气候变化领域集成服务门户(CCPortal): Analyzing urban forest coverage variation in Guangzhou-Foshan region using factorial analysis based multivariate statistical prediction models

CCPortal

DOI	10.1016/j.foreco.2018.09.010
	Analyzing urban forest coverage variation in Guangzhou-Foshan region using factorial analysis based multivariate statistical prediction models
	Wang J.; Li Y.P.; Sun J.; Lin Y.T.
发表日期	2019
ISSN	0378-1127
起始页码	121
结束页码	131
卷号	432
英文摘要	In this study, factorial analysis based multivariate statistical prediction (FAMSP) models are developed to analyze the variation of urban forest coverage area (FCA). Through incorporating techniques of multivariate linear regression (MLR), multivariate quantile regression (MQR), stepwise cluster analysis (SCA), and support vector machine (SVM) within factorial analysis framework, four FAMSP models are advanced. The developed models have advantages in reflecting the complex relationships (e.g., linear/nonlinear and/or continuous/discrete) among urban FCA, human activity, and natural factors. Factorial analysis is used for exploring the interactions among multiple factors on FCA variation. The FAMSP models are also applied to Guangzhou-Foshan region for illustrating their applicabilities in FCA variation analysis. Results reveal that different multivariate statistical prediction methods lead to different performances for FCA variation. SCA and SVM can get more satisfactory performances than MLR and MQR due to their superior ability in characterizing the nonlinear features of FCA variation. Population is one of the key drivers for FCA variation due to its high sensitivity to timber consumption and stock; population would affect the regional climatological condition (e.g., precipitation), which consequently alters forest growth. The factors of Guangzhou would primarily impact regional FCA variation due to its higher population and higher timber demand than those in Foshan. These findings are helpful for the urban forest sustainable development and timber resources management. © 2018 Elsevier B.V.
英文关键词	Factorial analysis; Forest coverage area; Human activity; Interaction; Multivariate statistical prediction
语种	英语
scopus关键词	Cluster analysis; Forecasting; Forestry; Image resolution; Maxwell equations; Population statistics; Sensitivity analysis; Support vector machines; Timber; Coverage area; Factorial analysis; Human activities; Interaction; Statistical prediction; Multivariant analysis; climate effect; cluster analysis; forest cover; growth response; human activity; prediction; regression analysis; support vector machine; sustainable forestry; timber harvesting; urban ecosystem; Analysis; Covering Power; Forecasts; Forestry; Impact; Lead; Management; Models; China; Foshan; Guangdong; Guangzhou
来源期刊	Forest Ecology and Management
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156405
作者单位	School of Environment, Beijing Normal University, Beijing, 100875, China; Sina-Canada Energy and Environmental Research Center, North China Electric Power University, Beijing, 102206, China; Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, Sask S4S 7H9, Canada
推荐引用方式 GB/T 7714	Wang J.,Li Y.P.,Sun J.,et al. Analyzing urban forest coverage variation in Guangzhou-Foshan region using factorial analysis based multivariate statistical prediction models[J],2019,432.
APA	Wang J.,Li Y.P.,Sun J.,&Lin Y.T..(2019).Analyzing urban forest coverage variation in Guangzhou-Foshan region using factorial analysis based multivariate statistical prediction models.Forest Ecology and Management,432.
MLA	Wang J.,et al."Analyzing urban forest coverage variation in Guangzhou-Foshan region using factorial analysis based multivariate statistical prediction models".Forest Ecology and Management 432(2019).