Remote Sensing of Forest Structure Characteristics to Inform Prescriptive Vegetation Maintenance on the Pinhoti National Recreation Trail
Date
2-15-2024
Faculty Mentor
Ross Martin, Chemistry & Geosciences
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Submission Type
Conference Proceeding
Location
10:45-10:55am | Houston Cole Library, 11th Floor
Description
This project details a remote sensing workflow intended to assist vegetation maintenance planning for the Pinhoti National Recreation Trail (PNRT). Trail maintenance is necessary to provide the best possible experience to users and to maintain the national recreation trail designation held by the PNRT. Often, this maintenance involves mechanical treatments of understory vegetation that has encroached upon the trail during the growing season. Generally, volunteers or students are sent into the field to monitor and document trail overgrowth conditions. With this information, land managers formulate a plan to deal with any issues that were recorded. The workflow documented here generates a shapefile of areas that are likely to experience trail overgrowth conditions. This data can be used to narrow the focus of initial monitoring efforts, making the planning process less resource demanding for the management agency.
The resulting shapefile is a selected range of values from a canopy height model (CHM). For the purposes of this project, canopy height and density are used as a proxy for the existence of trail overgrowth conditions. The relationship between canopy coverage and resource availability for understory plants makes canopy density a good predictor for understory conditions. The CHM is created from airborne LiDAR data and a range of its values is selected out into a new shapefile. Existing data from the PNRT brush management survey is used to determine the target canopy ranges through point sampling.
Field data collection for this project was conducted with ArcGIS Field Maps. Point and line data were taken to detail trail overgrowth. LiDAR data was sourced from the USGS at a resolution of one meter. All data used thus far has been focused on section 5 of the PNRT, near Gunthertown, AL. Data processing, analysis, and map creation were all done in ArcGIS Pro.
This project has been a collaborative effort between JSU’s Department of Chemistry and Geosciences, JSU’s Trail Science Institute, and the Alabama Trails Foundation.
Keywords
student research, geography
Rights
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Disciplines
Geochemistry
Recommended Citation
Graffeo, John, "Remote Sensing of Forest Structure Characteristics to Inform Prescriptive Vegetation Maintenance on the Pinhoti National Recreation Trail" (2024). JSU Student Symposium 2024. 3.
https://digitalcommons.jsu.edu/ce_jsustudentsymp_2024/3