Urban Flood Mapping Based on Unmanned Aerial Vehicle Remote Sensing and Random Forest Classifier-A Case of Yuyao, China

	Urban Flood Mapping Based on Unmanned Aerial Vehicle Remote Sensing and Random Forest Classifier-A Case of Yuyao, China
	Feng, Quanlong 1; Liu, Jiantao 1; Gong, Jianhua 1
刊名	WATER
	2015
卷号	7 期号:4
通讯作者	Gong, JH (reprint author), Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, 20 Datun Rd, Beijing 100101, Peoples R China.
英文摘要	Flooding is a severe natural hazard, which poses a great threat to human life and property, especially in densely-populated urban areas. As one of the fastest developing fields in remote sensing applications, an unmanned aerial vehicle (UAV) can provide high-resolution data with a great potential for fast and accurate detection of inundated areas under complex urban landscapes. In this research, optical imagery was acquired by a mini-UAV to monitor the serious urban waterlogging in Yuyao, China. Texture features derived from gray-level co-occurrence matrix were included to increase the separability of different ground objects. A Random Forest classifier, consisting of 200 decision trees, was used to extract flooded areas in the spectral-textural feature space. Confusion matrix was used to assess the accuracy of the proposed method. Results indicated the following: (1) Random Forest showed good performance in urban flood mapping with an overall accuracy of 87.3% and a Kappa coefficient of 0.746; (2) the inclusion of texture features improved classification accuracy significantly; (3) Random Forest outperformed maximum likelihood and artificial neural network, and showed a similar performance to support vector machine. The results demonstrate that UAV can provide an ideal platform for urban flood monitoring and the proposed method shows great capability for the accurate extraction of inundated areas.
研究领域[WOS]	Water Resources
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:000353715100007
内容类型	期刊论文
源URL	[http://ir.ceode.ac.cn/handle/183411/38240]
专题	遥感与数字地球研究所_SCI/EI期刊论文_期刊论文
作者单位	1.[Feng, Quanlong 2.Liu, Jiantao 3.Gong, Jianhua] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China 4.[Gong, Jianhua] Zhejiang Chinese Acad Sci CAS Applicat Ctr Geoinf, Jiashan 314100, Peoples R China
推荐引用方式 GB/T 7714	Feng, Quanlong,Liu, Jiantao,Gong, Jianhua. Urban Flood Mapping Based on Unmanned Aerial Vehicle Remote Sensing and Random Forest Classifier-A Case of Yuyao, China[J]. WATER,2015,7(4).
APA	Feng, Quanlong,Liu, Jiantao,&Gong, Jianhua.(2015).Urban Flood Mapping Based on Unmanned Aerial Vehicle Remote Sensing and Random Forest Classifier-A Case of Yuyao, China.WATER,7(4).
MLA	Feng, Quanlong,et al."Urban Flood Mapping Based on Unmanned Aerial Vehicle Remote Sensing and Random Forest Classifier-A Case of Yuyao, China".WATER 7.4(2015).