PM2.5 Inversion over the Wuhan Metropolitan Area
Satellite–ground data fusion for spatially continuous pollution mapping
MATLAB R ArcGIS mixed-effects models · Mar. 2016 – Oct. 2017
National Undergraduate Innovation and Entrepreneurship Training Program, as a core team member. Advisor: Prof. Huanfeng Shen.
Ground-monitoring measurements, NASA MODIS/AOD satellite observations, and meteorological data were integrated and spatiotemporally matched across sources, then fed into a mixed-effects model for PM2.5 inversion, evaluated against baselines with cross-validation.
The output is a set of spatially continuous PM2.5 concentration maps across the Wuhan “1+8” metropolitan area, with analysis of temporal and regional pollution patterns. The national program passed final review with a Good rating.