Classify Wetland and Vegetation using Multispec

Environmental and Maintenance tasks often rely on time consuming field reconnaissance to determine the extent of wetland vegetation communities or noxious weed invasion to comply with federal and state laws and regulations. There is a need to find methods to make field reconnaissance more efficient, or in some situations, entirely unnecessary. This research proposes to determine the type and extent of vegetation based on multispectral or hyperspectral sensors. This data would be very beneficial in delineating wetland and upland vegetation. MDT administers multiple wetland mitigation sites that are monitored annually by physical (on-the-ground) inspection and delineation of the wetland boundaries at each site. This research proposes to use Unmanned Aerial Systems (UAS) with multispectral and hyperspectral sensors in conjunction with Artificial Intelligence (AI) or Machine Learning (ML) to delineate the wetland boundaries and verify the results by comparison with the boundaries documented during on-the-ground delineations done at a selected number of MDT wetland sites. The ultimate goal of this research is to develop multi or hyperspectral wetland inspection techniques that are acceptable to regulators (US Army Corps of Engineers - USACE).


  • English


  • Status: Proposed
  • Sponsor Organizations:

    Montana Department of Transportation

    2701 Prospect Avenue
    P.O. Box 201001
    Helena, MT  United States  59620-1001
  • Project Managers:

    Callejas, Vaneza

  • Start Date: 20230614
  • Expected Completion Date: 0
  • Actual Completion Date: 0

Subject/Index Terms

Filing Info

  • Accession Number: 01888766
  • Record Type: Research project
  • Source Agency: Montana Department of Transportation
  • Files: RIP, STATEDOT
  • Created Date: Jul 26 2023 12:59PM