Drones as a tool for monoculture plantation assessment in the steepland tropics

Abstract

Smallholder tree plantations are expanding in the steepland tropics due to demand for timber and interest in ecosystem services, such as carbon storage. Financial mechanisms are developing to compensate vegetation carbon stores. However, measuring biomass-necessary for accessing carbon funds-at small scales is costly and time-intensive. Therefore, we test whether low-cost drones can accurately estimate height and biomass in monoculture plantations in the tropics. We used Ecosynth, a drone-based structure from motion technique, to build 3D vegetation models from drone photographs. These data were filtered to create a digital terrain model (DTM) and digital surface model (DSM). Two different canopy height models (CHMs) from the Ecosynth DSM were obtained by subtracting terrain elevations from the Ecosynth DTM and a LIDAR DTM. We compared height and biomass derived from these CHMs to field data. Both CHMs accurately predicted the height of all species combined; however, the CHM from the LiDAR DTM predicted heights and biomass on a per-species basis more accurately. Height and biomass estimates were strong for evergreen single-stemmed trees, and unreliable for small leaf-off species during the dry season. This study demonstrates that drones can estimate plantation biomass for select species when used with an accurate DTM.