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Enhancing Wetland Classification for the FGDC Wetland Mapping Standard in Montana

Award Number G12AC20144, Category 5: FGDC-endorsed Standards Implementation Training and Outreach

This project advanced a key recommendation to enhance the current FGDC-endorsed Wetland Mapping Standard. Specifically, the U.S. Fish and Wildlife Service (USFWS), the maintenance authority for the standard, developed a list of hydrogeomorphic descriptors to describe wetland characteristics not currently addressed under the existing wetland classification standard. These descriptors are added to existing digital wetland data to enhance the information associated with each wetland polygon by describing the landscape position, landform, water flow path, and waterbody type (LLWW). Enhancing wetland data with LLWW descriptors can provide a more comprehensive picture of wetland type and potential wetland function. With input from project partners, the Montana Natural Heritage Program (MTNHP) has developed semi-automated procedures to assign LLWW descriptors to existing digital wetland data. The MTNHP also developed training materials and other technical guidance on the LLWW approach. As a result, creators of digital wetland data in Montana have the tools necessary to add LLWW descriptors to wetland data. Additionally, users of wetland data have the information necessary to understand how these descriptors enhance the information that digital wetland data can provide. This project has been presented at both state and regional natural resource conferences, and a webinar is scheduled through the Wetland Mapping Consortium.

Final Report --- LLWW Training Materials

Interim Report

Kick-off Meeting Presentation (PDF)

The University of Montana-Montana Natural Heritage Program
Montana Department of Environmental Quality’s (DEQ) Wetland Program
Colorado Natural Heritage Program, Colorado State
CNL World


Karen Newlon, University of Montana-Montana Natural Heritage Program

Linda Vance, Montana Natural Heritage Program

Last Updated: Dec 19, 2013 10:34 AM
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