Infrastructure-driven growth of a coastal tourist city: A case study of Pattaya, Thailand
Vol 8, Issue 9, 2024
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Abstract
Pattaya City is a well-known tourist destination in Thailand, famous for its beautiful beachfront, lively nightlife, and stunning natural scenery. Since 2019, the Eastern Special Development Zone Act, the so-called EEC (Eastern Economic Corridor), has positioned the city as a focal point for Meetings, Incentives, Conferences, and Exhibitions (MICE), boosting its tourism-driven economy. Infrastructure improvements in the region have accelerated urban development over the past decade. However, it is uncertain whether this growth primarily comes from development within existing areas or the expansion of urban boundaries and what direction future growth may take. To investigate this, research using the Cellular Automata-Markov model has been conducted to analyze land use changes and urban growth patterns in Pattaya, using land use data from the Department of Land for 2013 and 2017. The findings suggest an upcoming city expansion along the motorway, indicating that infrastructure improvements could drive rapid urbanization in coastal areas. This urban expansion emphasizes the need for urban management and strategic land use planning in coastal cities.
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Arsanjani, J. J., Kainz, W., & Mousivand, A. J. (2011). Tracking dynamic land-use change using spatially explicit Markov Chain based on cellular automata: the case of Tehran. International Journal of Image and Data Fusion, 2(4), 329–345. https://doi.org/10.1080/19479832.2011.605397
Batty, M. (1997). Cellular Automata and Urban Form: A Primer. Journal of the American Planning Association, 63(2), 266–274. https://doi.org/10.1080/01944369708975918
Bhatta, B. (2010). Analysis of Urban Growth and Sprawl from Remote Sensing Data. In: Advances in Geographic Information Science. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-05299-6
CLARK LABS. (n.d.). TerrSet Geospatial Monitoring and Modeling Software. Available online: https://clarklabs.org/terrset/ (accessed on 20 February 2024).
Dadashpoor, H., & Hasankhani, Z. (2022). Exploring patterns and consequences of land consumption in a coastal city-region. Ecological Processes, 11(1). https://doi.org/10.1186/s13717-022-00391-z
Garcia-López, M.-À. (2012). Urban spatial structure, suburbanization and transportation in Barcelona. Journal of Urban Economics, 72(2–3), 176–190. https://doi.org/10.1016/j.jue.2012.05.003
Gaur, S., & Singh, R. (2023). A Comprehensive Review on Land Use/Land Cover (LULC) Change Modeling for Urban Development: Current Status and Future Prospects. Sustainability, 15(2), 903. https://doi.org/10.3390/su15020903
Gervasi, O., Murgante, B., Rocha, A. M. A. C., et al. (2023). Lecture Notes in Computer Science. In: Computational Science and Its Applications – ICCSA 2023 Workshops. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-37123-3
Hamad, R., Balzter, H., & Kolo, K. (2018). Predicting Land Use/Land Cover Changes Using a CA-Markov Model under Two Different Scenarios. Sustainability, 10(10), 3421. https://doi.org/10.3390/su10103421
Han, Y., Zhu, J., Wei, D., et al. (2022). Spatial-Temporal Effect of Sea–Land Gradient on Land Use Change in Coastal Zone: A Case Study of Dalian City. Land, 11(8), 1302. https://doi.org/10.3390/land11081302
Hansasooksin, S. T., & Tontisirin, N. (2018). Applying the Analytical Hierarchy Process (AHP) Approach to Assess an Area-Based Innovation System in Thailand. Nakhara : Journal of Environmental Design and Planning, 15, 63–76. https://doi.org/10.54028/nj2018156376
Hansasooksin, S. T., & Tontisirin, N. (2021). Placemaking as an urban development strategy for making the Pattaya Innovation District. Regional Science Policy & Practice, 13(6), 1930–1951. https://doi.org/10.1111/rsp3.12400
Harvey, R. O., & Clark, W. A. V. (1965). The Nature and Economics of Urban Sprawl. Land Economics, 41(1), 1. https://doi.org/10.2307/3144884
Huang, Y. (2016). Understanding China’s Belt & Road Initiative: Motivation, framework and assessment. China Economic Review, 40, 314–321. https://doi.org/10.1016/j.chieco.2016.07.007
Hyandye, C., & Martz, L. W. (2016). A Markovian and cellular automata land-use change predictive model of the Usangu Catchment. International Journal of Remote Sensing, 38(1), 64–81. https://doi.org/10.1080/01431161.2016.1259675
Jabareen, Y. (2006). Sustainable urban form: their typologies, models, and concept. Journal of Planning Education and Research, 26(1), 38-52. https://doi.org/10.1177/0739456X0528511
Jenks, M. (2000). The acceptability of urban intensification. In: Williams, K., Burton. E., & Jenks, M., (editors). Achieving Sustainable Urban Form. E & FN Spon. pp. 242-250.
Lagarias, A., & Stratigea, A. (2023). Coastalization patterns in the Mediterranean: a spatiotemporal analysis of coastal urban sprawl in tourism destination areas. GeoJournal, 88, 2529–2552. https://doi.org/10.1007/s10708-022-10756-8
Longjit, C., & Pearce, D. G. (2013). Managing a mature coastal destination: Pattaya, Thailand. Journal of Destination Marketing & Management, 2(3), 165–175. https://doi.org/10.1016/j.jdmm.2013.05.002
Maneethorn, E., Rugchoochip, K., Sangsunt, Y., et al. (2023). Innovation Application Toward Strategic Development of Pattaya City Administration from Viewpoints of Visitors Visiting Pattaya City, Chonburi Province, Thailand. International Journal of Sustainable Development and Planning, 18(6), 1813–1821. https://doi.org/10.18280/ijsdp.180616
Mansury, Y., Anantsuksomsri, S., & Tontisirin, N. (2021). New landscape of data and sustainable development in Asia. Regional Science Policy & Practice, 13(6), 1724–1728. https://doi.org/10.1111/rsp3.12487
Mathanraj, S., Rusli, N., & Ling, G. H. T. (2021). Applicability of the CA-Markov Model in Land-use/Land cover Change Prediction for Urban Sprawling in Batticaloa Municipal Council, Sri Lanka. IOP Conference Series: Earth and Environmental Science, 620, 012015. https://doi.org/10.1088/1755-1315/620/1/012015
Ministry of Tourism & Sports. (2019). Domestic Tourism Statistics Q1-Q4 (Classify by region and province). Available online: https://www.mots.go.th/news/category/618 (accessed on 10 December 2023).
Mondal, M. S., Sharma, N., Garg, P. K., et al. (2016). Statistical independence test and validation of CA Markov land use land cover (LULC) prediction results. The Egyptian Journal of Remote Sensing and Space Science, 19(2), 259–272. https://doi.org/10.1016/j.ejrs.2016.08.001
Osman, T., Shaw, D., & Kenawy, E. (2018). An integrated land use change model to simulate and predict the future of greater Cairo metropolitan region. Journal of Land Use Science, 13(6), 565–584. https://doi.org/10.1080/1747423x.2019.1581849
Pawlukiewicz, M., Gupta, P. K., & Koelbel, C. (2007). Ten Principles for Coastal Development. ULI-the Urban Land Institute.
Pongpisitkul, P. & Khumpaisal, S. (2021). A Development of Design and Management Guidelines for Condominium Projects to Enhance the Decision Making of the Investors: Case Studies of Pattaya City. Journal of Architectural/Planning Research and Studies (JARS), 18(2), 71–86. https://doi.org/10.56261/jars.v18i2.240132
Pontius, R. G., & Schneider, L. (2001). Land-cover change model validation by an ROC method for the Ipswich watershed, Massachusetts, USA. Agriculture, Ecosystems & Environment, 85, 239-248. https://doi.org/10.1016/S0167-8809(01)00187-6
Robino, D. M. (2019). Global Destination Cities Index. Available online: https://www.mastercard.com/news/media/wexffu4b/gdci-global-report-final-1.pdf (accessed on 10 December 2023).
Sang, L., Zhang, C., Yang, J., et al. (2011). Simulation of land use spatial pattern of towns and villages based on CA–Markov model. Mathematical and Computer Modelling, 54(3–4), 938–943. https://doi.org/10.1016/j.mcm.2010.11.019
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(3), 659–692. https://doi.org/10.1177/0042098007087340
Senawongse, P., & Eiumnoh, A. (2019). Decision Support System Module for Sustainable Land Development for Thailand: A Case of Chonburi Province. Journal of Sustainable Development, 12(3), 159. https://doi.org/10.5539/jsd.v12n3p159
Steven, A., Appeaning Addo, K., Llewellyn, G., et al (2020). Coastal Development: Resilience, Restoration and Infrastructure Requirements LEAD AUTHORS About the High-Level Panel for a Sustainable Ocean Economy. Available online: www.oceanpanel.org/blue-papers/coastal-development-resilience-restoration-and-infrastructure- (accessed on 10 December 2023).
Tian, Y., & Chen, J. (2022). Suburban sprawl measurement and landscape analysis of cropland and ecological land: A case study of Jiangsu Province, China. Growth and Change, 53(3), 1282–1305. Portico. https://doi.org/10.1111/grow.12608
Wang, Y., Hu, Y., Niu, X., et al. (2022). Land Use/Cover Change and Its Driving Mechanism in Thailand from 2000 to 2020. Land, 11(12), 2253. https://doi.org/10.3390/land11122253
Wilson, E., Hurd, J., Civco, D., et al. (2003). Development of a geospatial model to quantify, describe and map urban growth. Remote Sensing of Environment, 86(3), 275-285. https://doi.org/10.1016/S0034-4257(03)00074-9
Yi, L., Ma, S., Tao, S., et al. (2022). Coastal landscape pattern optimization based on the spatial distribution heterogeneity of ecological risk. Frontiers in Marine Science, 9. https://doi.org/10.3389/fmars.2022.1003313
Yılmaz, M., & Terzi, F. (2021). Measuring the patterns of urban spatial growth of coastal cities in developing countries by geospatial metrics. Land Use Policy, 107, 105487. https://doi.org/10.1016/j.landusepol.2021.105487
Zhang, C., Zhong, S., Wang, X., et al. (2019). Land Use Change in Coastal Cities during the Rapid Urbanization Period from 1990 to 2016: A Case Study in Ningbo City, China. Sustainability, 11(7), 2122. https://doi.org/10.3390/su11072122
DOI: https://doi.org/10.24294/jipd.v8i9.8141
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