Integrating Low-Cost UAV and GCP-based Structure-from-Motion Techniques to Generate Very High-Resolution Orthoimage for Bamboo Forest Mapping and Individuals Segmentation

Forest resources inventory and monitoring are essential for efficient management of natural resources. Remote sensing-based mapping technology provides geospatially explicit information on forest ecosystems. Generally, the attributes of forests derived from moderate satellite images show spatial and classification inaccuracy, introducing uncertainty in formulating forest dynamics and misleading inappropriate management plans. This study examines the efficiency of low-cost UAVs in generating orthoimages for differentiating bamboo from broadleaf species in forest succession. The results show that the generated very high-resolution orthoimage can reveal detailed spatial features of both bamboo and tree crowns, providing an excellent opportunity to differentiate individual bamboo crowns from trees and therefore help derive bamboo expansion and degradation over the forest.