Digital Innovation in Forest Science: Applications of Artificial Intelligence, Remote Sensing and Smart Monitoring Systems for Ecosystem Conservation

Abstract

The integration of digital technologies and artificial intelligence (AI) in forestry is revolutionizing traditional forest

management practices worldwide. This comprehensive review examines the current state, applications, challenges,

and future prospects of digital forestry technologies, including remote sensing, unmanned aerial vehicles (UAVs),

Light Detection and Ranging (LiDAR) systems, Internet of Things (IoT) sensors, machine learning algorithms, and

emerging technologies such as blockchain and digital twins. Digital forestry encompasses precision forest inventory,

real-time forest health monitoring, automated species classification, wildfire detection and management, and

sustainable forest resource planning. Recent advances in machine learning approaches, particularly deep learning

models like PointNet++, PointMLP, and convolutional neural networks, have demonstrated exceptional accuracy rates

exceeding 95% in tree species classification using UAV-LiDAR data. IoT sensor networks enable continuous

monitoring of forest parameters including temperature, humidity, soil moisture, and air quality, facilitating early

detection of forest disturbances. Blockchain technology ensures transparent and traceable forest supply chains,

combating illegal logging and supporting deforestation-free certification