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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

60 results

Time (local)	Label
2013-04-20 11:40:15	ga_ls8c_ard_3-0-0_113074_2013-04-20_final
2014-02-13 11:20:22	ga_ls8c_ard_3-0-0_110073_2014-02-13_final
2014-11-06 10:19:31	ga_ls8c_ard_3-0-0_100077_2014-11-06_final
2014-11-29 10:28:04	ga_ls8c_ard_3-0-0_101083_2014-11-29_final
2014-12-30 11:17:09	ga_ls8c_ard_3-0-0_110067_2014-12-30_final
2015-03-06 11:06:28	ga_ls8c_ard_3-0-0_108072_2015-03-06_final
2015-03-20 09:40:12	ga_ls8c_ard_3-0-0_094073_2015-03-20_final
2016-01-27 09:34:31	ga_ls8c_ard_3-0-0_093073_2016-01-27_final
2016-07-08 11:46:32	ga_ls8c_ard_3-0-0_114079_2016-07-08_final
2016-08-04 11:24:31	ga_ls8c_ard_3-0-0_111070_2016-08-04_final
2016-09-28 11:32:30	ga_ls8c_ard_3-0-0_112074_2016-09-28_final
2016-11-15 11:29:48	ga_ls8c_ard_3-0-0_112067_2016-11-15_final
2016-12-31 11:42:04	ga_ls8c_ard_3-0-0_114067_2016-12-31_final
2017-03-04 09:25:30	ga_ls8c_ard_3-0-0_091082_2017-03-03_final
2017-05-19 09:49:04	ga_ls8c_ard_3-0-0_095080_2017-05-19_final
2017-06-08 09:21:44	ga_ls8c_ard_3-0-0_091073_2017-06-07_final
2017-10-13 10:22:23	ga_ls8c_ard_3-0-0_100084_2017-10-13_final
2018-01-07 09:40:20	ga_ls8c_ard_3-0-0_094072_2018-01-07_final
2018-01-21 11:32:16	ga_ls8c_ard_3-0-0_112074_2018-01-21_final
2018-04-22 11:12:58	ga_ls8c_ard_3-0-0_109074_2018-04-22_final
2018-05-29 11:30:18	ga_ls8c_ard_3-0-0_112072_2018-05-29_final
2018-06-28 10:08:46	ga_ls8c_ard_3-0-0_098084_2018-06-28_final
2018-07-08 10:42:20	ga_ls8c_ard_3-0-0_104075_2018-07-08_final
2018-11-16 11:17:15	ga_ls8c_ard_3-0-0_109083_2018-11-16_final
2018-12-29 10:58:39	ga_ls8c_ard_3-0-0_106083_2018-12-29_final
2019-02-02 11:24:15	ga_ls8c_ard_3-0-0_111070_2019-02-02_final
2019-05-05 10:09:23	ga_ls8c_ard_3-0-0_099069_2019-05-05_final
2019-10-28 10:14:19	ga_ls8c_ard_3-1-0_099079_2019-10-28_final
2020-02-05 09:46:28	ga_ls8c_ard_3-1-0_095072_2020-02-05_final
2020-02-11 10:46:39	ga_ls8c_ard_3-1-0_105068_2020-02-11_final
2020-03-01 09:40:11	ga_ls8c_ard_3-1-0_094072_2020-03-01_final
2020-03-24 11:23:04	ga_ls8c_ard_3-1-0_111067_2020-03-24_final
2020-07-26 10:11:03	ga_ls8c_ard_3-1-0_099072_2020-07-26_final
2020-08-05 10:49:22	ga_ls8c_ard_3-1-0_105075_2020-08-05_final
2020-10-18 11:26:01	ga_ls8c_ard_3-1-0_111073_2020-10-18_final
2020-11-10 09:52:52	ga_ls8c_ard_3-1-0_096072_2020-11-10_final
2020-12-21 11:24:49	ga_ls8c_ard_3-2-0_111070_2020-12-21_final
2021-02-05 11:42:33	ga_ls8c_ard_3-2-0_113084_2021-02-05_final
2021-03-05 10:27:49	ga_ls8c_ard_3-2-0_101083_2021-03-05_final
2021-03-18 11:32:05	ga_ls8c_ard_3-2-0_112074_2021-03-18_final
2021-03-25 10:03:21	ga_ls8c_ard_3-2-0_097084_2021-03-25_final
2021-05-02 09:25:12	ga_ls8c_ard_3-2-0_091082_2021-05-01_final
2021-09-25 10:49:19	ga_ls8c_ard_3-2-0_105074_2021-09-25_final
2021-10-21 09:48:02	ga_ls8c_ard_3-2-0_095075_2021-10-21_final
2021-10-25 11:01:48	ga_ls8c_ard_3-2-0_107074_2021-10-25_final
2022-03-04 10:49:25	ga_ls8c_ard_3-2-1_105075_2022-03-04_final
2022-03-21 09:51:39	ga_ls8c_ard_3-2-1_096070_2022-03-21_final
2022-05-12 11:09:51	ga_ls8c_ard_3-2-1_108080_2022-05-12_final
2022-05-12 11:10:39	ga_ls8c_ard_3-2-1_108082_2022-05-12_final
2022-09-17 09:30:06	ga_ls8c_ard_3-2-1_092076_2022-09-17_final
2022-10-12 11:03:05	ga_ls8c_ard_3-2-1_107077_2022-10-12_final
2022-12-23 10:09:06	ga_ls8c_ard_3-2-1_099066_2022-12-23_final
2023-01-29 10:29:39	ga_ls8c_ard_3-2-1_102071_2023-01-29_final
2023-05-29 09:39:08	ga_ls8c_ard_3-2-1_094071_2023-05-29_final
2023-09-09 11:25:41	ga_ls8c_ard_3-2-1_111073_2023-09-09_final
2023-11-01 10:07:33	ga_ls8c_ard_3-2-1_098078_2023-11-01_final
2023-12-11 10:53:44	ga_ls8c_ard_3-2-1_106070_2023-12-11_final
2024-01-17 09:34:58	ga_ls8c_ard_3-2-1_093074_2024-01-17_final
2024-01-19 09:23:47	ga_ls8c_ard_3-2-1_091077_2024-01-18_final
2024-02-05 10:04:38	ga_ls8c_ard_3-2-1_098071_2024-02-05_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