Improvements to NCDOT’s Wetland Prediction Model (Phase II)

This Final Report is to summarize several main achievements of this project as follows: (1) Method Development for Wetland Type Identification and Prediction; (2) Wetland Type (Prediction) Automation Tool (WAMTAT) using LiDAR data for non-coastal areas; (3) Systematic Method Development of Wetland Functional E-Assessment for 16 North Carolina Wetland Assessment Method (NC WAM) Metrics and function combination; (4) Initial Wetland Functional E-Assessment Tools (WAMFEAT) as extra; and (5) User Friendly deliverables of methods, models and documentations. 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.” That also completes the goal of the project to provide an advanced wetland type prediction method and automation tool based on ArcGIS, and to develop wetland functional e-assessment method. The University of North Carolina (UNC) Charlotte WAM Research Team with Axiom Research Team has successfully completed a number of valuable research topics related to wetland type prediction process, such as process automation, variables exploration, data mining, and statistical analysis, and samples selection; and wetland functional e-assessment methodology and its tools. The acclaimed results include the deliverable WAM Type Automation Tool (WAMTAT) and WAMFEAT tools and the User Guides to the tools, wetland type prediction method, and the wetland e-functional assessment method.

• Record URL:
  https://connect.ncdot.gov/projects/research/RNAProjDocs/2016-16%20Final%20Report.pdf
• Summary URL:
  https://connect.ncdot.gov/projects/research/Pages/ProjDetails.aspx?ProjectID=2016-16
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/54663
• Supplemental Notes:
  • Report date March 3, 2020, initial November 28, 2019.
• 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 Computer Science
  Charlotte, NC  United States  28233

  Axiom Environmental

  Raleigh, NC  United States 

  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
  • Smith, Sandy
  • Davis, Scott
  • Jiang, Shanshan
• Publication Date: 2020-3-3

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Appendices; Figures; Maps; Photos; References; Tables;
• Pagination: 50p

Subject/Index Terms

• TRT Terms: Automation; Case studies; Forecasting; Laser radar; Methodology; Validation; Wetlands
• Identifier Terms: ArcGIS; North Carolina Department of Transportation
• Subject Areas: Environment; Highways; Planning and Forecasting;

Filing Info

• Accession Number: 01754654
• Record Type: Publication
• Report/Paper Numbers: FHWA/NC/2016-16
• Contract Numbers: NCDOT Project 2016-16
• Files: NTL, TRIS, ATRI, USDOT, STATEDOT
• Created Date: Oct 14 2020 5:41PM