Hailei Wang

Dr. Hailei Wang


Research Focus & Metrics

Academic Career Length

19Years (2008-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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28 October 2013 in Remote Sensing
Verified
Journal Article
Open access
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WLWenbo Li
Wenbo Li
ZDZhiqiang Du
Zhiqiang Du
Feng LingFeng Ling
Feng Ling
DZDongbo Zhou
Dongbo Zhou
HWHailei Wang
Hailei Wang
XZXiaoming Zhang
Xiaoming Zhang
Remote sensing has more advantages than the traditional methods of land surface water (LSW) mapping because it is a low-cost, reliable information source that is capable of making high-frequency and repeatable observations. The normalized difference water indexes (NDWIs), calculated from various band combinations (green, near-infrared (NIR), or shortwave-infrared (SWIR)), have been successfully applied to LSW mapping. In fact, new NDWIs will become available when Advanced Land Imager (ALI) data are used as the ALI sensor provides one green band (Band 4), two NIR bands (Bands 6 and 7), and three SWIR bands (Bands 8, 9, and 10). Thus, selecting the optimal band or combination of bands is critical when ALI data are employed to map LSW using NDWI. The purpose of this paper is to find the best performing NDWI model of the ALI data in LSW map. In this study, eleven NDWI models based on ALI, Thematic Mapper (TM), and Enhanced Thematic Mapper Plus (ETM+) data were compared to assess the performance of ALI data in LSW mapping, at three different study sites in the Yangtze River Basin, China. The contrast method, Otsu method, and confusion matrix were calculated to evaluate the accuracies of the LSW maps. The accuracies of LSW maps derived from eleven NDWI models showed that five NDWI models of the ALI sensor have more than an overall accuracy of 91% with a Kappa coefficient of 0.78 of LSW maps at three test sites. In addition, the NDWI model, calculated from the green (Band 4: 0.525–0.605 μm) and SWIR (Band 9: 1.550–1.750 μm) bands of the ALI sensor, namely NDWIA4,9, was shown to have the highest LSW mapping accuracy, more than the other NDWI models. Therefore, the NDWIA4,9 is the best indicator for LSW mapping of the ALI sensor. It can be used for mapping LSW with high accuracy.

1 January 2017 in Journal of Hazardous Materials
Verified
Journal Article
Closed access
HWHailei Wang
Hailei Wang
LPLi Ping
Li Ping
WYWang Ying
Wang Ying
LLLiu Lei
Liu Lei
YJYao Jianming
Yao Jianming

19 January 2019 in Applied Microbiology and Biotechnology
Verified
Journal Article
Closed access
KZKun Zhang
Kun Zhang
XLXinxin Lu
Xinxin Lu
YLYi Li
Yi Li
XJXiaobing Jiang
Xiaobing Jiang
LLLei Liu
Lei Liu
HWHailei Wang
Hailei Wang

1 January 2011 in Enzyme and Microbial Technology
Verified
Journal Article
Closed access
PLPing Li
Ping Li
HWHailei Wang
Hailei Wang
GLGuosheng Liu
Guosheng Liu
XLXin Li
Xin Li
JYJianming Yao
Jianming Yao

1 May 2011 in Bioresource Technology
Verified
Journal Article
Closed access
HWHailei Wang
Hailei Wang
RZRen Zhifang
Ren Zhifang
LPLi Ping
Li Ping
GYGu Yanchang
Gu Yanchang
LGLiu Guosheng
Liu Guosheng
YJYao Jianming
Yao Jianming

31 August 2022 in Microbiology Spectrum
Verified
Journal Article
Open access
MJMenglu Jin
Menglu Jin
JCJingchao Chen
Jingchao Chen
XZXueyang Zhao
Xueyang Zhao
GHGuoru Hu
Guoru Hu
HWHailei Wang
Hailei Wang
WCWeihua Chen
Weihua Chen
Pathogenic strains of Escherichia coli are responsible for 0.8 million deaths per year and together ranked the first among all pathogenic species. Here, we obtained, for the first time, an engineered phage, Eλ, that could specifically and efficiently eliminate EHEC, one of the most common and often lethal pathogens that can spread from person to person.