AI-Powered Forest Inventory: Advancing Tree Detection and Enumeration (KEY IJP************542)

• Bhuvan Ranjan Thadepu,Ms. Shubhangi Mahule, Thatikonda Pranathi ,Tirumani Asha Kiran ,Arrolla Siddhartha

Abstract

Tree detection and counting are fundamental tasks in environmental monitoring and management, crucial for assessing forest health and biodiversity. This study presents a focused effort on developing a robust system for tree detection and counting utilizing the YOLOv8 model, known for its efficiency in object detection tasks. Augmented with Roboflow annotations, the approach ensures structured handling of annotated datasets, facilitating model training. The methodology involves optimizing the YOLOv8 model parameters to achieve high precision and recall rates, crucial for accurate tree identification across diverse environmental settings.