Predicting the Potential Impact of Climate Change on People–Caused Forest Fire Occurrence in South Korea - 九大コレクション

＜紀要論文＞
Predicting the Potential Impact of Climate Change on People–Caused Forest Fire Occurrence in South Korea

作成者	作成者名 Lee, Si-Young 所属機関所属機関名 Division of the Professional Graduate School of Disasters Prevention Technology, Kangwon National University \| Korea Climate Change Countermeasure Research Center
	作成者名 Chae, Hee Mun 所属機関所属機関名 \| Korea Climate Change Countermeasure Research Center
	作成者名 Park, Gwan-Soo 所属機関所属機関名 Department of Forest Resources, Chungnam National University \| Korea Climate Change Countermeasure Research Center
	著者識別子 K001681 作成者名 Ohga, Shoji 大賀, 祥治所属機関所属機関名 Laboratory of Forest Resources Management, Division of Forest Environmental Sciences, Department of Agro–environmental Sciences, Faculty of Agriculture, Kyushu University \| Korea Climate Change Countermeasure Research Center 九州大学大学院農学研究院環境農学部門森林環境科学講座
本文言語	英語
出版者	Faculty of Agriculture, Kyushu University
出版者	九州大学大学院農学研究院
発行日	2012-02
収録物名	九州大学大学院農学研究院紀要
巻	57
号	1
開始ページ	17
終了ページ	25
出版タイプ	Version of Record
アクセス権	open access
Crossref DOI	https://doi.org/10.5109/22043
関連情報	Journal of the Faculty of Agriculture, Kyushu University \|\| 57(1) \|\| p17-25
	九州大学大学院農学研究院紀要 \|\| 57(1) \|\| p17-25
	http://www.agr.kyushu-u.ac.jp/

ファイル	ファイルタイプ	サイズ	閲覧回数	説明
p017	pdf	856 KB	495

PISSN	0023-6152
NCID	AA00697606
レコードID	22043
査読有無	査読無
主題	forest fire
	forest management
	General Circulation Models
ISSN	0023-6152
NCID	AA00697606
注記	We investigated the potential impact of climate change on people–caused forest fire occurrence in South Korea. Logistic regression analysis methods were used to develop daily fire occurrence prediction models for each of nine study areas. These models were then coupled with climate scenario data produced by two General Circulation Models (CCCma and CCSR/NIES) to predict future people–caused fire occurrence in those nine areas. Our results suggest the number of fire days will increase by roughly 7 to 58% depending upon the district. However, as the prediction of fire occurrence was varied by the land use, the vegetation, human activity, forest management policy and etc., more factors related this part should be need to research more with this study.
登録日	2012.06.20
更新日	2022.11.11