Automated forest land division using deep learning and drone imagery

Abstract

This paper proposes an automated solution for tree enumeration in areas designated for forest land division using drone image processing. Traditional tree counting methods are time-consuming and error-prone. Our approach leverages drone imagery and advanced computer vision algorithms. The solution demonstrates the potential to accurately detect tree crowns, facilitating informed decision-making in forest land division projects, promoting sustainability and efficient resource management.