講演詳細

経営部門[Forest Management]

日付	2026年3月17日
開始時刻	ポスター発表
会場名	多目的ホール
講演番号	PD-7
発表題目	Monitoring Forest Disturbance Dynamics in the University of Tokyo Hokkaido Forest Using Landsat Time Series Monitoring Forest Disturbance Dynamics in the University of Tokyo Hokkaido Forest Using Landsat Time Series
所属	東京大学
要旨本文	Forest disturbances alter ecosystem services and carbon storage, making accurate spatiotemporal mapping essential for sustainable management. Using Landsat time series (1985_2025), we applied the Continuous Change Detection and Classification (CCDC) algorithm in Google Earth Engine to delineate disturbance footprints in the University of Tokyo Hokkaido Forest (UTHF). We cross-referenced CCDC-detected events with the UTHF silvicultural management plan to quantify overlaps with plantation operations, examined post-disturbance recovery, and flaged likely unrecorded disturbances. The legacy of the 1981 typhoon remained detectable until 2005. Beyond planned replanting and the 1981 damage, CCDC revealed additional disturbance patches absent from historical records, some coinciding with road-damage zones attributed to the 2016 typhoon. These results characterize disturbance regimes, and provide actionable evidence for long-term planning and monitoring under changing climate at UTHF.
著者氏名	○Yunfan Li1 ・ Songqiu Deng1,2 ・ Toshiaki Owari1,2
著者所属	1The University of Tokyo ・ 2The University of Tokyo
キーワード	Forest disturbance, Time series, CCDC algorithm, Google earth engine
Key word	Forest disturbance, Time series, CCDC algorithm, Google earth engine