Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 2219-2223, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-2219-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 2219-2223, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-2219-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

URBAN EXPANSION MODELING APPROACH BASED ON MULTI-AGENT SYSTEM AND CELLULAR AUTOMATA

Y. N. Zeng1,2, M. M. Yu1,2, and S. N. Li3 Y. N. Zeng et al.
  • 1School of Geosciences and Info-physics, Central South University, Changsha, 410083, China
  • 2Center for Geomatics and Sustainabal Development Research, Central South University, Changsha, 410083, China
  • 3Department of Civil Engineering, Ryerson University, Toronto, Ontario, Canada

Keywords: Urban expansion, Modeling, Multi-agent system, Cellular automata

Abstract. Urban expansion is a land-use change process that transforms non-urban land into urban land. This process results in the loss of natural vegetation and increase in impervious surfaces. Urban expansion also alters the hydrologic cycling, atmospheric circulation, and nutrient cycling processes and generates enormous environmental and social impacts. Urban expansion monitoring and modeling are crucial to understanding urban expansion process, mechanism, and its environmental impacts, and predicting urban expansion in future scenarios. Therefore, it is important to study urban expansion monitoring and modeling approaches. We proposed to simulate urban expansion by combining CA and MAS model. The proposed urban expansion model based on MSA and CA was applied to a case study area of Changsha-Zhuzhou-Xiangtan urban agglomeration, China. The results show that this model can capture urban expansion with good adaptability. The Kappa coefficient of the simulation results is 0.75, which indicated that the combination of MAS and CA offered the better simulation result.