Back to Search
Start Over
Spatial Estimation of Regional PM 2.5 Concentrations with GWR Models Using PCA and RBF Interpolation Optimization.
- Source :
- Remote Sensing; Nov2022, Vol. 14 Issue 21, p5626, 26p
- Publication Year :
- 2022
-
Abstract
- In recent years, geographically weighted regression (GWR) models have been widely used to address the spatial heterogeneity and spatial autocorrelation of PM<subscript>2.5</subscript>, but these studies have not fully considered the effects of all potential variables on PM<subscript>2.5</subscript> variation and have rarely optimized the models for residuals. Therefore, we first propose a modified GWR model based on principal component analysis (PCA-GWR), then introduce five different spatial interpolation methods of radial basis functions to correct the residuals of the PCA-GWR model, and finally construct five combinations of residual correction models to estimate regional PM<subscript>2.5</subscript> concentrations. The results show that (1) the PCA-GWR model can fully consider the contributions of all potential explanatory variables to estimate PM<subscript>2.5</subscript> concentrations and minimize the multicollinearity among explanatory variables, and the PM<subscript>2.5</subscript> estimation accuracy and the fitting effect of the PCA-GWR model are better than the original GWR model. (2) All five residual correction combination models can better achieve the residual correction optimization of the PCA-GWR model, among which the PCA-GWR model corrected by Multiquadric Spline (MS) residual interpolation (PCA-GWRMS) has the most obvious accuracy improvement and more stable generalizability at different time scales. Therefore, the residual correction of PCA-GWR models using spatial interpolation methods is effective and feasible, and the results can provide references for regional PM<subscript>2.5</subscript> spatial estimation and spatiotemporal mapping. (3) The PM<subscript>2.5</subscript> concentrations in the study area are high in winter months (January, February, December) and low in summer months (June, July, August), and spatially, PM<subscript>2.5</subscript> concentrations show a distribution of high north and low south. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 14
- Issue :
- 21
- Database :
- Complementary Index
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 160219943
- Full Text :
- https://doi.org/10.3390/rs14215626