Application of Drone Technology for Forest Inventory and Monitoring in Oyo State Forest Reserves

Conventional forest inventory methods are labour-intensive, costly, and often unable to cover large and difficult terrain in adequate time, creating data gaps that compromise management planning for forest reserves in southwestern Nigeria. Drone-based remote sensing offers a practical, cost-effective complement to ground surveys for rapid canopy assessment and change monitoring. This study evaluates the application of unmanned aerial vehicle technology for forest inventory and monitoring in two Oyo State forest reserves, comparing the accuracy, cost, and operational feasibility of drone-based canopy height mapping with ground-based inventory. A DJI Phantom 4 RTK drone was used to acquire high-resolution imagery processed through structure-from-motion photogrammetry to generate canopy height models and digital terrain models. Sample plot data collected simultaneously provided ground truth for comparison. Individual tree detection was attempted using segmentation algorithms on the point cloud data. Accuracy of drone-derived tree height estimates was within 8% of ground measurements for emergent trees, though understorey estimation showed greater error. Individual tree detection achieved 74% accuracy. Drone surveys covered the equivalent of 30 ground survey plots per flight hour, representing a fourfold efficiency gain. Operational constraints including battery range, pilot certification requirements, and cloud cover disruptions are documented. The study concludes that drone technology is operationally viable for monitoring forest management units in Oyo State and recommends phased integration into the State Forestry Commission's annual inventory protocol. Keywords: drone, unmanned aerial vehicle, forest inventory, canopy height model, Oyo State