首頁  >  科學研究  >  科研成果  >  正文
科研成果
沈煥鋒、曾超的論文在INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 刊出
發布時間:2019-12-18 10:41:00     發布者:易真     浏覽次數:

标題: 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)

來源出版物: INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH  : 16  : 21  文獻号: 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

語言: English

文獻類型: Article

作者關鍵詞: 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.

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

電子郵件地址: shenhf@whu.edu.cn; ZhouM@whu.edu.cn; litw@whu.edu.cn; zengchaozc@hotmail.com

影響因子:2.468


信息服務
學院網站教師登錄 學院辦公電話 學校信息門戶登錄

版權所有 © 88858cc永利官网
地址:湖北省武漢市珞喻路129号 郵編:430079 
電話:027-68778381,68778284,68778296 傳真:027-68778893    郵箱:sres@whu.edu.cn

Baidu
sogou