Improving soil salinity prediction with high resolution DEM derived from LiDAR data

Liu, Xiaoye and Peterson, Jim and Zhang, Zhenyu and Chandra, Shobhit (2005) Improving soil salinity prediction with high resolution DEM derived from LiDAR data. In: 9th International Symposium on Physical Measurements and Signatures in Remote Sensing (ISPMSRS 2005), 17-19 Oct 2005, Beijing, China.

Abstract

The aim of this study is to investigate the capability of integration of LiDAR derived terrain and hydrological features with other salinity related datasets to improve prediction of areas at risk from salinity in a catchment area in Victoria, Australia. Terrain and hydrological features including slope, drainage density and hilltop were generated from LiDAR derived DEM and a relative low quality DEM separately. These features were combined with other salinity related datasets to predict areas at risk from salinity. The results showed that using LiDAR-derived high quality DEM can improve the accuracy of salinity risk prediction.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: c. ISPMSRS.
Depositing User: Ms Leslie Blay
Faculty / Department / School: Historic - Faculty of Engineering and Surveying - Department of Electrical, Electronic and Computer Engineering
Date Deposited: 09 Sep 2011 05:09
Last Modified: 02 Jul 2013 23:56
Uncontrolled Keywords: salinity; Victoria; LiDAR;
Fields of Research (FOR2008): 04 Earth Sciences > 0406 Physical Geography and Environmental Geoscience > 040608 Surfacewater Hydrology
05 Environmental Sciences > 0502 Environmental Science and Management > 050204 Environmental Impact Assessment
05 Environmental Sciences > 0503 Soil Sciences > 050302 Land Capability and Soil Degradation
Socio-Economic Objective (SEO2008): D Environment > 96 Environment > 9609 Land and Water Management > 960999 Land and Water Management of Environments not elsewhere classified
URI: http://eprints.usq.edu.au/id/eprint/8217

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