Improving Geographically Weighted Regression Considering Directional Nonstationary for Ground-Level PM<sub>2.5</sub> Estimation

Improving Geographically Weighted Regression Considering Directional Nonstationary for Ground-Level PM<sub>2.5</sub> Estimation

The increase in atmospheric pollution dominated by particles with an aerodynamic diameter smaller than 2.5 μm (PM<sub>2.5</sub>) has become one of the most serious environmental hazards worldwide. The geographically weighted regression (GWR) model is a vital method to estimate the spatia...

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Bibliographic Details
Main Authors: Weihao Xuan, Feng Zhang, Hongye Zhou, Zhenhong Du, Renyi Liu
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:ISPRS International Journal of Geo-Information
Subjects:
GWR
non-stationarity
wind
PM<sub>2.5</sub> concentrations
locally varying anisotropy
Online Access:https://www.mdpi.com/2220-9964/10/6/413

Internet

https://www.mdpi.com/2220-9964/10/6/413

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