Tree Profiling and Data Analysis of Forest Canopy Cover Using Aerial Images

Tree counting is a crucial task in forest management and conservation, providing valuable information on the abundance of tree populations. Traditional methods of manual counting and measuring can be time-consuming and labor-intensive, but advances in technology have enabled more efficient approaches, such as using drones and computer vision algorithms. In this project, we explore the use of drones and OpenCV for non linear tree counting. Aerial images captured by drones are processed using OpenCV algorithms to identify and locate individual trees, providing accurate and efficient data on tree populations. The image processing algorithms can be customized to distinguish between different types of trees and provide information such as tree height and crown density. Our results demonstrate the effectiveness of using drones and OpenCV form on linear tree counting, with improved accuracy and efficiency compared to manual counting methods. Overall, our approach has the potential to revolutionize forest management and conservation by providing precise data on tree populations, which can be used to inform decision-making and planning.