A geographically weighted regression model augmented by Geodetector analysis and principal component analysis for the spatial distribution of PM2.5-Reference-Cited by-同舟云学术

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A geographically weighted regression model augmented by Geodetector analysis and principal component analysis for the spatial distribution of PM2.5

Published:2020-05 Issue: Volume:56 Page:102106
ISSN:2210-6707
Container-title:Sustainable Cities and Society
language:en
Short-container-title:Sustainable Cities and Society

Author:

Zhao Rui,Zhan Liping,Yao Mingxing,Yang Linchuan

Funder

National Natural Science Foundation of China

Sichuan Provincial Key Technology Support

Sichuan Province Circular Economy Research Center Fund

Publisher

Elsevier BV

Subject

Transportation,Renewable Energy, Sustainability and the Environment,Civil and Structural Engineering,Geography, Planning and Development

Reference81 articles.

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2. Procurement innovation for a circular economy of construction and demolition waste: lessons learnt from Suzhou, China;Bao;Waste Management,2019

3. Geographically weighted regression: A method for exploring spatial nonstationarity;Brunsdon;Geographical Analysis,1996

4. Optimal discretization for geographical detectors-based risk assessment;Cao;GIScience & Remote Sensing,2013

5. Detecting the causality influence of individual meteorological factors on local PM2.5 concentration in the Jing-Jin-Ji region;Chen;Scientific Reports,2017

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