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沈焕锋、曾超的论文在INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 刊出
发布时间:2019-12-18     发布者:易真         审核者:     浏览次数:

标题: Integration of Remote Sensing and Social Sensing Data in a Deep Learning Framework for Hourly Urban PM2.5 Mapping

作者: Shen, HF (Shen, Huanfeng); Zhou, M (Zhou, Man); Li, TW (Li, Tongwen); Zeng, C (Zeng, Chao)

来源出版物: INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH  : 16  : 21  文献号: 4102  DOI: 10.3390/ijerph16214102  出版年: NOV 1 2019  

摘要: Fine spatiotemporal mapping of PM2.5 concentration in urban areas is of great significance in epidemiologic research. However, both the diversity and the complex nonlinear relationships of PM2.5 influencing factors pose challenges for accurate mapping. To address these issues, we innovatively combined social sensing data with remote sensing data and other auxiliary variables, which can bring both natural and social factors into the modeling; meanwhile, we used a deep learning method to learn the nonlinear relationships. The geospatial analysis methods were applied to realize effective feature extraction of the social sensing data and a grid matching process was carried out to integrate the spatiotemporal multi-source heterogeneous data. Based on this research strategy, we finally generated hourly PM2.5 concentration data at a spatial resolution of 0.01 degrees. This method was successfully applied to the central urban area of Wuhan in China, which the optimal result of the 10-fold cross-validation R-2 was 0.832. Our work indicated that the real-time check-in and traffic index variables can improve both quantitative and mapping results. The mapping results could be potentially applied for urban environmental monitoring, pollution exposure assessment, and health risk research.

入藏号: WOS:000498842000048

PubMed ID: 31653059

语言: English

文献类型: Article

作者关键词: PM2.5; social sensing; remote sensing; feature extraction; deep learning

地址: [Shen, Huanfeng; Zhou, Man; Li, Tongwen; Zeng, Chao] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Hubei, Peoples R China.

[Shen, Huanfeng] Collaborat Innovat Ctr Geospatial Technol, Wuhan 430079, Hubei, Peoples R China.

[Shen, Huanfeng] Wuhan Univ, Key Lab Geog Informat Syst, Minist Educ, Wuhan 430079, Hubei, Peoples R China.

通讯作者地址: Zeng, C (通讯作者)Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Hubei, Peoples R China.

电子邮件地址: shenhf@whu.edu.cn; ZhouM@whu.edu.cn; litw@whu.edu.cn; zengchaozc@hotmail.com

影响因子:2.468