United States Department of Transportation
i
Improvements to NCDOT's Wetland Prediction Model
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2015-02-25
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[PDF-1.97 MB]
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Corporate Creators:University of North Carolina at Charlotte. Dept. of Engineering Technology ; University of North Carolina at Charlotte. Dept. of Software and Information Systems ; University of North Carolina at Charlotte. Dept. of Geography and Earth Sciences ; University of North Carolina at Charlotte. Department of Civil and Environmental Engineering
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Edition:Final report, April 30, 2012 – February 15, 2015
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Abstract:This Final Report is to summarize several main achievements of this project as follows: (1) Automation Method and its Tools for the Wetland Identification and Analysis Process; (2) Method Development for Wetland Identification Process; (3) Reliability and Flexibility of Automation Tools and Methods; and (4) User Friendly deliverables. These achievements fit the North Carolina Department of Transportation (NCDOT) research needs as: “while NCDOT has made significant advances with the concept, the process and tools of predicting wetlands using LiDAR is under-developed.” The goal of the project is to provide the improved LiDAR-based wetland prediction models with highly automated, reliable, and user-friendly tools based on ArcGIS for NCDOT. The UNC Charlotte wetland assessment method (WAM) Research Team has successfully completed a number of valuable research topics related to wetland prediction process, such as process automation, variables exploration, data mining, and statistical analysis. The acclaimed results include the deliverable WAM Automation Process Tools and the Users’ Guide to the Tools.
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