Simultaneous Simulation of Urban Shrinkage and Expansion Using Cellular Automaton and Maximum Information Entropy Models: Case Study of Urban Evolution in Wuhan Metropolitan Area
Publication: Journal of Urban Planning and Development
Volume 149, Issue 4
Abstract
During the past two decades discussions on urban shrinkage have been increasing in intensity, mainly due to the irresistible trends of migration, economic transformation, and the so-called “siphon effect” of large and mega cities. Yet, very few studies have tried to understand urban shrinkage from the perspective of local microscopic unit evolution. This study develops a novel model for simultaneous simulation of expansion and shrinkage (MSSES) of urban built-up areas. Starting from a microscopic basis, our MSSES can simulate both the processes and the states that lead to spatial expansion or shrinkage. A MaxEnt model is further used to investigate the driving factors of microspatial changes and compute the probabilities of shrinkage (or expansion) of urban built-up areas. Finally, it simulates the explicit layout of the spatial distribution of shrinkage (or expansion) patches with the help of a sorting cellular automata (CA) model. The validity of MSSES is verified using multisourced data from the Wuhan agglomeration, China. We show that (1) MSSES can more accurately simulate urban expansion or shrinkage than the currently widely used neighborhood-based Logistic-CA (NL-CA) and (2) MSSES has advantage in solving the commonly seen problem of “diffusion-coalescence,” especially for the simulation of outlying expansion. Against the context of the Wuhan metropolitan area, we also found that overall the shrinkage trend is slowing down significantly, presenting three types of shrinkage at city-scale: remote shrinkage, peripheral shrinkage, and international shrinkage. Our study has contributions to the body of knowledge as well as practical implications for urban management and improving the sustainable development of urban areas in both China and abroad.
Practical Applications
The city we live in may be experiencing a situation where expansion and shrinkage are happening simultaneously. Hence, the simulation and prediction of temporal and spatial changes in urban expansion and shrinkage hold great importance in formulating urban policies. In this study, we propose a model capable of simultaneously predicting urban growth and shrinkage, and apply this model to the urban morphological changes in the Wuhan metropolitan area from 2000 to 2035. The simulation results demonstrate the effectiveness of this model in predicting the locations of urban expansion and contraction in advance. Furthermore, we discovered that the overall shrinkage trend is projected to significantly decelerate in the future. These findings offer support for intervention in urban planning, guiding the development of urban spaces and advancing the scientific aspects of urban planning.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This research was funded by the Key Laboratory of Territorial Spatial Planning and Development-Protection of the Ministry of Natural Resources of PRC and CAUPD Beijing Planning & Design Consultants LTD (ID. TSPDP23/01), the National Natural Science Foundation of China (ID. 42001334), and the Independent Innovation Fund for Young Teachers of Huazhong University of Science and Technology (ID. 2021WKYXQN031 and 2022WKFZZX025).
References
Aburas, M. M., Y. M. Ho, M. F. Ramli, and Z. H. Ash’aari. 2016. “The simulation and prediction of spatio-temporal urban growth trends using cellular automata models: A review.” Int. J. Appl. Earth Obs. Geoinf. 52: 380–389. https://doi.org/10.1016/j.jag.2016.07.007.
Bhatti, S. S., N. K. Tripathi, V. Nitivattananon, I. A. Rana, and C. Mozumder. 2015. “A multi-scale modeling approach for simulating urbanization in a metropolitan region.” Habitat Int. 50: 354–365. https://doi.org/10.1016/j.habitatint.2015.09.005.
Chen, T., E. C. Hui, Y. Tu, and W. Lang. 2021. “Growth or shrinkage: Discovering development patterns and planning strategies for cross-border areas in China.” J. Urban Plann. Dev. 147 (4): 05021046. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000761.
Deng, T., D. Wang, Y. Yang, and H. Yang. 2019. “Shrinking cities in growing China: Did high speed rail further aggravate urban shrinkage?” Cities 86: 210–219. https://doi.org/10.1016/j.cities.2018.09.017.
Dong, L., X. Yuan, M. Li, C. Ratti, and Y. Liu. 2021. “A gridded establishment dataset as a proxy for economic activity in China.” Sci. Data 8 (1): 1–9. https://doi.org/10.1038/s41597-020-00792-9.
Du, Z., L. Jin, Y. Ye, and H. Zhang. 2020. “Characteristics and influences of urban shrinkage in the exo-urbanization area of the Pearl River Delta, China.” Cities 103: 102767. https://doi.org/10.1016/j.cities.2020.102767.
Guan, D., X. He, and X. Hu. 2021. “Quantitative identification and evolution trend simulation of shrinking cities at the county scale, China.” Sustainable Cities Soc. 65: 102611. https://doi.org/10.1016/j.scs.2020.102611.
Haase, D., A. Haase, N. Kabisch, S. Kabisch, and D. Rink. 2012. “Actors and factors in land-use simulation: the challenge of urban shrinkage.” Environ. Modell. Software 35: 92–103. https://doi.org/10.1016/j.envsoft.2012.02.012.
Hàussermann, H., and W. Siebel. 1988. “The shrinking city and urban sociology.” Soziologische Stadtforschung Jurgen Friedrichs 29: 78–94. https://doi.org/10.1007/978-3-322-83617-5_5.
He, C., N. Okada, Q. Zhang, P. Shi, and J. Li. 2008. “Modelling dynamic urban expansion processes incorporating a potential model with cellular automata.” Landscape Urban Plann. 86 (1): 79–91. https://doi.org/10.1016/j.landurbplan.2007.12.010.
He, Q., W. He, Y. Song, J. Wu, C. Yin, and Y. Mou. 2018. “The impact of urban growth patterns on urban vitality in newly built-up areas based on an association rules analysis using geographical ‘big data’.” Land Use Policy 78: 726–738. https://doi.org/10.1016/j.landusepol.2018.07.020.
He, Q., R. Tan, and J. Yang. 2021. “Synchronized simulation of urban diffusional and aggregational process based on the affinity propagation cellular automata—A case study of Wuhan city.” [In Chinese with English Abstract.] Acta Geogr. Sin. 76 (10): 2522–2535.
He, Q., J. Zhou, S. Tan, Y. Song, L. Zhang, Y. Mou, and J. Wu. 2020. “What is the developmental level of outlying expansion patches? A study of 275 Chinese cities using geographical big data.” Cities 105: 102395. https://doi.org/10.1016/j.cities.2019.102395.
Hu, Y., Z. Wang, and T. Deng. 2021. “Expansion in the shrinking cities: Does place-based policy help to curb urban shrinkage in China?” Cities 113: 103188. https://doi.org/10.1016/j.cities.2021.103188.
Iwasaki, Y. 2021. “Shrinkage of regional cities in Japan: Analysis of changes in densely inhabited districts.” Cities 113: 103168. https://doi.org/10.1016/j.cities.2021.103168.
Jain, M., S. Siedentop, H. Taubenböck, and S. Namperumal. 2013. “From suburbanization to counterurbanization? Investigating urban dynamics in the National Capital Region Delhi, India.” Environ. Urban. Asia 4 (2): 247–266. https://doi.org/10.1177/0975425313510765.
Jiang, N., A. Crooks, W. Wang, and Y. Xie. 2021. “Simulating urban shrinkage in Detroit via agent-based modeling.” Sustainability 13 (4): 2283. https://doi.org/10.3390/su13042283.
Jiang, Z., W. Zhai, X. Meng, and Y. Long. 2020. “Identifying shrinking cities with NPP-VIIRS nightlight data in China.” J. Urban Plann. Dev. 146 (4): 04020034. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000598.
Jiao, L. 2015. “Urban land density function: A new method to characterize urban expansion.” Landscape Urban Plann. 139: 26–39. https://doi.org/10.1016/j.landurbplan.2015.02.017.
Kamarajugedda, S. A., and E. Y. Lo. 2019. “Modelling urban growth for Bangkok and assessing linkages with road density and socio-economic indicators. The International Archives of Photogrammetry.” Remote Sens. Spatial Inf. Sci. 42: 255–262.
Karp, D. N., S. Bagchi-Sen, and P. Rogerson. 2022. “Not all shrinking places are similar: The variegated nature of population decline in the United States.” Appl. Geogr. 138: 102581. https://doi.org/10.1016/j.apgeog.2021.102581.
Kumar, V., V. K. Singh, K. Gupta, and A. K. Jha. 2021. “Integrating cellular automata and agent-based modeling for predicting urban growth: A case of Dehradun City.” J. Indian Soc. Remote Sens. 49 (11): 2779–2795. https://doi.org/10.1007/s12524-021-01418-2.
Lang, W., J. Deng, and X. Li. 2020. “Identification of “growth” and “shrinkage” pattern and planning strategies for shrinking cities based on a spatial perspective of the Pearl River Delta Region.” J. Urban Plann. Dev. 146 (4): 05020020. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000612.
Lauf, S., D. Haase, R. Seppelt, and N. Schwarz. 2012. “Simulating demography and housing demand in an urban region under scenarios of growth and shrinkage.” Environ. Plann. B: Plann. Des. 39: 229–246. https://doi.org/10.1068/b36046t.
Li, X., and A. G. O. Yeh. 2000. “Modelling sustainable urban development by the integration of constrained cellular automata and GIS.” Int. J. Geogr. Inf. Sci. 14 (2): 131–152. https://doi.org/10.1080/136588100240886.
Li, Y. 2014. Chinese city and regional planning systems. Surrey: Ashgate.
Liu, X., M. Lei, L. Xia, B. Ai, S. Li, and Z. He. 2014. “Simulating urban growth by integrating landscape expansion index (lei) and cellular automata.” Int. J. Geogr. Inf. Sci. 28 (1–2): 148–163. https://doi.org/10.1080/13658816.2013.831097.
Liu, X., X. Li, Y. Chen, Z. Tan, S. Li, and B. Ai. 2010. “A new landscape index for quantifying urban expansion using multi-temporal remotely sensed data.” Landscape Ecol. 25 (5): 671–682. https://doi.org/10.1007/s10980-010-9454-5.
Liu, Y., Q. He, R. Tan, Y. Liu, and C. Yin. 2016. “Modeling different urban growth patterns based on the evolution of urban form: A case study from Huangpi, Central China.” Appl. Geogr. 66: 109–118. https://doi.org/10.1016/j.apgeog.2015.11.012.
Liu, Z., and S. Liu. 2022. “Urban shrinkage in a developing context: Rethinking China's present and future trends.” Sustainable Cities Soc. 80: 103779. https://doi.org/10.1016/j.scs.2022.103779.
Long, Y., and K. Wu. 2016. “Shrinking cities in a rapidly urbanizing China.” Environ. Plann. A 48 (2): 220–222. https://doi.org/10.1177/0308518X15621631.
Lym, Y. 2021. “Exploring dynamic process of regional shrinkage in Ohio: A Bayesian perspective on population shifts at small-area levels.” Cities 115: 103228. https://doi.org/10.1016/j.cities.2021.103228.
Martinez-Fernandez, C., I. Audirac, S. Fol, and E. Cunningham-Sabot. 2012. “Shrinking cities: Urban challenges of globalization.” Int. J. Urban Reg. Res. 36 (2): 213–225. https://doi.org/10.1111/j.1468-2427.2011.01092.x.
Mouratidis, K., and W. Poortinga. 2020. “Built environment, urban vitality and social cohesion: Do vibrant neighborhoods foster strong communities?” Landscape Urban Plann. 204: 103951. https://doi.org/10.1016/j.landurbplan.2020.103951.
NESSDS (National Earth System Science Data Science). 2022. www.geodata.cn/data/datadetails.html?dataguid=122535017095134&docid=9790.
Pratama, A. P., and M. H. Yudhistira. 2022. “Highway expansion and urban sprawl in the Jakarta metropolitan area.” Land Use Policy 112: 105856. https://doi.org/10.1016/j.landusepol.2021.105856.
Rosenstein-Rodan, P. N. 1943. “Problems of industrialisation of eastern and south-eastern Europe”. The Economic Journal 53: 202–211.
Santé, I., A. García, and D. Miranda. 2010. “Cellular automata models for the simulation of real-world urban processes: A review and analysis.” Landscape Urban Plann. 96 (2): 108–122. https://doi.org/10.1016/j.landurbplan.2010.03.001.
Sarkar, A., and P. Chouhan. 2020. “Modeling spatial determinants of urban expansion of Siliguri a metropolitan city of India using logistic regression.” Model. Earth Syst. Environ. 6 (4): 2317–2331. https://doi.org/10.1007/s40808-020-00815-9.
Tan, R., Y. Liu, K. Zhou, L. Jiao, and W. Tang. 2015. “A game-theory based agent-cellular model for use in urban growth simulation: A case study of the rapidly urbanizing Wuhan area of central China.” Comput. Environ. Urban Syst. 49: 15–29. https://doi.org/10.1016/j.compenvurbsys.2014.09.001.
Tong, X., and Y. Feng. 2020. “A review of assessment methods for cellular automata models of land-use change and urban growth.” Int. J. Geogr. Inf. Sci. 34 (5): 866–898. https://doi.org/10.1080/13658816.2019.1684499.
Torrens, P. M., and D. O'Sullivan. 2001. “Cellular automata and urban simulation: where do we go from here?” Environ. Plann. B: Plann. Des. 28 (2): 163–168. https://doi.org/10.1068/b2802ed.
Van Vliet, J., R. White, and S. Dragicevic. 2009. “Modeling urban growth using a variable grid cellular automaton.” Comput. Environ. Urban Syst. 33 (1): 35–43. https://doi.org/10.1016/j.compenvurbsys.2008.06.006.
Wang, J., Q. Wu, S. Yan, G. Guo, and S. Peng. 2020a. “China’s local governments breaking the land use planning quota: A strategic interaction perspective.” Land Use Policy 92: 104434. https://doi.org/10.1016/j.landusepol.2019.104434.
Wang, J., Z. Yang, and X. Qian. 2020b. “Driving factors of urban shrinkage: Examining the role of local industrial diversity.” Cities 99: 102646. https://doi.org/10.1016/j.cities.2020.102646.
Wang, R., W. He, D. Wu, L. Zhang, and Y. Li. 2021. “Urban land expansion simulation considering the diffusional and aggregated growth simultaneously: A case study of Luoyang City.” Sustainability 13: 9781. https://doi.org/10.3390/su13179781.
White, R., and G. Engelen. 1993. “Cellular automata and fractal urban form: A cellular modelling approach to the evolution of urban land-use patterns.” Environ. Plann. A 25: 1175–1195. https://doi.org/10.1068/a251175.
Wiechmann, T., and K. M. Pallagst. 2012. “Urban shrinkage in Germany and the USA: A comparison of transformation patterns and local strategies.” Int. J. Urban Reg. Res. 36 (2): 261–280. https://doi.org/10.1111/j.1468-2427.2011.01095.x.
Wu, H., A. Lin, X. Xing, D. Song, and Y. Li. 2021. “Identifying core driving factors of urban land use change from global land cover products and POI data using the random forest method.” Int. J. Appl. Earth Obs. Geoinf. 103: 102475. https://doi.org/10.1016/j.jag.2021.102475.
Wu, J., N. Ta, Y. Song, J. Lin, and Y. Chai. 2018. “Urban form breeds neighborhood vibrancy: A case study using a GPS-based activity survey in suburban Beijing.” Cities 74: 100–108. https://doi.org/10.1016/j.cities.2017.11.008.
Xu, G., L. Jiao, M. Yuan, T. Dong, B. Zhang, and C. Du. 2019. “How does urban population density decline over time? An exponential model for Chinese cities with international comparisons.” Landscape Urban Plann. 183 (3): 59–67. https://doi.org/10.1016/j.landurbplan.2018.11.005.
Zeng, C., Y. Song, Q. He, and F. Shen. 2018. “Spatially explicit assessment on urban vitality: Case studies in Chicago and Wuhan.” Sustainable Cities Soc. 40: 296–306. https://doi.org/10.1016/j.scs.2018.04.021.
Zeng, C., M. Zhang, J. Cui, and S. He. 2015. “Monitoring and modeling urban expansion—A spatially explicit and multi-scale perspective.” Cities 43: 92–103. https://doi.org/10.1016/j.cities.2014.11.009.
Zhang, Y., X. Liu, G. Chen, and G. Hu. 2020. “Simulation of urban expansion based on cellular automata and maximum entropy model.” Sci. China Earth Sci. 63 (5): 701–712. https://doi.org/10.1007/s11430-019-9530-8.
Zhao, C., J. Jensen, and B. Zhan. 2017. “A comparison of urban growth and their influencing factors of two border cities: Laredo in the US and Nuevo Laredo in Mexico.” Appl. Geogr. 79: 223–234. https://doi.org/10.1016/j.apgeog.2016.12.017.
Information & Authors
Information
Published In
Journal of Urban Planning and Development
Volume 149 • Issue 4 • December 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Oct 18, 2022
Accepted: Jun 12, 2023
Published online: Aug 4, 2023
Published in print: Dec 1, 2023
Discussion open until: Jan 4, 2024
ASCE Technical Topics:
- Automation and robotics
- Case studies
- Computer models
- Distribution functions
- Engineering fundamentals
- Infrastructure
- Material mechanics
- Material properties
- Materials engineering
- Mathematical functions
- Mathematics
- Methodology (by type)
- Models (by type)
- Research methods (by type)
- Shrinkage (material)
- Simulation models
- Spatial distribution
- Systems engineering
- Urban and regional development
- Urban areas
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.