Improvements to NCDOT's Wetland Prediction Model

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.

• Record URL:
  https://connect.ncdot.gov/projects/research/RNAProjDocs/2013-13%20Final%20Report.pdf
• 
• Summary URL:
  https://connect.ncdot.gov/projects/research/pages/ProjDetails.aspx?ProjectID=2013-13
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/44234
• Corporate Authors:

  University of North Carolina, Charlotte

  Department of Engineering Technology
  9201 University City Boulevard
  Charlotte, NC  United States  28233

  University of North Carolina, Charlotte

  Department of Software and Information Systems
  9201 University City Boulevard
  Charlotte, NC  United States  28223-0001

  University of North Carolina, Charlotte

  Department of Geography and Earth Sciences
  9201 University City Boulevard
  Charlotte, NC  United States  28223

  University of North Carolina, Charlotte

  Department of Civil and Environmental Engineering
  9201 University City Boulevard
  Charlotte, NC  United States  28223-0001

  North Carolina Department of Transportation

  Raleigh, NC  United States 

  Federal Highway Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Wang, Sheng-Guo
  • Bai, Libin
  • Deng, Jing
  • Jia, Meijuan
  • Chen, Mingzhi
  • Liang, Shu
  • Wang, Peng
  • Yalla, Sushmitha
  • Huang, Fangjian
  • Chen, Shen-En
  • Tang, Wenwu
• Publication Date: 2015-2-28

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Appendices; Figures; Maps; References; Tables;
• Pagination: 48p

Subject/Index Terms

• TRT Terms: Analysis; Automation; Forecasting; Laser radar; Regression analysis; Wetlands
• Identifier Terms: ArcGIS; North Carolina Department of Transportation
• Geographic Terms: North Carolina
• Subject Areas: Environment; Highways; Planning and Forecasting;

Filing Info

• Accession Number: 01712423
• Record Type: Publication
• Report/Paper Numbers: NCDOT RP 2013-13
• Files: NTL, TRIS, ATRI, USDOT, STATEDOT
• Created Date: Jul 24 2019 10:35PM