UNH scientists experiment with drones to collect forestry data
June 24. 2018 10:45PM
DURHAM — Scientists with the New Hampshire Agricultural Experiment Station at the University of New Hampshire recently analyzed the effectiveness of unmanned aerial systems to collect forestry data to assess ecological changes of forests and land cover.
“Remote sensing is learning something about an object without coming in contact with it — so trying to learn from a distance,” said experiment station researcher Russell Congalton, professor of remote sensing and geographic information systems.
“There are many benefits to this because we can collect information at different levels of detail at various spatial scales. We can use different portions of the electromagnetic spectrum, and we can do it over different time frames. Some projects require knowing something every hour. Some things we want to know about once a year.”
Congalton conducted this research with Benjamin Fraser, a doctoral student in his research lab.
According to Congalton and Fraser, unmanned aerial systems offer users the ability to capture imagery at unprecedented spatial resolutions due to their flexible designs, low costs, automated workflows, and minimal technical knowledge requirements.
Experiment station scientists conducted research using an eBee Plus, fixed-wing drone on three woodland properties owned and managed by the University of New Hampshire — the Kingman Research Farm, Moore Field and West Foss Farm.
Researchers were interested in evaluating the impacts of flying height on Structure from Motion (SfM) processing success, discrepancies in software output results, and the effects of processing parameter quality, according to a University of New Hampshire news release.
Structure from Motion is a photogrammetric imaging technique for estimating three-dimensional structures from two-dimensional image sequences.
After experimenting with flying the eBee Plus at heights of 50 meters, 100 meters, and 120 meters above the forest canopy, scientists concluded it is impractical to process imagery captured at lower than 100 meters. Overall, the 100-meter flying height provided the highest quality results.
“As unmanned aerial systems continue to expand their sphere of influence and develop technologically, data quality evaluation methods and best use practices based on aerial photogrammetry principles must remain apparent” Congalton said.
The research material is based upon work supported by the NH Agricultural Experiment Station, through joint funding of the National Institute of Food and Agriculture, U.S. Department of Agriculture, and the state of New Hampshire.