An overview of remote sensing technology in forest management

Abstract

Remote sensing technology has revolutionized the field of forest management, offering unparalleled capabilities for monitoring, assessing, and managing forested landscapes. This overview paper explores the diverse applications and advancements of remote sensing techniques in forest management. It delves into the various remote sensing technologies, including satellite imaging, LiDAR (Light Detection and Ranging), and drones equipped with high-resolution cameras, highlighting their roles in data collection, analysis, and interpretation. This chapter discusses the utilization of remote sensing data for forest inventory, species identification, habitat assessment, and monitoring of forest disturbances such as wildfires, pests, and diseases. Furthermore, it emphasizes the integration of remote sensing with Geographic Information Systems (GIS) and machine learning algorithms for enhanced accuracy in mapping, modeling, and decision-making processes. Challenges and limitations inherent in remote sensing applications within forest management are also addressed, including issues related to data accuracy, processing techniques, and cost-effectiveness. Additionally, the paper explores future trends and potential advancements in remote sensing technology, emphasizing the need for continued research and development to further improve its efficacy in sustainable forest management practices. This chapter aims to provide a comprehensive understanding of the role and significance of remote sensing technology in modern forest management, emphasizing its potential to contribute to informed decision-making, conservation efforts, and the sustainable utilization of forest resources. © 2026 Elsevier Inc. All rights reserved..