Toward a digital twin of forest roads – road weather stations for monitoring road condition and trafficability in Eastern Finland - Väätäinen, Kari; Kostensalo, Joel; Anttila, Perttu; Savinainen, Matti; Kaakkurivaara, Tomi; Pohjankukka, Jonne; Lumberg, Ville; Ala-Ilomäki, Jari; Laitila, Juha; Lindeman, Harri; Lopatin, Eugene; Sikanen, Lauri (Taylor & Francis, 2026)
Forest roads are crucial for forest management, wood supply, recreation, and wildfire mitigation. However, adverse weather conditions in spring and autumn can weaken these roads, leading to damage and traffic disruptions. This study developed components for a digital twin of forest roads in Eastern Finland, with a focus on weather and moisture monitoring, road structure, traffic monitoring, and their impact on road bearing capacity. Sensors and weather stations reliably monitored road conditions, achieving 99.98% and 100% uptime over a year. Traffic on forest roads was monitored using pressure sensors and game camera images, with a neural network classifying traffic types with 97% accuracy. A light falling weight deflectometer indicated that road bearing capacity during critical periods could decrease to 10–20% of its maximum, underscoring the necessity for reliable real-time solutions to alert road users about road trafficability
Keywords: bearing capacity; light falling weight deflectometer; neural network; sensor data; timber truck; soil type