Recent Advances in Forest Inventory and Mapping: A Review

Forest inventory and mapping are foundational for effective forest management, enabling systematic assessment of forest structure, composition, biomass, and ecological changes over time. Traditional methods, while historically valuable, are constrained by limited spatial coverage, high labour costs, and slow data processing. Recent technological advances have revolutionized forest inventory practices through the integration of remote sensing platforms, unmanned aerial vehicles (UAVs), robotics, artificial intelligence (AI), and mobile-based data collection tools. Satellite based optical imagery from platforms such as Landsat, Sentinel-2, and Planet Scope facilitates high resolution and long-term monitoring of forest cover and health. Light Detection and Ranging (LiDAR) and Terrestrial Laser Scanning (TLS) enable precise 3D characterization of forest structure and aboveground biomass. Digital Aerial Photogrammetry (DAP), which employs drones to generate point clouds through structure-from-motion algorithms, provides cost-effective alternatives for even-aged forest inventory. Robotic systems such as the FGI ROAMER and Komatsu 931.1 now automate ground-level forest measurements using real-time LiDAR processing, even in GPS-denied environments. Furthermore, AI and machine learning algorithms are increasingly deployed for species classification, biomass estimation, and change detection from satellite and LiDAR data. Mobile-based tools such as Open Foris, Van Darshan, and Forest Watcher enable real-time, geo-tagged forest data collection, improving participatory monitoring and forest governance. Collectively, role and opportunities of these technologies have been over viewed, which offers scalable, accurate, and timely inventory systems essential for sustainable forestry, biodiversity conservation, and climate change mitigation.