@article{oai:nied-repo.bosai.go.jp:00000795,
 author = {秋田 寛己 and 若月 強 and 檀上 徹 and 佐藤 昌人},
 issue = {60},
 journal = {主要災害調査, Natural Disaster Research Report},
 month = {Feb},
 note = {令和2年7月豪雨で土砂災害のあった熊本県と岐阜県の一部地域に，NDVI（正規化植生指数）差分画像を用いた斜面変動範囲の抽出手法を適用し，その適用性や課題を検討した．まず，災害前後のSentinel-2 衛星画像を用いてNDVI 差分画像を作成し，NDVI 差分値の下位25% 確率値を閾値に定めて斜面変動範囲を抽出した．さらに，抽出結果からは平地部のノイズ（斜面勾配10度未満，河道内の裸地，雲範囲，小面積裸地）を除去した．現地調査で確認した土石流地点での抽出結果を確認したところ，熊本調査地では約77%（13地点中10地点），岐阜調査地では約67%（9地点中6地点）の土石流を抽出できていたが，土石流の流走部などの細長い形状の場所は，林冠被覆などにより抽出漏れがあることがわかった．, We extracted slope movement range using differential normalized-difference-vegetation-index (NDVI) images of areas that were severely affected by heavy rainfall events and landslides in Kumamoto and Gifu prefectures in July 2020. We then examined the potential application and challenges associated with extracting slope movement range using this method. NDVI images were prepared using Sentinel-2 satellite images taken before and after the disasters. The slope movement range was extracted from the images using the 25th percentile of the differential NDVI values as a threshold. Furthermore, noise (i.e., areas with a slope angle <10°, 100 m-wide bands on each side of river channel centerlines, areas of cloud, and small areas of bare ground) were excluded from the classifications.
By comparing the extraction results to actual debris flows in the field, we successfully extracted approximately 67-77% of the slope movement range in the satellite images. However, elongated debris flows could not be extracted in sufficient detail because the area was covered by forest canopy.},
 pages = {49--64},
 title = {NDVI差分画像を用いた斜面変動範囲抽出手法の検討－令和2年7月豪雨による熊本県・岐阜県の土砂災害解析事例－},
 year = {2022},
 yomi = {アキタ ヒロミ and ワカツキ ツヨシ and ダンジョウ トオル and サトウ マサト}
}