Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion

被引:527
作者
Arsanjani, Jamal Jokar [1 ]
Helbich, Marco [2 ]
Kainz, Wolfgang [1 ]
Boloorani, Ali Darvishi [3 ]
机构
[1] Univ Vienna, Dept Geog & Reg Res, Vienna, Austria
[2] Heidelberg Univ, Dept Geog, Heidelberg, Germany
[3] Univ Tehran, Dept Geog & Cartog, Tehran, Iran
关键词
Land use change; Logistic regression; Markov chain; Cellular automata; Tehran; LAND-COVER CHANGES; GROWTH; GIS; ASSOCIATION; VALIDATION; ATLANTA; FRINGE;
D O I
10.1016/j.jag.2011.12.014
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
This research analyses the suburban expansion in the metropolitan area of Tehran, Iran. A hybrid model consisting of logistic regression model, Markov chain (MC), and cellular automata (CA) was designed to improve the performance of the standard logistic regression model. Environmental and socio-economic variables dealing with urban sprawl were operationalised to create a probability surface of spatiotemporal states of built-up land use for the years 2006, 2016, and 2026. For validation, the model was evaluated by means of relative operating characteristic values for different sets of variables. The approach was calibrated for 2006 by cross comparing of actual and simulated land use maps. The achieved outcomes represent a match of 89% between simulated and actual maps of 2006, which was satisfactory to approve the calibration process. Thereafter, the calibrated hybrid approach was implemented for forthcoming years. Finally, future land use maps for 2016 and 2026 were predicted by means of this hybrid approach. The simulated maps illustrate a new wave of suburban development in the vicinity of Tehran at the western border of the metropolis during the next decades. Crown Copyright (C) 2011 Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:265 / 275
页数:11
相关论文
共 55 条
  • [21] Hill T., 2007, Statistics methods and applications
  • [22] Modeling urban growth in Atlanta using logistic regression
    Hu, Zhiyong
    Lo, C. P.
    [J]. COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 2007, 31 (06) : 667 - 688
  • [23] Support vector machines for urban growth modeling
    Huang, Bo
    Xie, Chenglin
    Tay, Richard
    [J]. GEOINFORMATICA, 2010, 14 (01) : 83 - 99
  • [24] Spatiotemporal analysis of rural-urban land conversion
    Huang, Bo
    Zhang, Li
    Wu, Bo
    [J]. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE, 2009, 23 (03) : 379 - 398
  • [25] Rural sustainability under threat in Zimbabwe - Simulation of future land use/cover changes in the Bindura district based on the Markov-cellular automata model
    Kamusoko, Courage
    Aniya, Masamu
    Adi, Bongo
    Manjoro, Munyaradzi
    [J]. APPLIED GEOGRAPHY, 2009, 29 (03) : 435 - 447
  • [26] Kaplan D., 2008, URBAN GEOGR
  • [27] Lambin E.F., 2006, Land-Use and Land-Cover Change, DOI [10.1007/3-540-32202-7, DOI 10.1007/3-540-32202-7]
  • [28] MEASUREMENT OF OBSERVER AGREEMENT FOR CATEGORICAL DATA
    LANDIS, JR
    KOCH, GG
    [J]. BIOMETRICS, 1977, 33 (01) : 159 - 174
  • [29] Liu Yan., 2008, Modelling urban development with geographical information systems and cellular automata
  • [30] Application of high-resolution thermal infrared remote sensing and GIS to assess the urban heat island effect
    Lo, CP
    Quattrochi, DA
    Luvall, JC
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 1997, 18 (02) : 287 - 304