Cici Alexander, Amanda H. Korstjens, Emma Hankinson, Graham Usher, Nathan Harrison, Matthew G. Nowak, Abdullah Abdullah, Serge A. Wich, Ross A. Hill
Emergent trees, which are taller than surrounding trees with exposed crowns, provide crucial services to several rainforest species especially to endangered primates such as gibbons and siamangs (Hylobatidae). Hylobatids show a preference for emergent trees as sleeping sites and for vocal displays, however, they are under threat from both habitat modifications and the impacts of climate change. Traditional plot-based ground surveys have limitations in detecting and mapping emergent trees across a landscape, especially in dense tropical forests. In this study, a method is developed to detect emergent trees in a tropical rainforest in Sumatra, Indonesia, using a photogrammetric point cloud derived from RGB images collected using an Unmanned Aerial Vehicle (UAV). If a treetop, identified as a local maximum in a Digital Surface Model generated from the point cloud, was higher than the surrounding treetops (Trees_EM), and its crown was exposed above its neighbours (Trees_SL; assessed using slope and circularity measures), it was identified as an emergent tree, which might therefore be selected preferentially as a sleeping tree by hylobatids. A total of 54 out of 63 trees were classified as emergent by the developed algorithm and in the field. The algorithm is based on relative height rather than canopy height (due to a lack of terrain data in photogrammetric point clouds in a rainforest environment), which makes it equally applicable to photogrammetric and airborne laser scanning point cloud data. © 2018 The Authors
Bournemouth University, Department of Life and Environmental Sciences, Talbot Campus, Poole, BH12 5BB, Dorset, United Kingdom; The PanEco Foundation - Sumatran Orangutan Conservation Programme, Chileweg 5, Berg am Irchel 8415, Switzerland; Southern Illinois University, Department of Anthropology, 1000 Faner Drive, Carbondale, 62901, IL, United States; Syiah Kuala University, Department of Biology, Banda Aceh, 23111, Indonesia; Liverpool John Moores University, School of Natural Sciences and Psychology, Liverpool, L33AF, United Kingdom; University of Amsterdam, Institute for Biodiversity and Ecosystem Dynamics, Sciencepark 904, Amsterdam, 1098, Netherlands; Aarhus University, Aarhus Institute of Advanced Studies (AIAS), Høegh-Guldbergs Gade 6B, Aarhus C, DK-8000, Denmark
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