Simulation and analysis of urban growth scenarios for the Greater Shanghai Area, China

This research investigates the potential of an integrated Markov chain analysis and cellular automata model to better understand the dynamics of Shanghai's urban growth. The model utilizes detailed land cover categories to simulate and assess landscape changes under three different scenarios, i.e., baseline, Service Oriented Center, and Manufacturing Dominant Center scenarios. In the study, multi-temporal land use datasets, derived from remotely-sensed images from 1995, 2000, and 2005, were used for simulation and validation. Urban growth patterns and processes were then analyzed and compared with the aid of landscape metrics. This research represents the first scenario-based simulations of the future growth of Shanghai, and is one of the few studies to use landscape metrics to analyze urban scenario-based simulation results with detailed land use categories. The results indicate that the future expansion of both high-density and low-density residential/commercial zones is always located around existing built-up urban areas or along existing transportation lines. In contrast to the baseline and Service Oriented Center scenarios, industrial land under the Manufacturing Dominant Center scenario in 2015 and 2025 will form industrial parks or industrial belts along the transportation channels from Shanghai to Nanjing and Hangzhou. The study's approach, which combines scenario-based urban simulation modeling and landscape metrics, is shown to be effective in representing, understanding, and predicting the spatial-temporal dynamics and patterns of urban evolution, including urban expansion trends. (C) 2010 Elsevier Ltd. All rights reserved.

[1]  Thomas L. Saaty,et al.  Multicriteria Decision Making: The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation , 1990 .

[2]  Anthony Gar-On Yeh,et al.  Analyzing spatial restructuring of land use patterns in a fast growing region using remote sensing and GIS , 2004 .

[3]  F. Wu,et al.  Simulation of Land Development through the Integration of Cellular Automata and Multicriteria Evaluation , 1998 .

[4]  P. Shi,et al.  Modelling dynamic urban expansion processes incorporating a potential model with cellular automata , 2008 .

[5]  N. Grimm,et al.  Global Change and the Ecology of Cities , 2008, Science.

[6]  Nigel Waters,et al.  Modeling Urban Land Use Change and Urban Sprawl: Calgary, Alberta, Canada , 2007 .

[7]  L. Hubert‐Moy,et al.  MODELING AND PROJECTING LAND-USE AND LAND-COVER CHANGES WITH A CELLULAR AUTOMATON IN CONSIDERING LANDSCAPE TRAJECTORIES: AN IMPROVEMENT FOR SIMULATION OF PLAUSIBLE FUTURE STATES , 2005 .

[8]  Anthony Gar-On Yeh,et al.  Neural-network-based cellular automata for simulating multiple land use changes using GIS , 2002, Int. J. Geogr. Inf. Sci..

[9]  Y. Hayashi,et al.  Application of an integrated system dynamics and cellular automata model for urban growth assessment: A case study of Shanghai, China , 2009 .

[10]  Yang Zhong,et al.  Urbanization, land use, and water quality in Shanghai. 1947-1996. , 2003, Environment international.

[11]  Martin Herold,et al.  The spatiotemporal form of urban growth: measurement, analysis and modeling , 2003 .

[12]  Joachim Karlsson,et al.  A Cost-Value Approach for Prioritizing Requirements , 1997, IEEE Softw..

[13]  J. Diamond,et al.  China's environment in a globalizing world , 2005, Nature.

[14]  Wei Ji,et al.  Characterizing urban sprawl using multi-stage remote sensing images and landscape metrics , 2006, Comput. Environ. Urban Syst..

[15]  M. Herold,et al.  The Use of Remote Sensing and Landscape Metrics to Describe Structures and Changes in Urban Land Uses , 2002 .

[16]  Eastman J. Ronald,et al.  RASTER PROCEDURES FOR MULTI-CRITERIA/MULTI-OBJECTIVE DECISIONS , 1995 .

[17]  Michael P. Prisloe,et al.  Development of a geospatial model to quantify, describe and map urban growth , 2003 .

[18]  W. Solecki,et al.  Downscaling climate change scenarios in an urban land use change model. , 2004, Journal of environmental management.

[19]  Norio Okada,et al.  Modeling urban expansion scenarios by coupling cellular automata model and system dynamic model in Beijing, China , 2006 .

[20]  S. Geertman,et al.  Spatial externalities, neighbourhood rules and CA land-use modelling , 2008 .

[21]  H. Tian,et al.  China's changing landscape during the 1990s: Large‐scale land transformations estimated with satellite data , 2005 .

[22]  H. Tian,et al.  Spatial and temporal patterns of China's cropland during 1990¿2000: An analysis based on Landsat TM data , 2005 .

[23]  R. Lathrop,et al.  Modeling the Ecological Consequences of Land-Use Policies in an Urbanizing Region , 2005, Environmental management.

[24]  John Robinson,et al.  The problem of the future: sustainability science and scenario analysis , 2004 .

[25]  C. Lavalle,et al.  Modelling dynamic spatial processes: simulation of urban future scenarios through cellular automata , 2003 .

[26]  Xia Li,et al.  Cellular automata for simulating land use changes based on support vector machines , 2008, Comput. Geosci..

[27]  P. Torrens,et al.  Geosimulation: Automata-based modeling of urban phenomena , 2004 .

[28]  Yunpeng Wang,et al.  Temporal and spatial change detecting (1998–2003) and predicting of land use and land cover in Core corridor of Pearl River Delta (China) by using TM and ETM+ images , 2008, Environmental monitoring and assessment.

[29]  Michael P. Johnson Environmental Impacts of Urban Sprawl: A Survey of the Literature and Proposed Research Agenda , 2001 .

[30]  Keith C. Clarke,et al.  Loose-Coupling a Cellular Automaton Model and GIS: Long-Term Urban Growth Prediction for San Francisco and Washington/Baltimore , 1998, Int. J. Geogr. Inf. Sci..

[31]  Roger White,et al.  The Use of Constrained Cellular Automata for High-Resolution Modelling of Urban Land-Use Dynamics , 1997 .

[32]  Xia Li,et al.  Sustainable Land Development Model for Rapid Growth Areas Using GIS , 1998, Int. J. Geogr. Inf. Sci..

[33]  K. McGarigal,et al.  FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. , 1995 .

[34]  Keith C. Clarke,et al.  A Self-Modifying Cellular Automaton Model of Historical Urbanization in the San Francisco Bay Area , 1997 .

[35]  K. Seto,et al.  Quantifying Spatiotemporal Patterns of Urban Land-use Change in Four Cities of China with Time Series Landscape Metrics , 2005, Landscape Ecology.

[36]  P. Gong,et al.  Assessment of the Urban Development Plan of Beijing by Using a CA-Based Urban Growth Model , 2002 .

[37]  Xia Li,et al.  Simulating complex urban development using kernel-based non-linear cellular automata , 2008 .

[38]  S. Goetz,et al.  Using the Sleuth Urban Growth Model to Simulate the Impacts of Future Policy Scenarios on Urban Land Use in the Baltimore-Washington Metropolitan Area , 2004 .

[39]  R. White,et al.  High-resolution integrated modelling of the spatial dynamics of urban and regional systems , 2000 .

[40]  Mark D. Gross,et al.  EML: a modeling environment for exploring landscape dynamics , 1994 .

[41]  Richard E. Klosterman,et al.  The What If? Collaborative Planning Support System , 1999 .