講演詳細

経営部門[Forest Management]

日付	2024年3月8日
開始時刻	ポスター発表
会場名	531
講演番号	PD-21（学生ポスター賞審査対象）
発表題目	Estimating structural parameters of a complex mixed conifer-broadleaf forest using UAV photogrammetry Estimating structural parameters of a complex mixed conifer-broadleaf forest using UAV photogrammetry
所属	Graduate School of Agricultural and Life Sciences, The University of Tokyo
要旨本文	Estimating forest structural parameters in structurally complex forests remains as challenging. Use of high-resolution imagery, suitable remote sensing variables and models will highly contribute to improve estimation accuracy. We used high-resolution UAV RGB imagery to estimate forest structural parameters in a mixed conifer-broadleaf forest at the University of Tokyo Hokkaido Forest. In addition to DBH, spatial position and height of dominant trees were measured in the inventory plots. Pix4D software was used to derive dense point clouds, digital surface model, canopy height model (CHM) and orthomosaics. Mean, maximum, percentile and standard deviation of CHM were validated with the height and DBH, basal area (BA), stem volume (V) and tree carbon stock (CST). 75–99% percentile heights of CHM were highly correlated with dominant tree height, while CHM mean was highly correlated with BA, V, and CST. Conifer dominated plots had a higher estimation accuracy with dominant tree height.
著者氏名	○Karthigesu, Jeyavanan1,2 ・ Toshiaki Owari3 ・ Satoshi Tsuyuki1 ・ Takuya Hiroshima1
著者所属	1The University of Tokyo ・ 2University of Jaffna ・ 3The University of Tokyo
キーワード	stand parameters, Central Hokkaido, Unmanned aerial vehicle
Key word	stand parameters, Central Hokkaido, Unmanned aerial vehicle