Simulating urban growth processes incorporating a potential model with spatial metrics

Urbanization is one phenomena that drives land use pattern change. Persistent rapid urbanization is associated with depletion of natural resources and worsening conditions in the urban environment. Monitoring urban development is, therefore, an absolute necessity in order to assure sustainable cities in the future. The main objective of this paper is to develop and apply an urban growth potential model incorporating spatial metrics. The model has been tested in Jinan City, China. Firstly, two satellite images (1989 and 2004 SPOT) were used to extract the land-cover. A general land use spatial pattern analysis, based on landscape metrics and a transformation matrix analysis, was conducted. Secondly, a moving window method was used to identify and capture the urbanization process through the PLAND landscape metric. The remote satellite data have been further processed: first to produce an initial state of the land-cover surface, and second to perform a time-series analysis and to assess the potential accuracy of the model application. In the second step, the calibrated model was used to predict the location of the urban growth over 16 years (2004–2020). The results indicated there will be a significant land use change until 2020. However, the spatial distribution of the potential growth areas is not homogenous. The study has confirmed the usefulness of a growth potential model incorporating the moving window method to predict urban growth trends and examining the impacts of urban development on natural resources. The results can provide decision support documents for urban planners and stakeholders with spatially explicit information for future planning and monitoring plans.

[1]  Jianguo Wu,et al.  A gradient analysis of urban landscape pattern: a case study from the Phoenix metropolitan region, Arizona, USA , 2004, Landscape Ecology.

[2]  R. Tateishi,et al.  Evaluating urban expansion and land use change in Shijiazhuang, China, by using GIS and remote sensing , 2006 .

[3]  J. Qi,et al.  Spatio-temporal dynamics and evolution of land use change and landscape pattern in response to rapid urbanization , 2009 .

[4]  Christiane Weber,et al.  Urbanization pressure and modeling of urban growth: example of the Tunis Metropolitan Area , 2003 .

[5]  Michael Batty,et al.  Urban Modeling in Computer-Graphic and Geographic Information System Environments , 1992 .

[6]  Paul A. Longley,et al.  Geographical Information Systems: will developments in urban remote sensing and GIS lead to ‘better’ urban geography? , 2002 .

[7]  R. Meaille,et al.  Using geographical information system and satellite imagery within a numerical simulation of regional urban growth , 1990, Int. J. Geogr. Inf. Sci..

[8]  B. Turner,et al.  Changes in land use and land cover: a global perspective , 1995 .

[9]  Y. Murayama,et al.  Urban mapping, accuracy, & image classification: A comparison of multiple approaches in Tsukuba City, Japan , 2009 .

[10]  M. Wegener.  Operational Urban Models State of the Art , 1994 .

[11]  Jochen A. G. Jaeger,et al.  Suitability criteria for measures of urban sprawl , 2010 .

[12]  Keith C. Clarke,et al.  The role of spatial metrics in the analysis and modeling of urban land use change , 2005, Comput. Environ. Urban Syst..

[13]  Duncan Cavens,et al.  Urban permeation of landscapes and sprawl per capita: New measures of urban sprawl , 2010 .

[14]  Michael Batty,et al.  Traffic, urban growth and suburban sprawl , 2003 .

[15]  Michael Batty,et al.  Predicting Temporal Pattern in Urban Development from Remote Imagery , 2001 .

[16]  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 .

[17]  Benoit B. Mandelbrot,et al.  Fractal Geometry of Nature , 1984 .

[18]  M. Ramsey,et al.  Monitoring urban land cover change: An expert system approach to land cover classification of semiarid to arid urban centers , 2001 .

[19]  Arza Churchman,et al.  Disentangling the Concept of Density , 1999 .

[20]  J. Wickham,et al.  A Landscape Atlas of the Chesapeake Bay Watershed. , 1995 .

[21]  MA Shu-hong.  Research on the development of satellite cities oriented on potential model and economic power theory , 2008 .

[22]  Shoufan Fang,et al.  The impact of interactions in spatial simulation of the dynamics of urban sprawl , 2005 .

[23]  T. Ramachandra,et al.  Urban sprawl: metrics, dynamics and modelling using GIS , 2004 .

[24]  J. Swenson,et al.  The effects of future urban development on habitat fragmentation in the Santa Monica Mountains , 2000, Landscape Ecology.

[25]  Marvin E. Bauer,et al.  Integrating Contextual Information with per-Pixel Classification for Improved Land Cover Classification , 2000 .

[26]  Virginia H. Dale,et al.  Patterns and impacts of deforestation in Rondônia, Brazil , 1997 .

[27]  G. K. Heilig,et al.  Neglected Dimensions of Global Land-Use Change: Reflections and Data , 1994 .

[28]  Tanja Tötzer,et al.  Modeling growth and densification processes in sub-urban regions – simulation of landscape transition with spatial agents , 2005 .

[29]  Yuan Zhang,et al.  Evaluating the effectiveness of landscape metrics in quantifying spatial patterns , 2010 .

[30]  J. Palmer.  Using spatial metrics to predict scenic perception in a changing landscape: Dennis, Massachusetts , 2004 .

[31]  Christiane Weber.  Interaction model application for urban planning , 2003 .

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

[33]  Xia Li,et al.  A new landscape index for quantifying urban expansion using multi-temporal remotely sensed data , 2010, Landscape Ecology.

[34]  M. K. Trani,et al.  Key Elements of Landscape Pattern Measures , 1999, Environmental management.

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

[36]  Christiane Weber,et al.  Processus de croissance et limites urbaines , 1997 .

[37]  Arnold K. Bregt,et al.  Relationship between landscape structure metrics and wetland nutrient retention function: A case study of Liaohe Delta, China , 2005 .

[38]  Executive Summary.  World Urbanization Prospects: The 2018 Revision , 2019 .

[39]  L. Jansen,et al.  Analysis of land-cover/use change dynamics in Manica Province in Mozambique in a period of transition (1990–2004) , 2008 .

[40]  A. Frenkel.  The potential effect of national growth-management policy on urban sprawl and the depletion of open spaces and farmland , 2004 .

[41]  J. W. Bruce,et al.  The causes of land-use and land-cover change: moving beyond the myths , 2001 .

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

[43]  F. F. Yang,et al.  Services and metropolitan development in China: the case of Guangzhou , 2004 .

[44]  Fulong Wu.  An Empirical Model of Intrametropolitan Land-Use Changes in a Chinese City , 1998 .

[45]  David N. Wear,et al.  Land-Use Changes in Southern Appalachian Landscapes: Spatial Analysis and Forecast Evaluation , 1998, Ecosystems.

[46]  Y. Yamaguchi,et al.  A case study on the relation between city planning and urban growth using remote sensing and spatial metrics , 2011 .

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

[48]  Evelyn Uuemaa,et al.  Landscape assessment for sustainable planning , 2010 .

[49]  Scott J. Goetz,et al.  Mapping residential density patterns using multi-temporal Landsat data and a decision-tree classifier , 2004 .

[50]  G. Lin,et al.  The Chinese globalizing cities: national centers of globalization and urban transformation , 2004 .