Integration of Remote Sensing and Social Sensing Data in a Deep Learning Framework for Hourly Urban PM 2.5 Mapping
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- Tianhao Zhang & Wei Gong & Wei Wang & Yuxi Ji & Zhongmin Zhu & Yusi Huang, 2016. "Ground Level PM 2.5 Estimates over China Using Satellite-Based Geographically Weighted Regression (GWR) Models Are Improved by Including NO 2 and Enhanced Vegetation Index (EVI)," IJERPH, MDPI, vol. 13(12), pages 1-12, December.
- Qianqian Yang & Qiangqiang Yuan & Tongwen Li & Huanfeng Shen & Liangpei Zhang, 2017. "The Relationships between PM 2.5 and Meteorological Factors in China: Seasonal and Regional Variations," IJERPH, MDPI, vol. 14(12), pages 1-19, December.
- Li Tian & Wei Hou & Jiquan Chen & Chaonan Chen & Xiaojun Pan, 2018. "Spatiotemporal Changes in PM 2.5 and Their Relationships with Land-Use and People in Hangzhou," IJERPH, MDPI, vol. 15(10), pages 1-14, October.
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Keywords
PM2.5; social sensing; remote sensing; feature extraction; deep learning;All these keywords.
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