A framework for precisely thinning planning in a managed pure Chinese fir forest based on UAV remote sensing

Abstract

Where and how many trees should be thinned in a pure managed forest to improve forest quality and increase ecological benefits are important forest questions. In this study we address such challenges by providing a novel framework for planning thinning operations through Unmanned Aerial Vehicle (UAV) remote sensing techniques, which can not only obtain forest attributes of its entire stand with spatial properties, but also optimize the selection of thinning areas, thinning intensities and cut-trees. This study helps to reduce the costs of time-consuming and laborious ground investigations. The framework was demonstrated by applying it into a subtropical Chinese fir plantation in southeastern China. Results showed that RGB images acquired by a low-cost UAV have great potential in depicting forest structure. The overall accuracy of the individual tree detection in the case study was 85.19 % ± 0.48 %. The overall accuracy and the intersection over union of the non-crown area extraction were 94.94 % and 82.65 %, respectively. For the two determined thinning areas, 19.5 % and 14.3 % crown density were required to thin in the primary and secondary regions, respectively. In addition, the top-down perspective of UAV remote sensing makes up for the limitations of the bottom-up perspective of traditional forestry. The framework can act as a basic model for forest managers to modify and expand for customizing detailed thinning guidelines.

Keywords: Forest management; Individual tree; Remote sensing; Thinning; Unmanned aerial vehicle.