日本地球惑星科学連合2024年大会

講演情報

[E] ポスター発表

セッション記号 H (地球人間圏科学) » H-TT 計測技術・研究手法

[H-TT14] 高精細地形表層情報と人新世におけるコネクティビティ

2024年5月28日(火) 17:15 〜 18:45 ポスター会場 (幕張メッセ国際展示場 6ホール)

コンビーナ:早川 裕弌(北海道大学地球環境科学研究院)、Gomez Christopher(神戸大学 海事科学部 海域火山リスク科学研究室)、笠井 美青(北海道大学大学院農学研究院)、小倉 拓郎(兵庫教育大学学校教育研究科)


17:15 〜 18:45

[HTT14-P03] Reconstruction of traditional knowledge of flood damage by integrating high-definition topographic data and local knowledge

*小倉 拓郎1、島本 多敬2水野 敏明3山内 啓之4、片山 大輔2八反地 剛5 (1.兵庫教育大学学校教育研究科、2.滋賀県立琵琶湖博物館、3.滋賀県琵琶湖環境科学研究センター、4.立命館大学アート・リサーチセンター、5.筑波大学生命環境系)

キーワード:Eco-DRR、UAV-LiDAR、水害伝統知

Landslides and floods, frequently occurring in Japan due to torrential rains in its humid fluctuation zone, raise concerns about exacerbated disasters amid climate change—traditional Eco-DRR facilities, like levees and flood-protection forests, historically safeguarded against floods by leveraging the ecosystem. However, loss, modification, and urbanization have obscured their existence and distribution. This study re-evaluates forgotten Eco-DRR facilities in the Echi River basin, Shiga Prefecture, employing high-definition topographic data, historical documents, and resident interviews. The Study area is the riparian forest 15.2 km from the Echi River mouth in Higashi-omi City, where residents recall an old stone dam named "Saruo" in the forest's southeastern part. Utilizing UAV-LiDAR technology, we measured the forest floor, generated point cloud data, and extracted ground surfaces using filtering software. Resident reports of Saruo in farmland south of the forest guided the mapping of convex landforms Saruo by merging topographic data in GIS. Comparison with historical maps, such as the 1874 Kanzaki-gun village map, facilitated the identification and scale determination of Saruo. Topographic interpretation unveiled six convex landforms, three confirmed as Saruo stone dams. Discrepancies between observed sizes and historical records suggest modifications over time, including modern embankment construction post-1874. These findings may result from sedimentation or land modifications, indicating new Saruo's presence and existing ones' discrepancies. Future efforts aim to integrate natural and human data to understand disaster risk comprehensively.