In the new study, Dr. Zahawi and the team, including researchers from the University of Maryland and the University of California-Santa Cruz, USA, tested a new automated approach to monitoring that doesn’t involve manual intervention. Using an inexpensive drone-based remote sensing methodology called “Ecosynth”, the researchers measured the structure of the forest canopy across in 1-hectare regenerating fields that were previously agricultural land spread over 100km2 of southern Costa Rica. The land is part of a long-term tropical forest restoration study.
The drones were fitted with a simple 10 megapixel point-and-shoot digital camera and use open-source software to process these overlapping images. The camera takes thousands of photos and the Ecosynth methodology creates 3D images called point clouds that represent the vegetation. In total, the drone and camera cost US$1500 – less than a tenth the cost of some equivalent flights.
The researchers compared the results produced by Ecosynth for canopy height, above ground biomass and canopy structure – whether the canopy was rough or open – to field based measures. They also evaluated whether Ecosynth-measured canopy height could predict the abundance of fruit-eating (frugivore) birds were present as field based height measures; many fruit-eating birds, such as the mountain thrush, black guan and sooty-capped bush tanager, are important for forest regeneration. The results showed that Ecosynth was as accurate as human monitoring, although there were some errors when the canopy was low.
“There is still some work to do to optimize Ecosynth and make sure measurements are accurate in all situations. However, the approach has real promise in monitoring regeneration,” said Dr. Zahawi. “The reduced cost and labor intensity means that many more farmers will be able to monitor their land, giving us far more data about how best to conserve tropical forests.”
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