{"title":"Geographically and temporally weighted principal component analysis: a new approach for exploring air pollution non-stationarity in China, 2015–2019","authors":"Jiakuan Han, Xiaochen Kang, Yi Yang, Yinyin Zhang","doi":"10.1080/14498596.2022.2028270","DOIUrl":null,"url":null,"abstract":"ABSTRACT In spatiotemporal applications, geographically weighted principal component analysis (GWPCA) is commonly adopted to describe spatial heterogeneity. However, time effects are ignored in GWPCA. In this study, the temporal effect was incorporated into GWPCA . Thus, an extended model, geographically and temporally weighted principal component analysis (GTWPCA), was developed to simultaneously explore spatial and temporal non-stationarity. The GTWPCA was implemented using a case study of air pollution in China. The results mainly show that GTWPC1 (the local component one in GTWPCA) corresponds to a ‘winning group’ with constantly varying ‘winning’ variables adapted to the spatiotemporal non-stationary characteristics of air pollution in China.","PeriodicalId":50045,"journal":{"name":"Journal of Spatial Science","volume":"68 1","pages":"451 - 468"},"PeriodicalIF":1.0000,"publicationDate":"2022-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Spatial Science","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/14498596.2022.2028270","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GEOGRAPHY, PHYSICAL","Score":null,"Total":0}
引用次数: 1
Abstract
ABSTRACT In spatiotemporal applications, geographically weighted principal component analysis (GWPCA) is commonly adopted to describe spatial heterogeneity. However, time effects are ignored in GWPCA. In this study, the temporal effect was incorporated into GWPCA . Thus, an extended model, geographically and temporally weighted principal component analysis (GTWPCA), was developed to simultaneously explore spatial and temporal non-stationarity. The GTWPCA was implemented using a case study of air pollution in China. The results mainly show that GTWPC1 (the local component one in GTWPCA) corresponds to a ‘winning group’ with constantly varying ‘winning’ variables adapted to the spatiotemporal non-stationary characteristics of air pollution in China.
期刊介绍：
The Journal of Spatial Science publishes papers broadly across the spatial sciences including such areas as cartography, geodesy, geographic information science, hydrography, digital image analysis and photogrammetry, remote sensing, surveying and related areas. Two types of papers are published by he journal: Research Papers and Professional Papers.
Research Papers (including reviews) are peer-reviewed and must meet a minimum standard of making a contribution to the knowledge base of an area of the spatial sciences. This can be achieved through the empirical or theoretical contribution to knowledge that produces significant new outcomes.
It is anticipated that Professional Papers will be written by industry practitioners. Professional Papers describe innovative aspects of professional practise and applications that advance the development of the spatial industry.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
