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Analyzing and modeling the spatiotemporal dynamics of urban expansion: a case study of Hangzhou City, China

    Jie Zhao Affiliation
    ; Wenfu Yang Affiliation
    ; Junhuan Peng Affiliation
    ; Cheng Li Affiliation
    ; Zhen Li Affiliation
    ; Xiaosong Liu Affiliation

Abstract

Understanding the spatiotemporal characteristics of urban expansion is increasingly important for assisting the decision making related to sustainable urban development. By integrating remote sensing (RS), spatial metrics, and the cellular automata (CA) model, this study explored the spatiotemporal dynamics of urban expansion and simulated future scenarios for Hangzhou City, China. The land cover maps (2002, 2008, and 2013) were derived from Landsat images. Moreover, the spatial metrics were applied to characterize the spatial pattern of urban land. The CA model was developed to simulate three scenarios (Business-As-Usual (BAU), Environmental Protection (EP), and Coordination Development (CD)) based on the various strategies. In addition, the scenarios were further evaluated and compared. The results indicated that Hangzhou City has experienced significant urban expansion, and the urban area has increased by 698.59 km2. Meanwhile, the spatial pattern of urban land has become more fragmented and complex. Hangzhou City will face unprecedented pressure on land use efficiency and coordination development if this historical trend continues. The CD scenario was regarded as the optimized scenario for achieving sustainable development. The findings revealed the spatiotemporal characteristics of urban expansion and provide a support for future urban development.

Keyword : urban expansion, spatiotemporal dynamics, remote sensing, spatial patterns, cellular automata model, future scenario

How to Cite
Zhao, J., Yang, W., Peng, J., Li, C., Li, Z., & Liu, X. (2019). Analyzing and modeling the spatiotemporal dynamics of urban expansion: a case study of Hangzhou City, China. Journal of Environmental Engineering and Landscape Management, 27(4), 228-241. https://doi.org/10.3846/jeelm.2019.11561
Published in Issue
Nov 28, 2019
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This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Abo-El-Wafa, H., Yeshitela, K., & Pauleit, S. (2018). The use of urban spatial scenario design model as a strategic planning tool for Addis Ababa. Landscape and Urban Planning, 180, 308-318. https://doi.org/10.1016/j.landurbplan.2017.08.004

Aburas, M. M., Ho, M. Y., Ramli, M. F., & Ash’aari, Z. H. (2016). The simulation and prediction of spatio-temporal urban growth trends using cellular automata models: A review. International Journal of Applied Earth Observation and Geoinformation, 52, 380-389. https://doi.org/10.1016/j.jag.2016.07.007

Agyemang, F. S. K., & Silva, E. (2019). Simulating the urban growth of a predominantly informal Ghanaian city-region with a cellular automata model: Implications for urban planning and policy. Applied Geography, 105, 15-24. https://doi.org/10.1016/j.apgeog.2019.02.011

Aladejana, O. O., Salami, A. T., Adetoro, O.-I. O. (2018). Hydrological responses to land degradation in the Northwest Benin Owena River Basin, Nigeria. Journal of Environmental Management, 225, 300-312. https://doi.org/10.1016/j.jenvman.2018.07.095

Arsanjani, J. J., Helbich, M., Kainz, W., & Boloorani, A. D. (2013). Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion. International Journal of Applied Earth Observation and Geoinformation, 21, 265-275. https://doi.org/10.1016/j.jag.2011.12.014

Bai, X., Chen, J., & Shi, P. (2012). Landscape urbanization and economic growth in China: Positive feedbacks and sustainability dilemmas. Environmental Science & Technology, 46, 132-139. https://doi.org/10.1021/es202329f

Benza, M., Weeks, J. R., Stow, D. A., López-Carr, D., & Clarke, K. C. (2016). A pattern-based definition of urban context using remote sensing and GIS. Remote Sensing of Environment, 183, 250-264. https://doi.org/10.1016/j.rse.2016.06.011

Carter, J. G. (2018). Urban climate change adaptation: Exploring the implications of future land cover scenarios. Cities, 77, 7380. https://doi.org/10.1016/j.cities.2018.01.014

Catalán, B., Saurí, D., & Serra, P. (2008). Urban sprawl in the Mediterranean? Patterns of growth and change in the Barcelona Metropolitan Region 1993–2000. Landscape and Urban Planning, 85, 174-184. https://doi.org/10.1016/j.landurbplan.2007.11.004

Chakraborti, S., Das, D. N., Mondal, B., Shafizadeh-Moghadam, H., & Feng, Y. (2018). A neural network and landscape metrics to propose a flexible urban growth boundary: A case study. Ecological Indicators, 93, 952-965. https://doi.org/10.1016/j.ecolind.2018.05.036

Dadashpoor, H., Azizi, P., & Moghadasi, M. (2019). Land use change, urbanization, and change in landscape pattern in a metropolitan area. Science of The Total Environment, 655, 707-719. https://doi.org/10.1016/j.scitotenv.2018.11.267

Estoque, R.C., & Murayama, Y. (2013). Landscape pattern and ecosystem service value changes: Implications for environmental sustainability planning for the rapidly urbanizing summer capital of the Philippines. Landscape and Urban Planning, 116, 60-72. https://doi.org/10.1016/j.landurbplan.2013.04.008

Fuglsang, M., Münier, B., & Hansen, H. S. (2013). Modelling land-use effects of future urbanization using cellular automata: An Eastern Danish case. Environmental Modelling & Software, 50, 1-11. https://doi.org/10.1016/j.envsoft.2013.08.003

García, A. M., Santé, I., Boullón, M., & Crecente, R. (2012). A comparative analysis of cellular automata models for simulation of small urban areas in Galicia, NW Spain. Computers, Environment and Urban Systems, 36, 291-301. https://doi.org/10.1016/j.compenvurbsys.2012.01.001

García-Nieto, A. P., Geijzendorffer, I. R., Baró, F., Roche, P. K., Bondeau, A., & Cramer, W. (2018). Impacts of urbanization around Mediterranean cities: Changes in ecosystem service supply. Ecological Indicators, 91, 589-606. https://doi.org/10.1016/j.ecolind.2018.03.082
Hayek, U. W., Efthymiou, D., Farooq, B., von Wirth, T., Teich, M., Neuenschwander, N., & Grêt-Regamey, A. (2015). Quality of urban patterns: Spatially explicit evidence for multiple scales. Landscape and Urban Planning, 142, 47-62. https://doi.org/10.1016/j.landurbplan.2015.05.010

He, C., Li, J., Zhang, X., Liu, Z., & Zhang, D. (2017). Will rapid urban expansion in the drylands of northern China continue: A scenario analysis based on the Land Use Scenario Dynamics-urban model and the Shared Socioeconomic Pathways. Journal of Cleaner Production, 165, 57-69. https://doi.org/10.1016/j.jclepro.2017.07.018

He, Q., Zeng, C., Xie, P., Tan, S., & Wu, J. (2019). Comparison of urban growth patterns and changes between three urban agglomerations in China and three metropolises in the USA from 1995 to 2015. Sustainable Cities and Society, 50, 101649. https://doi.org/10.1016/j.scs.2019.101649

Heikkila, E., & Xu, Y. (2014). Seven prototypical Chinese Cities. Urban Studies, 51, 827-847. https://doi.org/10.1177/0042098013492231

Herold, M., Couclelis, H., & Clarke, K. C. (2005). The role of spatial metrics in the analysis and modeling of urban land use change. Computers, Environment and Urban Systems, 29, 369-399. https://doi.org/10.1016/j.compenvurbsys.2003.12.001

Jenks, M., Burton, E., & Williams, K. (1996). The compact city: a sustainable urban form? London: E&F Spon.

Jiang, W., Deng, Y., Tang, Z., Lei, X., & Chen, Z. (2017). Modelling the potential impacts of urban ecosystem changes on carbon storage under different scenarios by linking the CLUE-S and the InVEST models. Ecological Modelling, 345, 30-40. https://doi.org/10.1016/j.ecolmodel.2016.12.002

Jin, X., Long, Y., Sun, W., Lu, Y., Yang, X., & Tang, J. (2017). Evaluating cities’ vitality and identifying ghost cities in China with emerging geographical data. Cities, 63, 98-109. https://doi.org/10.1016/j.cities.2017.01.002

Kaza, N. (2013). The changing urban landscape of the continental United States. Landscape and Urban Planning, 110, 74-86. https://doi.org/10.1016/j.landurbplan.2012.10.015

Kim, H., Kim, Y. K., Song, S. K., & Lee, H. W. (2016). Impact of future urban growth on regional climate changes in the Seoul Metropolitan Area, Korea. Science of The Total Environment, 571, 355-363. https://doi.org/10.1016/j.scitotenv.2016.05.046

Kukkonen, M. O., Muhammad, M. J., Käyhkö, N., & Luoto, M. (2018). Urban expansion in Zanzibar City, Tanzania: Analyzing quantity, spatial patterns and effects of alternative planning approaches. Land Use Policy, 71, 554-565. https://doi.org/10.1016/j.landusepol.2017.11.007

Li, C., Zhao, J., & Xu, Y. (2017). Examining spatiotemporally varying effects of urban expansion and the underlying driving factors. Sustainable Cities and Society, 28, 307-320. https://doi.org/10.1016/j.scs.2016.10.005

Li, G., Sun, S., & Fang, C. (2018). The varying driving forces of urban expansion in China: Insights from a spatial-temporal analysis. Landscape and Urban Planning, 174, 63-77. https://doi.org/10.1016/j.landurbplan.2018.03.004

Liu, T., & Yang, X. (2015). Monitoring land changes in an urban area using satellite imagery, GIS and landscape metrics. Applied Geography, 56, 42-54. https://doi.org/10.1016/j.apgeog.2014.10.002

Lu, D. (2007). Urbanization process and spatial sprawl in China. Urban Planning Forum, 4, 47-52. https://doi.org/10.3969/j.issn.1000-3363.2007.04.006

Luo, T., Zhang, T., Wang, Z., & Gan, Y. (2016). Driving forces of landscape fragmentation due to urban transportation networks: Lessons from Fujian, China. Journal of Urban Planning and Development, 142, 04015013. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000292

Luo, T., Xu, M., Huang, T., Ren, X., & Bu, X. (2018). Rethinking the intensified disparity in urbanization trajectory of a Chinese coastal province and its implications. Journal of Cleaner Production, 195, 1523-1532. https://doi.org/10.1016/j.jclepro.2017.10.083

McGarigal, K., Cushman, S. A., & Ene, E. (2012). FRAGSTATS v4: Spatial pattern analysis program for categorical and continuous maps. Retrieved from http://www.umass.edu/landeco/research/fragstats/fragstats.html

Mikovits, C., Rauch, W., & Kleidorfer, M. (2018). Importance of scenario analysis in urban development for urban water infrastructure planning and management. Computers, Environment and Urban Systems, 68, 9-16. https://doi.org/10.1016/j.compenvurbsys.2017.09.006

Newland, C. P., Maier, H. R., Zecchin, A. C., Newman, J. P., & van Delden, H. (2018). Multi-objective optimisation framework for calibration of Cellular Automata land-use models. Environmental Modelling & Software, 100, 175-200. https://doi.org/10.1016/j.envsoft.2017.11.012

Pham, H. M., Yamaguchi, Y., & Bui, T. Q. (2011). A case study on the relation between city planning and urban growth using remote sensing and spatial metric. Landscape and Urban Planning, 100, 223-230. https://doi.org/10.1016/j.landurbplan.2010.12.009

Pontius, R. G., Boersma, W., Castella, J. C., Clarke, K., de Nijs, T., Dietzel, C., Duan, Z., Fotsing, E., Goldstein, N., Kok, K., Koomen, E., Lippitt, C. D., McConnell, W., Sood, A. M., Pijanowski, B., Pithadia, S., Sweeney, S., Trung, T. N., Veldkamp, A. T., & Verburg, P. H. (2008). Comparing the input, output, and validation maps for several models of land change. Annals of Regional Science, 42, 11-37. https://doi.org/10.1007/s00168-007-0138-2

Pozoukidou, G., & Ntriankos, I. (2017). Measuring and assessing urban sprawl: A proposed indicator system for the city of Thessaloniki, Greece. Remote Sensing Applications: Society and Environment, 8, 30-40. https://doi.org/10.1016/j.rsase.2017.07.005

Santé, I., Marcía, A. M., Miranda, D., & Crecente, R. (2010). Cellular automata models for the simulation of real-world urban processes: A review and analysis. Landscape and Urban Planning, 96, 108-122. https://doi.org/10.1016/j.landurbplan.2010.03.001

Schneider, A., & Woodcock, C. E. (2008). Compact, dispersed, fragmented, extensive? A comparison of urban growth in twenty-five global cities using remotely sensed data, pattern metrics and census information. Urban Studies, 45, 659-692. https://doi.org/10.1177/0042098007087340

Simwanda, M., & Murayama, Y. (2018). Spatiotemporal patterns of urban land use change in the rapidly growing city of Lusaka, Zambia: Implications for sustainable urban development. Sustainable Cities and Society, 39, 262-274. https://doi.org/10.1016/j.scs.2018.01.039

Son, N. T., Chen, C. F., Chen, C. R., Thanh, B. X., & Vuong, T. H. (2017). Assessment of urbanization and urban heat islands in Ho Chi Minh City, Vietnam using Landsat data. Sustainable Cities and Society, 30, 150-161. https://doi.org/10.1016/j.scs.2017.01.009

Song, W., Pijanowski, B. C., & Tayyebi, A. (2015). Urban expansion and its consumption of high-quality farmland in Beijing, China. Ecological Indicators, 54, 60-70. https://doi.org/10.1016/j.ecolind.2015.02.015

Tian, G. J., Ouyang, Y., Quan, Q., & Wu, J. (2011). Simulating spatiotemporal dynamics of urbanization with multi-agent systems-A case study of the Phoenix metropolitan region, USA. Ecological Modelling, 222, 1129-1138. https://doi.org/10.1016/j.ecolmodel.2010.12.018

Tian, L., Li, Y., Yan, Y., & Wang, B. (2017). Measuring urban sprawl and exploring the role planning plays: A Shanghai case study. Land Use Policy, 67, 426-435. https://doi.org/10.1016/j.landusepol.2017.06.002

Tripathy, P., & Kumar, A. (2019). Monitoring and modelling spatio-temporal urban growth of Delhi using Cellular Automata and geoinformatics. Cities, 90, 52-63. https://doi.org/10.1016/j.cities.2019.01.021

United Nations. (2018). World Urbanization Prospects: the 2018 Revision. Retrieved from https://esa.un.org/unpd/wup/

Vanderhaegen, S., & Canters, F. (2017). Mapping urban form and function at city block level using spatial metrics. Landscape and Urban Planning, 167, 399-409. https://doi.org/10.1016/j.landurbplan.2017.05.023

White, R., & Engelen, G. (2000). High-resolution integrated modelling of the spatial dynamics of urban and regional systems. Computers, Environment and Urban Systems, 24, 383-400. https://doi.org/10.1016/S0198-9715(00)00012-0

Wu, J., Jenerette, G. D., Buyantuyev, A., & Redman, C. L. (2011). Quantifying spatiotemporal patterns of urbanization: The case of the two fastest growing metropolitan regions in the United States. Ecological Complexity, 8, 1-8. https://doi.org/10.1016/j.ecocom.2010.03.002

Xu, C., Haase, D., & Pauleit, S. (2018). The impact of different urban dynamics on green space availability: A multiple scenario modeling approach for the region of Munich, Germany. Ecological Indicators, 93, 1-12. https://doi.org/10.1016/j.ecolind.2018.04.058

Xu, Q., Zheng, X., & Zheng, M. (2019). Do urban planning policies meet sustainable urbanization goals? A scenario-based study in Beijing, China. Science of The Total Environment, 670, 498-507. https://doi.org/10.1016/j.scitotenv.2019.03.128

Yang, Y., Liu, Y., Li, Y., & Du, G. (2018). Quantifying spatiotemporal patterns of urban expansion in Beijing during 19852013 with rural-urban development transformation. Land Use Policy, 74, 220-230. https://doi.org/10.1016/j.landusepol.2017.07.004

Zang, Z., Zou, X., Zuo, P., Song, Q., Wang, C., & Wang, J. (2017). Impact of landscape patterns on ecological vulnerability and ecosystem service values: An empirical analysis of Yancheng Nature Reserve in China. Ecological Indicators, 72, 142-152. https://doi.org/10.1016/j.ecolind.2016.08.019

Zhang, D., Huang, Q., He, C., Dan, Y., & Liu, Z. (2019). Planning urban landscape to maintain key ecosystem services in a rapidly urbanizing area: A scenario analysis in the Beijing-Tianjin-Hebei urban agglomeration, China. Ecological Indicators, 96, 559-571. https://doi.org/10.1016/j.ecolind.2018.09.030

Zinia, N. J., & McShane, P. (2018). Ecosystem services management: An evaluation of green adaptations for urban development in Dhaka, Bangladesh. Landscape and Urban Planning, 173, 23-32. https://doi.org/10.1016/j.landurbplan.2018.01.008