The delineation of urban growth boundaries in complex ecological environment areas by using cellular automata and a dual-environmental evaluation

Abstract Urban growth boundaries are an efficient tool for protecting non-urban land uses from being dominated by urban sprawl and can promote sustainable urban development. Previous studies have explored the use of a cellular automata simulation and its visualization products in delimiting future UGBs. However, existing CA-UGB delineation models lack a transcendental component for ecological evaluation and are difficult to apply to areas with complex ecological environments or heterogeneous resource endowments. Therefore, this paper introduces an innovative model by coupling the dual-environmental evaluation and the Future Land-use Simulation CA model for delimiting future UGBs. To prioritize ecological protection, some intermediate products of the DEE are processed as pivotal components in the CA simulations. Strict urban simulation constraints are also applied in the FLUS model to meet the DEE regulations and prioritize ecological protection. This model was implemented to plan future UGBs in Chungking, China. After quantifying and comparing the proposed UGB scheme with other UGB delineations of Chungking by using various landscape metrics, the DEE-UGBs show a stronger ability to manage urban patches via aggregation with the simultaneous reconciliation of contradictions among land uses.

[1]  B. Bhatta,et al.  Modelling of urban growth boundary using geoinformatics , 2009, Int. J. Digit. Earth.

[2]  Xiaoping Liu,et al.  A future land use simulation model (FLUS) for simulating multiple land use scenarios by coupling human and natural effects , 2017 .

[3]  Shishir Mathur,et al.  Impact of an urban growth boundary across the entire house price spectrum: The two-stage quantile spatial regression approach , 2019 .

[4]  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..

[5]  A. Bregt,et al.  Revisiting Kappa to account for change in the accuracy assessment of land-use change models , 2011 .

[6]  Cindy Q. Tang,et al.  Species Diversity Patterns in Natural Secondary Plant Communities and Man-made Forests in a Subtropical Mountainous Karst Area, Yunnan, SW China , 2010 .

[7]  Stefan Coe,et al.  Erratum to: Urban growth patterns and growth management boundaries in the Central Puget Sound, Washington, 1986–2007 , 2011, Urban Ecosystems.

[8]  Andrés Manuel García,et al.  Cellular automata models for the simulation of real-world urban processes: A review and analysis , 2010 .

[9]  Eric Koomen,et al.  Comparing the input, output, and validation maps for several models of land change , 2008 .

[10]  Michael Ball,et al.  Urban Growth Boundaries and their Impact on Land Prices , 2014 .

[11]  W. D. de Vries,et al.  Combining land-use planning and tenure security: a tenure responsive land-use planning approach for developing countries , 2017 .

[12]  Jing Wang,et al.  Changes in ecological, agricultural, and urban land space in 1984-2012 in China: land policies and regional social-economical drivers. , 2018 .

[13]  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..

[14]  Ying Long,et al.  Urban growth boundaries of the Beijing Metropolitan Area: Comparison of simulation and artwork , 2013 .

[15]  Xiaoping Liu,et al.  Delineating multi-scenario urban growth boundaries with a CA-based FLUS model and morphological method , 2018, Landscape and Urban Planning.

[16]  Junlong Huang,et al.  Simulating urban expansion and its impact on functional connectivity in the Three Gorges Reservoir Area. , 2018, The Science of the total environment.

[17]  E. Kalnay,et al.  Impact of urbanization and land-use change on climate , 2003, Nature.

[18]  G. H. Brundtland World Commission on environment and development , 1985 .

[19]  Maria Cerreta,et al.  Urbanization suitability maps: a dynamic spatial decision support system for sustainable land use , 2012 .

[20]  Xiaohu Zhang,et al.  Simulating land-use dynamics under planning policies by integrating artificial immune systems with cellular automata , 2010, Int. J. Geogr. Inf. Sci..

[21]  P. Shi,et al.  Modeling the urban landscape dynamics in a megalopolitan cluster area by incorporating a gravitational field model with cellular automata , 2013 .

[22]  Patrick Hostert,et al.  Uncovering land-use dynamics driven by human decision-making - A combined model approach using cellular automata and system dynamics , 2012, Environ. Model. Softw..

[23]  Bryan C. Pijanowski,et al.  An urban growth boundary model using neural networks, GIS and radial parameterization: An application to Tehran, Iran , 2011 .

[24]  David B. Eastwood,et al.  The Impact of an Urban Growth Boundary on Land Development in Knox County, Tennessee: A Comparison of Two-Stage Probit Least Squares and Multilayer Neural Network Models , 2007, Journal of Agricultural and Applied Economics.

[25]  Kongjian Yu,et al.  The negative approach to urban growth planning of Beijing, China , 2011 .

[26]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[27]  Lin Liu,et al.  A bottom‐up approach to discover transition rules of cellular automata using ant intelligence , 2008, Int. J. Geogr. Inf. Sci..

[28]  Xiaohua Tong,et al.  Dynamic land use change simulation using cellular automata with spatially nonstationary transition rules , 2018 .

[29]  Mariana Belgiu,et al.  Random forest in remote sensing: A review of applications and future directions , 2016 .

[30]  Amin Tayyebi,et al.  Predicting the expansion of an urban boundary using spatial logistic regression and hybrid raster–vector routines with remote sensing and GIS , 2014, Int. J. Geogr. Inf. Sci..

[31]  Xia Li,et al.  Delimiting the urban growth boundaries with a modified ant colony optimization model , 2017, Comput. Environ. Urban Syst..

[32]  Liu Wei-dong Spatial Planning System in China: Status,Problems and Reconstruction , 2012 .

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

[34]  Myung-Jin Jun,et al.  The Effects of Portland's Urban Growth Boundary on Urban Development Patterns and Commuting , 2004 .

[35]  Yao Yao,et al.  Multiple intra-urban land use simulations and driving factors analysis: a case study in Huicheng, China , 2018, GIScience & Remote Sensing.

[36]  Shaowen Wang,et al.  Sustainable land use optimization using Boundary-based Fast Genetic Algorithm , 2012, Comput. Environ. Urban Syst..

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

[38]  Gérard Biau,et al.  Analysis of a Random Forests Model , 2010, J. Mach. Learn. Res..

[39]  Hu Huang,et al.  Simulating urban growth boundaries using a patch-based cellular automaton with economic and ecological constraints , 2018, Int. J. Geogr. Inf. Sci..

[40]  Daniel Neagu,et al.  Interpreting random forest classification models using a feature contribution method , 2013, IRI.