Zhang, T.; Gong, W.; Wang, W.; Ji, Y.; Zhu, Z.; Huang, Y.
Ground Level PM2.5 Estimates over China Using Satellite-Based Geographically Weighted Regression (GWR) Models Are Improved by Including NO2 and Enhanced Vegetation Index (EVI). Int. J. Environ. Res. Public Health 2016, 13, 1215.
https://doi.org/10.3390/ijerph13121215
AMA Style
Zhang T, Gong W, Wang W, Ji Y, Zhu Z, Huang Y.
Ground Level PM2.5 Estimates over China Using Satellite-Based Geographically Weighted Regression (GWR) Models Are Improved by Including NO2 and Enhanced Vegetation Index (EVI). International Journal of Environmental Research and Public Health. 2016; 13(12):1215.
https://doi.org/10.3390/ijerph13121215
Chicago/Turabian Style
Zhang, Tianhao, Wei Gong, Wei Wang, Yuxi Ji, Zhongmin Zhu, and Yusi Huang.
2016. "Ground Level PM2.5 Estimates over China Using Satellite-Based Geographically Weighted Regression (GWR) Models Are Improved by Including NO2 and Enhanced Vegetation Index (EVI)" International Journal of Environmental Research and Public Health 13, no. 12: 1215.
https://doi.org/10.3390/ijerph13121215
APA Style
Zhang, T., Gong, W., Wang, W., Ji, Y., Zhu, Z., & Huang, Y.
(2016). Ground Level PM2.5 Estimates over China Using Satellite-Based Geographically Weighted Regression (GWR) Models Are Improved by Including NO2 and Enhanced Vegetation Index (EVI). International Journal of Environmental Research and Public Health, 13(12), 1215.
https://doi.org/10.3390/ijerph13121215
