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)

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)

Highly accurate data on the spatial distribution of ambient fine particulate matter (<2.5 μm: PM2.5) is currently quite limited in China. By introducing NO2 and Enhanced Vegetation Index (EVI) into the Geographically Weighted Regression (GWR) model, a newly developed GWR model combined with a...

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Bibliographic Details
Main Authors: Tianhao Zhang, Wei Gong, Wei Wang, Yuxi Ji, Zhongmin Zhu, Yusi Huang
Format: Article
Language:English
Published: MDPI AG 2016-12-01
Series:International Journal of Environmental Research and Public Health
Subjects:
nationwide ambient PM2.5
MODIS (Moderate Resolution Imaging Spectroradiometer) AOD
satellite-derived NO2 column density
enhanced vegetation index
geographically weighted regression
Online Access:http://www.mdpi.com/1660-4601/13/12/1215

Internet

http://www.mdpi.com/1660-4601/13/12/1215

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