Across northern New England and New York, the Northern Forest Center helps rural communities leverage their best assets to improve the local economy and revitalize their towns. The work the Center does ranges from supporting entrepreneurship and innovation in the forestry industry to building housing and improving outdoor recreation assets. In Lancaster, New Hampshire, the Center is helping establish a series of walking, biking, and general use trails. One of the potential areas for development is the dense 283-acre Town Forest. Before establishing any new trails, the Center and the Lancaster Conservation Commission wanted to better understand the unique ecological features of the forest and the suitability of the terrain for the proposed trails. As a geospatial technology company with extensive work in forestry, Whiteout Solutions was well suited to support this project on both the data collection and analysis side.

Objective: The objective of this project was to establish a baseline dataset for planning trailhead accessibility, recreation trail development and conservation planning. LiDAR and multispectral imagery would be collected from a UAV. The project was to be conducted in June during leaf out or fully vegetated condition, this required flights to be conducted at slower speeds for LiDAR to ensure penetration of the tree canopies. Digital terrain models (DTM) from LiDAR data would provide a foundation to conduct a suitability analysis that highlighted the best location for trail development and accessibility. The criteria for the analysis weighted a series of factors including slope of terrain, water runoff, proximity to parking, proximity to old logging roads and trail standards like IMBA trail grading system. When pairing the DSM, DTM, multispectral imagery and available wetlands data, we were able to produce a map that delineates the most sensitive areas in the forest, unhealthy vegetation, and probable tree species – all insights that help with on-going conservation efforts.

Challenge: To date the Town Forest had been underutilized. The town recently conducted a timber sale, and a decade ago had created a hiking trail through the forest, which has since grown over. The only direct access to the forest was through an unmaintained road shared only by owners of a few camps. Easements had been established on the north side of the forest, but to-date no trail or parking had been established to allow access. Additionally, the forest is very dense, with an abundance of high and low vegetation. The terrain is rolling with some steeper areas and other swampy wetland zones. Both accessibility and the overgrown vegetation and terrain were key factors in the forest’s underutilization.

Effective planning for new trail development required a better understanding of all the factors above, which could be achieved by collecting high resolution imagery and LiDAR. Pre-planning the data collection missions are critical for all projects. For this project, we encountered large swaths of land with no available take-off or landing zones for our UAVs due to canopy density. The terrain varied greatly with rolling hills obstructing visibility of the collection areas, large ponds, and transmission power lines. All these factors meant that battery management and flight planning had to be done with precision to ensure data quality and safety.

This project included a variety of stakeholders, including the project leader from Northern Forest Center, the town manager, conservation committee members, consulting ecologist and trail builders. Each of these stakeholders had different levels of experience with geospatial data and hoped to get different answers from the data. We strongly believe that the value of LiDAR and other remote sensed data comes when it is combined to tell a more comprehensive story. The final deliverables for this project included ten different datasets and analyses. For deliverables to generate value over time for stakeholders, especially those who are not geospatial professionals, it’s our responsibility to create data and imagery that can be digested in a glance and each interaction expands the comprehension of the data. We found that providing the deliverables in an interactive website including descriptions of the datasets help reduce confusion and adds value to the data overtime.