Application of Photogrammetry for the Estimation of Tree Height in Closed Canopied Tropical Forests of Southwestern Nigeria

Abstract

The study estimated tree height from high-resolution Digital Surface Models (DSMs) and Digital Terrain Models (DTMs) products derived from photogrammetric orthomosaics captured with the Sensor Optimized for Drone Applications (S.O.D.A) metric camera mounted on an Ebee Sensefly Survey Drone.  This was to determine a sustainable approach for the estimation of tree height in dense forests with closed canopies. A 500-meter drone sampling plot was marked for each of the 3 tropical forest reserves that were used for this study, and 10 cm digital aerial photos were captured during the drone survey. The data sets were converted to point clouds and thereafter to Ortho mosaics for DSM and DTM, respectively, using standard processing techniques with the Pix4D software.

Results showed average tree height ranges from 0 - 50 meters for the three forest reserves with photogrammetry, and a correlation of 0.96, R² of 97.6, and SE of 0.05 compared with height from field measurements using a laser range finder .The study concluded that Photogrammetry offers a cost-effective, scalable, and spatially continuous approach for estimating tree height over expansive areas in the area of study while enabling integration with GIS and remote sensing workflows, supporting large-scale forest monitoring, inventory, and management with higher efficiency and broader utility.