Huan Jing Ke Xue 2020 May;41(5):2057-2065
College of Geography and Tourism, Anhui Normal University, Wuhu 241002, China.
In this paper, aerosol optical depth (AOD), elevation (DEM), annual precipitation (PRE), annual average temperature (TEM), annual average wind speed (WS), population density (POP), gross domestic product density (GDP), and normalized difference vegetation index (NDVI) were selected as factors influencing PM concentration. The random forest model, order of feature importance, and partial dependency plots were applied to investigate these factors and their regional differences in PM spatial pattern. The results showed that:① The random forest model was more accurate than multiple regression, generalized additive, and back propagation neural network models in estimating PM concentration, which can be applied to quantifying PM influencing factors. Read More