科研成果
博士生李同文的论文在GEOPHYSICAL RESEARCH LETTERS刊出
发布时间:2018-01-18 17:19:40     发布者:yz     浏览次数:

标题:Estimating Ground-Level PM2.5 by Fusing Satellite and Station Observations: A Geo-Intelligent Deep Learning Approach

作者: Li, TW (Li, Tongwen); Shen, HF (Shen, Huanfeng); Yuan, QQ (Yuan, Qiangqiang); Zhang, XC (Zhang, Xuechen); Zhang, LP (Zhang, Liangpei)
来源出版物:GEOPHYSICAL RESEARCH LETTERS 卷:44 期:23 页码:   11985-11993    DOI:10.1002/2017GL075710      出版年:  DEC 16 2017
摘要:Fusing satellite observations and station measurements to estimate ground-level PM2.5 is promising for monitoring PM2.5 pollution. A geo-intelligent approach, which incorporates geographical correlation into an intelligent deep learning architecture, is developed to estimate PM2.5. Specifically, it considers geographical distance and spatiotemporally correlated PM2.5 in a deep belief network (denoted as Geoi-DBN). Geoi-DBN can capture the essential features associated with PM2.5 from latent factors. It was trained and tested with data from China in 2015. The results show that Geoi-DBN performs significantly better than the traditional neural network. The out-of-sample cross-validation R-2 increases from 0.42 to 0.88, and RMSE decreases from 29.96 to 13.03 mu g/m(3). On the basis of the derived PM(2.)5 distribution, it is predicted that over 80% of the Chinese population live in areas with an annual mean PM2.5 of greater than 35 mu g/m(3). This study provides a new perspective for air pollution monitoring in large geographic regions.
入藏号:WOS:000419102400035
文献类型:Article
语种:English
扩展关键词: AEROSOL OPTICAL DEPTH; REMOTE-SENSING DATA; MULTIANGLE IMAGING SPECTRORADIOMETER; FINE PARTICULATE MATTER; AIR-QUALITY; EXPOSURE ASSESSMENT; UNITED-STATES; CHINA; POLLUTION; MODIS
通讯作者地址:Shen, HF (reprint author), Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Hubei, Peoples R China.
Shen, HF (reprint author), Collaborat Innovat Ctr Geospatial Technol, Wuhan, Hubei, Peoples R China.
Shen, HF (reprint author), Wuhan Univ, Key Lab Geog Informat Syst, Minist Educ, Wuhan, Hubei, Peoples R China.
电子邮件地址:shenhf@whu.edu.cn
地址:
[Li, Tongwen; Shen, Huanfeng; Zhang, Xuechen] Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Hubei, Peoples R China. 
[Shen, Huanfeng; Yuan, Qiangqiang; Zhang, Liangpei] Collaborat Innovat Ctr Geospatial Technol, Wuhan, Hubei, Peoples R China. 
[Shen, Huanfeng] Wuhan Univ, Key Lab Geog Informat Syst, Minist Educ, Wuhan, Hubei, Peoples R China. 
[Yuan, Qiangqiang] Wuhan Univ, Sch Geodesy & Geomat, Wuhan, Hubei, Peoples R China. 
[Zhang, Liangpei] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan, Hubei, Peoples R China.
影响因子:4.253
 

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