General Introduction

  • Jamal Jokar Arsanjani
Part of the Springer Theses book series (Springer Theses)


This chapter introduces the agenda of this research which intends to deal with the most popular methods regarding dynamic land use/cover change studies, specifically focusing on Geosimulation and a geospatial agent-based modelling domain. The chapter identifies existing problems in the topic area; addressees research questions and proposed motivations throughout this dissertation. It also comprises assumed hypotheses, intended objectives, and the planned research methodology within this work. The chapter will conclude by addressing the structure and organisation of this thesis.


Cellular Automaton Urban Expansion Markov Chain Model Cellular Automaton Model Land Change 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Benenson I, Torrens PM (2004) Geosimulation: automata-based modeling of urban phenomena. Wiley, New YorkCrossRefGoogle Scholar
  2. Crooks AT (2006) Exploring cities using agent-based models and GIS. In Proceedings of the agent conference on social agents: results and prospects, University of Chicago and Argonne National Laboratory, Chicago, 2006Google Scholar
  3. Ellis E, Pontius RG Jr (2006) Land-use and land-cover change—encyclopedia of earth.
  4. Hatna E, Benenson I (2007) Building a city in vitro: the experiment and the simulation model. Environ Planning B: Planning Des 34(4):687–707CrossRefGoogle Scholar
  5. Huang B, Zhang L, Wu B (2009) Spatiotemporal analysis of rural-urban land conversion. Int J Geog Inf Sci 23(3):379–398CrossRefGoogle Scholar
  6. Iranian National Statistics Center (2006)
  7. Kerridge J, Hine J, Wigan M (2001) Agent-based modelling of pedestrian movements: the questions that need to be asked and answered. Environ Planning B 28(3):327–342CrossRefGoogle Scholar
  8. Lambin EF, Geist HJ (2006) Land-use and land-cover change: local processes and global impacts. Springer, BerlinGoogle Scholar
  9. Ljubovic V (2009) Traffic simulation using agent-based models. In information, communication and automation technologies, 2009. ICAT 2009. 22nd international symposium on information, communication and automation technologies, pp 1–6, 2009Google Scholar
  10. Michopoulos J, Farhat C, Houstis E, Tsompanopoulou P, Zhang H, Gullaud T (2004) Agent-based simulation of data-driven fire propagation dynamics. In: Michopoulos J (ed) Agent-based simulation of data-driven fire propagation dynamics. Computational Science-ICCS 2004, pp 732–739Google Scholar
  11. Pontius RG Jr, Chen H (2006) GEOMOD modeling, IDRISI Andes help contents. Massachusetts Clark University, Worcester, MA Google Scholar
  12. Rana S, Sharma J (2006) Frontiers of geographic information technology, 1st edn. Springer, BerlinCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg  2012

Authors and Affiliations

  1. 1.Department of Geography and Regional ResearchUniversity of ViennaViennaAustria

Personalised recommendations