Abstract
Urban growth is an unavoidable process caused by economic development and population growth. Traditional urban growth models represent the future urban growth pattern by repeating the historical urban growth regulations, which can lead to a lot of environmental problems. The Yangtze watershed is the largest and the most prosperous economic area in China, and it has been suffering from rapid urban growth from the 1970s. With the built-up area increasing from 23,238 to 31,054 km2 during the period from 1980 to 2005, the watershed has suffered from serious nonpoint source (NPS) pollution problems, which have been mainly caused by the rapid urban growth. To protect the environment and at the same time maintain the economic development, a multiobjective optimization (MOP) is proposed to tradeoff the multiple objectives during the urban growth process of the Yangtze watershed. In particular, the four objectives of minimization of NPS pollution, maximization of GDP value, minimization of the spatial incompatibility between the land uses, and minimization of the cost of land-use change are considered by the MOP approach. Conventionally, a genetic algorithm (GA) is employed to search the Pareto solution set. In our MOP approach, a two-dimensional GA, rather than the traditional one-dimensional GA, is employed to assist with the search for the spatial optimization solution, where the land-use cells in the two-dimensional space act as genes in the GA. Furthermore, to confirm the superiority of the MOP approach over the traditional prediction approaches, a widely used urban growth prediction model, cellular automata (CA), is also carried out to allow a comparison with the Pareto solution of MOP. The results indicate that the MOP approach can make a tradeoff between the multiple objectives and can achieve an optimal urban growth pattern for Yangtze watershed, while the CA prediction model just represents the historical urban growth pattern as the future growth pattern. Moreover, according to the spatial clustering index, the urban growth pattern predicted through MOP is more reasonable. In summary, the proposed model provides a set of Pareto urban growth solutions, which compromise environmental and economic issues for the Yangtze watershed.
Similar content being viewed by others
References
Aerts JCJH, Eisinger E, Heuvelink GBM, Stewart TJ (2003) Using linear integer programming for multi-site land-use allocation. Geogr Anal 35:148–169
Balling R, Wilson S (2001) The maxi-min fitness function for multi-objective evolutionary computation: Application to city planning. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO’2001)
Balling R, Taber JT, Brown MR, Day K (1999) Multiobjective urban planning using genetic algorithm. J Urban Plan Dev 125(2):86–99
Balling R, Powell B, Saito M (2004) Generating future land-use and transportation plans for high-growth cities using a Genetic Algorithm. Aided Civ Infrastruct Eng 19:213–222
Cao K, Huang B, Wang SW, Lin H (2012) Sustainable land use optimization using Boundary-based Fast Genetic Algorithm. Comput Environ Urban Syst 36(3):257–269
Chandramouli M, Huang B, Xue L (2009) Spatial change optimization: Integrating GA with visualization for 3D scenario generation. Photogramm Eng Remote Sens 75(8):1015–1023
Chreod Ltd (2001) Urbanizing Regions in China’s Yangtze Basin: Development Trends and Key Priorities, summary report. Shanghai
Ding XW, Shen ZY, Hong Q, Yang ZF, Wu X, Liu RM (2010) Development and test of the Export Coefficient Model in the Upper Reach of The Yangtze River. J Hydrol 383:233–244
Duan XJ, Yu XG (2002) Analysis and assessment of the sustainable development in Changjiang River Valley. China Popul Resour Environ 12(2):75–80
Feng YJ, Liu Y, Tong XH, Liu ML, Deng SS (2011) Modeling dynamic urban growth using cellular automata and particle swarm optimization rules. Landsc Urban Plan 102:188–196
Grimm NB, Morgan Grove J, Pickett STA, Redman CL (2000) Integrated approaches to long-term studies of Urban Ecological Systems. Am Inst Biol Sci 50(7):571–584
Guldmann JM (1979) Urban land use allocation and environmental pollution control: an intertemporal optimization approach. Socio Econ Plan Sci 13(2):71–86
Herold M, Goldstein NC, Clarke KC (2003) The spatiotemporal form of urban growth: Measurement, analysis and modeling. Remote Sens Environ 86(3):286–302
Johnes PJ (1996) Evaluation and management of the impact of land use change on the nitrogen and phosphorus load delivered to surface waters: the export coefficient modelling approach. J Hydrol 183:323–349
Kay D, Crowther J, Stapleton CM, Wyer MD, Fewtrell L, Anthony S, Bradford M, Edwards A, Francis CA, Hopkins M, Kay C, McDonald AT, Watkins J, Wilkinson J (2008) Faecal indicator organism concentrations and catchment export coefficients in the UK. Water Res 42(10–11):2649–2661
Kiril S, Michael B (2011) Exploring the historical determinants of urban growth patterns through cellular automata. Trans GIS 15(3):253–271
Li XY, Yang LB, Yan WJ (2011) Model analysis of dissolved inorganic phosphorus exports from The Yangtze River to the estuary. Nutr Cycl Agroecosyst 90:157–170
Ligmann-Zielinska A, Church RL, Jankowski P (2008) Spatial optimization as a generative technique for sustainable multiobjective land-use allocation. Int J Geogr Inf Sci 22(6):601–622
Liu QQ, Singh VP (2004) Effect of microtopography, slope length and gradient, and vegetative cover on overland flow through simulation. J Hydrol Eng 9:375–382
Liu RM, Yang ZF, Shen ZY, Wu X (2006) Relationship and simulation information system of land use/cover change and non-point source pollution in Yangtze river basin. Resour Environ Yangtze Basin 15(3):372–377
Liu RM, Yang ZF, Shen ZY, Yu SL, Ding XW, Wu X, Liu F (2009) Estimating nonpoint source pollution in the upper the Yangtze River using the Export Coefficient Model, Remote Sensing, and Geographical Information System. J Hydraul Eng 135(9):698–704
Maithani S (2010) Cellular Automata-Based Model of urban spatial growth. J Indian Soc Remote Sens 38(4):604–610
Mansor SB, Pormanafi S, Mahmud ARB, Pirasteh S (2012) Optimization of land use suitability for agriculture using Integrated Geospatial Model and Genetic Algorithms. ISPRS Ann Photogramm Remote Sens Spat Inf Sci I-2:234–299
Matthews KB (2001) Applying genetic algorithms to multi-objective land-use planning. Doctoral dissertation. The Robert Gordon University
Matthews KB, Buchan K, Sibbald AR, Craw S (2006) Combining deliberative and computer-based methods for multi-objective land-use planning. Agric Syst 87:18–37
Oğuz H (2004) Modeling urban growth and land use/land cover change in the Houston metropolitan area from 2002–2030. Doctoral dissertation. Texas A & M University, U.S
Oguz H, Klein AG, Srinivasan R (2007) Using the SLEUTH urban growth model to simulate the impacts of future policy scenarios on urban land use in the Houston-Galveston-Brazoria CMSA. Res J Soc Sci 2:72–82
Rabbani A, Aghababaee H, Rajabi MA (2012) Modeling dynamic urban growth using hybrid cellular automata and particle swarm optimization. J Appl Remote Sens 6:063582
Sadeghi SHR, Jalili K, Nikkami D (2009) Land use optimization in watershed scale. Land Use Policy 26:186–193
Shen Z, Hong Q, Yu H, Liu R (2008) Parameter uncertainty analysis of the nonpoint source pollution in the Daning River watershed of the Three Gorges Reservoir Region, China. Sci Total Environ 405:195–205
Silva EA, Clarke KC (2002) Calibration of the SLEUTH urban growth model for Lisbon and Porto, Portugal. Comput Environ Urban Syst 26(6):525–552
Sims JT, Simard RR, Joern BC (1998) Phosphorus losses in agricultural drainage: Historical perspective and current research. J Environ Qual 27:277–293
Srinivas N, Deb K (1994) Multiobjective optimization using nondominated sorting in genetic algorithms. Evol Comput 2(3):221–248
Srivastava P, Hamlett JM, Robillard PD, Day RL (2002) Watershed optimization of best management practices using AnnAGNPS and a genetic algorithm. Water. Resour Res 38(3):1021–1034
Stewart TJ, Janssen R, Herwijnen M (2004) A genetic algorithm approach to multiobjective land use planning. Comput Oper Res 31:2293–2313
Vose MD (1999) The simple genetic algorithm: foundations and theory. MIT Press, U.S.A
Walker R (2001) Urban sprawl and natural areas encroachment: linking land cover change and economic development in the Florida Everglades. Ecol Econ 37:357–369
Wang XT, Liu ZW, Yang QY (2003) Countermeasure on the ecological barrier construction of upper reach of The Yangtze River. China Agricultural Press, Beijing
Wang XH, Yu S, Huang GH (2004) Land allocation based on integrated GIS-optimization modeling at a watershed level. Landsc Urban Plan 66:61–74
Weng QH, Lu DS (2008) A sub-pixel analysis of urbanization effect on land surface temperature and its interplay with impervious surface and vegetation coverage in Indianapolis, United States. Int J Appl Earth Obs Geoinf 10(1):68–83
Worralla F, Burtb TP (1999) The impact of land-use change on water quality at the catchment scale: the use of export coefficient and structural models. J Hydrol 221:75–90
Zhang XB, Zhang YY, Wen AB, Feng MY (2003) Assessment of soil losses on cultivated land by using the 137 Cs technique in the Upper Yangtze River Basin of China. Soil Tillage Res 69:99–106
Zhang HH, Zeng YN, Bian L (2010) Simulating multi-objective spatial optimization allocation of land use based on the integration of Multi-Agent System and Genetic Algorithm. Int J Environ Res 4:765–776
Zobrist J, Reichert P (2006) Bayesian estimation of export coefficients from diffuse and point sources in Swiss watersheds. J Hydrol 329:207–223
Acknowledgments
This study was supported by funding from the CHINA SCHOLARSHIP COUNCIL (File No. 201308420279), National Natural Science Foundation of China (NSFC: 40871179) and Hong Kong Research Grants Council (RGC: 444612). The authors are also very grateful to the Data Sharing Infrastructure of Earth System Science and Changjiang Soil and Water Conservation Monitoring Centre, CWRC, China for providing the land-use data of the Yangtze watershed between 1980 and 2005.
Author information
Authors and Affiliations
Corresponding author
Additional information
Responsible editor: Michael Matthies
Rights and permissions
About this article
Cite this article
Zhang, W., Wang, H., Han, F. et al. Modeling urban growth by the use of a multiobjective optimization approach: Environmental and economic issues for the Yangtze watershed, China. Environ Sci Pollut Res 21, 13027–13042 (2014). https://doi.org/10.1007/s11356-014-3007-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11356-014-3007-4