干旱区生态环境知识资源中心(Arid): Mapping the risk zoning of storm flood disaster based on heterogeneous data and a machine learning algorithm in Xinjiang, China

Arid

DOI	10.1111/jfr3.12671
	Mapping the risk zoning of storm flood disaster based on heterogeneous data and a machine learning algorithm in Xinjiang, China
	Liu, Yan; Lu, Xinyu; Yao, Yuanzhi; Wang, Ni; Guo, Yanyun; Ji, Chunrong; Xu, Jianhui
通讯作者	Liu, Y ; Ji, CR
来源期刊	JOURNAL OF FLOOD RISK MANAGEMENT
ISSN	1753-318X
英文摘要	Mapping flood risk zone is an essential task in the arid region for sustainable water resources management. Due to the lack of hydrological and meteorological information and disaster event inventory in Xinjiang, China, storm flood disaster (SFD) risk zoning is an effective technique in investigating the potential impact of SFD. In this study, the statistics about natural, social, and risk related to SFD are collated. With the help of the compiled inventory data, a disaster risk assessment model for storm flood is proposed for the Xinjiang region based on the random forest (RF) algorithm. Randomly selected negative and positive samples from the historical SFD locations are composed of five different total samples. The overall prediction accuracy of the five sample groups attained 83.48%, indicating that the proposed RF model can well capture the spatial distribution of SFD in Xinjiang. It should also be noted that the spatial heterogeneity and complexity of SFD had a significant effect on its spatial distribution in Xinjiang. There are spatial distribution characteristics of lowland plains and high plateaus; the main mountainous regions, plains in the middle-lower reaches of major rivers, and areas surrounding major lakes are prone to flooding. The variable importance RF indicates that the disaster risk is mainly affected by the following factors, including hazard factors, catastrophic intensity, population density, as well as economic development in the affected area. Besides, latitude, longitude, agricultural acreage, road density, distance from rivers, and the maximum monthly precipitation account for most of the increase in storm flooding disasters, and they are the main triggering point for SFD in Xinjiang. The proposed model provides some insight into the disaster in the mountainous region, and gives useful guidance for the national macro-control of flood prevention and disaster reduction.
英文关键词	random forests storm flood disaster Xinjiang zoning maps
类型	Article ; Early Access
语种	英语
开放获取类型	DOAJ Gold
收录类别	SCI-E
WOS记录号	WOS:000588552700001
WOS关键词	REMOTE-SENSING DATA
WOS类目	Environmental Sciences ; Water Resources
WOS研究方向	Environmental Sciences & Ecology ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/328473
作者单位	[Liu, Yan; Lu, Xinyu; Wang, Ni; Ji, Chunrong] China Meteorol Adm, Inst Desert Meteorol, Urumqi 830002, Peoples R China; [Yao, Yuanzhi] Auburn Univ, Sch Forestry & Wildlife Sci, Auburn, AL 36849 USA; [Guo, Yanyun] Xinjiang Uygur Autonomous Reg Meteorol Bur, Xinjiang Agr Meteorol Stn, Agr Meteorol Stn, Urumqi, Peoples R China; [Xu, Jianhui] Guangzhou Inst Geog, Guangdong Open Lab Geospatial Informat Technol &, Key Lab Guangdong Utilizat Remote Sensing & Geog, Guangzhou, Peoples R China
推荐引用方式 GB/T 7714	Liu, Yan,Lu, Xinyu,Yao, Yuanzhi,et al. Mapping the risk zoning of storm flood disaster based on heterogeneous data and a machine learning algorithm in Xinjiang, China[J].
APA	Liu, Yan.,Lu, Xinyu.,Yao, Yuanzhi.,Wang, Ni.,Guo, Yanyun.,...&Xu, Jianhui.
MLA	Liu, Yan,et al."Mapping the risk zoning of storm flood disaster based on heterogeneous data and a machine learning algorithm in Xinjiang, China".JOURNAL OF FLOOD RISK MANAGEMENT