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- W2762022704 abstract "Air quality has the strong regional characteristics, and the land use type can reflect human activities in the area to some extent. In order to explore the spatial relationships between air quality indicators (PM 2.5 , PM 10 , O 3 , SO 2 , NO 2 , CO) and land use indicators ( tree, grass, farm, water and building proportion), the ordinary least squares (OLS) and geographically weighted regression (GWR) models are established and tested by comparing R 2 and AICc (Akaika Information Criterion corrected) of the models. The Moran's I statistics on the residuals from OLS and GWR models shows that the GWR models can be a good deal with the spatial autocorrelation. Meanwhile local parameters at different locations from GWR models can be good performance in the spatial heterogeneity of the air quality and land use, providing a scientific basis for rational and effective regional governance." @default.
- W2762022704 created "2017-10-20" @default.
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- W2762022704 date "2017-03-01" @default.
- W2762022704 modified "2023-09-23" @default.
- W2762022704 title "Research on Spatial Correlation Between Air Quality and Land Use Based on GWR Models" @default.
- W2762022704 hasPublicationYear "2017" @default.
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