AI-Powered Precision Forestry for Sustainable Timber Management and Reforestation

Abstract

Sustainable forestry is critical for preserving biodiversity and mitigating deforestation. This paper examines the role of machine learning in precision forestry, including AI-driven tree health monitoring, logging optimization, and reforestation planning. Remote sensing data, LiDAR, and deep learning techniques such as convolutional neural networks (CNNs) are applied to detect illegal logging, track forest growth, and enhance carbon sequestration efforts. The study presents real-world examples of AI-driven forestry management systems that balance economic needs with environmental conservation, ensuring long-term sustainability.