ゴトウ　シンタロウ   SHINTARO GOTOH
  後藤　真太郎
   所属   地球環境科学部 環境システム学科
   職種   教授
言語種別 英語
発行・発表の年月 2022/09/30
形態種別 論文（その他）
査読 査読あり
標題 Disaster Area Detection by Deep Learning using UAV and Satellite Imagery
執筆形態 共著
掲載誌名 Proc. of Asian Conference on Remote sensing 2022
掲載区分国外
出版社・発行元 Asian Conference on Remote sensing
担当範囲 論文統括、結果の評価
担当区分 責任著者
著者・共著者 Kazuaki AOKI, Shintaro GOTO. Chitomi SAKAI
概要 Due to recent changes in the global environment, damage from disasters such as extreme
weather, typhoons, and heavy rainfall has been occurring frequently. In this study, we investigated a
method for automatic detection of damaged areas from aerial photographs taken by UAV and
satellite photographs in order to obtain detailed information on the damage at an early stage. We
applied a deep learning-based method to detect damaged areas from orthomosaic images of
disaster-stricken areas using data taken by a drone in the area affected by Typhoon 19 and other
disasters. The construction of a system that automatically detects damaged areas is expected to lead
to an early understanding situations and cost reductions.