Background Remote sensing for forest monitoring has expanded substantially over the past four decades, driven by advances in Earth observation, geospatial analytics, and artificial intelligence. Despite this rapid growth, the literature remains fragmented across diverse themes, methods, and disciplinary domains, limiting a comprehensive understanding of its long-term evolution. Unlike previous bibliometric studies that have focused on specific technologies or applications, this study provides an integrated assessment of the field’s intellectual foundations, collaboration patterns, thematic dynamics, and emerging research frontiers over a period of four and a half decades. Methods A bibliometric and science-mapping approach was applied to Scopus-indexed publications published between 1980 and 2025. Performance analysis was combined with co-authorship, co-citation, and keyword co-occurrence techniques to examine scientific productivity, collaboration networks, intellectual foundations, and thematic developments. Results Scientific output has increased steadily, accompanied by interconnected citation networks and expanding international collaboration. Scholarly activity is concentrated among influential authors, institutions, and countries, with North America, Western Europe, and East Asia serving as centers of knowledge production. Five domains shape the intellectual landscape: land-cover dynamics, LiDAR-based assessment, Earth observation analytics, forest inventory modeling, and ecosystem disturbance studies. Thematic trajectories indicate a transition from descriptive land-cover analysis to predictive, data-intensive approaches driven by machine learning, deep learning, cloud computing, multi-sensor integration, and observations. Linkages between forest monitoring, carbon accounting, climate adaptation, and environmental governance highlight the growing societal relevance of the field. Emerging research frontiers include foundation models, explainable artificial intelligence, digital-twin forest ecosystems, near-real-time monitoring, and climate-smart forest governance.
Rumakito et al. (Thu,) studied this question.