Small Drones for Community-Based Forest Monitoring: An Assessment of Their Feasibility and Potential in Tropical Areas

نویسندگان

  • Jaime Paneque-Gálvez
  • Michael K. McCall
  • Brian M. Napoletano
  • Serge A. Wich
  • Lian Pin Koh
چکیده

Data gathered through community-based forest monitoring (CBFM) programs may be as accurate as those gathered by professional scientists, but acquired at a much lower cost and capable of providing more detailed data about the occurrence, extent and drivers of forest loss, degradation and regrowth at the community scale. In addition, CBFM enables greater survey repeatability. Therefore, CBFM should be a fundamental component of national forest monitoring systems and programs to measure, report and verify (MRV) REDD+ activities. To contribute to the development of more effective approaches to CBFM, in this paper we assess: (1) the feasibility of using small, low-cost drones (i.e., remotely piloted aerial vehicles) in CBFM programs; (2) their potential advantages and disadvantages for communities, partner organizations and forest data end-users; and (3) to what extent their utilization, coupled with ground surveys and local ecological knowledge, OPEN ACCESS Forests 2014, 5 1482 would improve tropical forest monitoring. To do so, we reviewed the existing literature regarding environmental applications of drones, including forest monitoring, and drew on our own firsthand experience flying small drones to map and monitor tropical forests and training people to operate them. We believe that the utilization of small drones can enhance CBFM and that this approach is feasible in many locations throughout the tropics if some degree of external assistance and funding is provided to communities. We suggest that the use of small drones can help tropical communities to better manage and conserve their forests whilst benefiting partner organizations, governments and forest data end-users, particularly those engaged in forestry, biodiversity conservation and climate change mitigation projects such as REDD+.

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تاریخ انتشار 2014