Implementation Strategy of Remote Sensing and Road Network Optimization in Forest Harvesting Operations Planning

Abstract

The integration of remote sensing technologies and road network optimization presents a transformative approach to planning forest harvesting operations. This study employs a qualitative methodology based on an extensive literature review and library research to explore effective implementation strategies for combining these technologies in forest management. Remote sensing, particularly through aerial laser scanning and satellite imagery, provides detailed spatial data such as digital terrain models (DTMs) that enhance the identification of suitable harvesting areas by capturing critical terrain features like slope, elevation, and proximity to roads. Concurrently, optimizing road networks facilitates efficient timber extraction by minimizing transportation costs and environmental impacts. The literature reveals that machine learning algorithms, such as random forests, can effectively classify terrain suitability by analyzing remote sensing-derived features, thus supporting decision-making in harvesting method selection. However, challenges remain in integrating these technologies within existing forest management frameworks due to infrastructural, technical, and institutional constraints. The study highlights the importance of adaptive workflows that incorporate remote sensing data into operational planning without disrupting established procedures. Moreover, it emphasizes the role of multi-scale data integration—from national forest inventories to plot-level measurements—in achieving precise, spatially explicit planning outputs. This synthesis underscores that successful implementation requires coordinated efforts among forest managers, technology providers, and policymakers to develop user-friendly tools and supportive policies. Ultimately, the combined use of remote sensing and road network optimization holds significant potential to improve the sustainability, cost-effectiveness, and environmental performance of forest harvesting operations.