ls8c_ard_3-0-0_107079_2017-11-15_final
2018-01-13 10:42:30	ga_ls8c_ard_3-0-0_104073_2018-01-13_final
2018-02-16 10:31:04	ga_ls8c_ard_3-0-0_102076_2018-02-16_final
2018-09-13 09:33:39	ga_ls8c_ard_3-0-0_093072_2018-09-13_final
2018-12-14 10:03:01	ga_ls8c_ard_3-0-0_097083_2018-12-14_final
2019-02-25 11:31:34	ga_ls8c_ard_3-0-0_112073_2019-02-25_final
2019-06-15 11:47:15	ga_ls8c_ard_3-1-0_114081_2019-06-15_final
2019-12-30 11:07:23	ga_ls8c_ard_3-1-0_108073_2019-12-30_final
2020-01-24 12:37:35	ga_ls8c_ard_3-2-1_123067_2020-01-24_final
2020-06-18 09:09:00	ga_ls8c_ard_3-2-1_089072_2020-06-17_interim
2020-09-28 10:09:02	ga_ls8c_ard_3-2-1_099066_2020-09-28_final
2021-03-11 08:10:36	ga_ls8c_ard_3-2-1_079080_2021-03-10_final
2021-06-03 09:23:50	ga_ls8c_ard_3-2-0_091078_2021-06-02_final
2021-06-28 10:57:52	ga_ls8c_ard_3-2-0_106081_2021-06-28_final
2021-07-21 09:24:50	ga_ls8c_ard_3-2-0_091080_2021-07-20_final
2021-10-27 09:16:08	ga_ls8c_ard_3-2-0_089088_2021-10-26_final
2022-02-24 09:58:24	ga_ls8c_ard_3-2-1_097071_2022-02-24_final
2022-04-25 10:23:16	ga_ls8c_ard_3-2-1_101072_2022-04-25_final
2022-09-04 11:40:35	ga_ls8c_ard_3-2-1_113078_2022-09-04_final
2022-12-01 10:53:09	ga_ls8c_ard_3-2-1_105083_2022-12-01_final
2022-12-27 08:11:07	ga_ls8c_ard_3-2-1_079080_2022-12-26_final
2022-12-31 11:02:11	ga_ls8c_ard_3-2-1_107075_2022-12-31_final
2023-01-04 10:40:15	ga_ls8c_ard_3-2-1_103082_2023-01-04_final
2023-01-21 11:21:02	ga_ls8c_ard_3-2-1_110076_2023-01-21_final
2023-03-31 10:01:45	ga_ls8c_ard_3-2-1_097080_2023-03-31_final
2023-04-29 09:31:45	ga_ls8c_ard_3-2-1_092083_2023-04-29_final
2023-10-09 10:00:06	ga_ls8c_ard_3-2-1_097075_2023-10-09_final
2023-11-07 09:35:13	ga_ls8c_ard_3-2-1_092090_2023-11-07_final
2024-01-03 12:37:33	ga_ls8c_ard_3-2-1_123067_2024-01-03_final
2024-01-08 09:43:07	ga_ls8c_ard_3-2-1_094079_2024-01-08_final
2024-01-26 11:09:33	ga_ls8c_ard_3-2-1_108079_2024-01-26_final
2024-01-29 09:58:24	ga_ls8c_ard_3-2-1_097071_2024-01-29_final
2024-02-21 10:05:24	ga_ls8c_ard_3-2-1_098073_2024-02-21_final
2024-02-29 12:31:16	ga_ls8c_ard_3-2-1_122067_2024-02-29_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