Identifying the urban-rural fringe using wavelet transform and kernel density estimation: A case study in Beijing City, China. (September 2016)

• Record Type: Journal Article
• Authors: Peng, Jian; Zhao, Shiquan; Liu, Yanxu; Tian, Lu
• Is Part Of: Environmental modelling & software. Volume 83(2016:Sep.)
• Page Start: 286
• Page End: 302
• Publication Date: 2016-09
• Subjects: Urban-rural fringe -- Spatial continuous wavelet transform -- Kernel density estimation -- Land use degree index -- Beijing City; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2016.06.007
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: The urban-rural fringe, known as the region located between the urban and rural areas, is the frontier of urban expansion against rural reservations. Identifying this particular region precisely, which was usually simplified by researchers, is the most important prerequisite in studies related to urban-rural patterns. In this study, we proposed a new model, combining wavelet transform and kernel density estimation, to identify the urban-rural fringe based on land use data. After testing the model using Beijing City as a case study, it is proved that the model is able to delineate the boundaries of urban-rural fringe precisely with respect to different landscape patterns at different regions (central urban area, urban-rural fringe area, and outer rural area). Furthermore, due to the advantage of the self-adaptive-bandwidth kernel density estimation, the model can also distinguish some of the satellite towns from the central urban area and outer rural area with the boundaries of urban-rural fringe. Highlights: A quantitative model is proposed to identify urban-rural fringe. Mutation points can be detected automatically using spatial wavelet transform. The density surface of the mutational points is constructed by modified KDE. Noise mutation points are eliminated by slicing the density surface. Urban-rural fringe in Beijing City are precisely identified based on land use map.