This study presents a new method of detecting individual treetops from lidar data and applies marker-controlled watershed segmentation into isolating individual trees in savanna woodland The treetops

Additionally, the proposed method was compared with two existing methods: a manual delineation method and a watershed segmentation method using a fixed threshold. The proposed method outperformed both methods, including the manual delineation method, with an absolute accuracy of 64.1 percent compared to 58.5 percent and 60.1 percent, respectively.

The study also showed that the proposed method was effective in detecting individual trees in savanna woodlands, which are characterized by scattered trees and open canopy cover. The method could be further improved by incorporating additional information, such as spectral and textural features, and by applying machine learning algorithms to enhance the accuracy of tree detection.

Overall, the study presents a new and promising method for detecting individual trees from lidar data, which could have important implications for forest monitoring and management.