講演詳細

利用部門[Forest Engineering]

日付	2026年3月18日
開始時刻	11:00
会場名	406
講演番号	K-8
発表題目	Towards Data-Driven Modeling of Cut-to-Length Harvester Productivity in Japan Towards Data-Driven Modeling of Cut-to-Length Harvester Productivity in Japan
所属	東京大学
要旨本文	The cut-to-length (CTL) harvesting method is increasingly adopted in Japan’s forest operations, yet quantitative knowledge on the productivity of harvesting machines under local conditions remains limited. This study aims to develop data-driven models of daily productivity based on standardized StanForD data collected from harvesters in CTL operations in Hokkaido and Tochigi. The analysis focuses on key site and stand variables such as tree dimensions, ground slope, stand density and ground roughness. By identifying the most influential factors and quantifying their relationships to productivity, the study seeks to improve the understanding of machine performance across varying operational conditions. The results will contribute to developing locally adapted productivity benchmarks and support more efficient planning and optimization of mechanized harvesting operations in Japan.
著者氏名	○Lahrsen, Steffen T1 ・ Yoshioka, Takuyuki1 ・ Aruga, Katsuhiro2
著者所属	1Faculty of Agriculture, Forest Science, Forest Utilization, The University of Tokyo ・ 2Faculty of Agriculture, Department of Forest Science, Utsunomiya University
キーワード	StanForD, LiDAR, Benchmarking, Automation, Mechanized Harvesting
Key word	StanForD, LiDAR, Benchmarking, Automation, Mechanized Harvesting