IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v8y2019i9p140-d268069.html
   My bibliography  Save this article

Predicting Urban Expansion and Urban Land Use Changes in Nakhon Ratchasima City Using a CA-Markov Model under Two Different Scenarios

Author

Listed:
  • Pakawan Chotchaiwong

    (Inter-disciplinary Program, Environmental Science, Graduate School, Chulalongkorn University, Phayathai Road, Pathumwan, Bangkok 10330, Thailand)

  • Saowanee Wijitkosum

    (Environmental Research Institute, Chulalongkorn University, Phayathai Road, Pathumwan, Bangkok 10330, Thailand)

Abstract

This study focused on the prediction of land-use changes in Nakhon Ratchasima city using a CA-Markov Model with GIS. Satellite images taken by Landsat-5 (1992), Landsat-7 (2002) and THEOS (2016) were used to predict land use in 2026. In 1992, the most proportion of land usage was built-up areas (47.76%) and followed by green areas (37.45%), bare lands (13.19%), and water bodies (1.60%), respectively. In 2002, the land use comprised built-up areas (56.04%), green areas (35.52%), bare lands (4.80%) and water bodies (3.63%). By 2016, urbanisation had changed the land use pattern, which comprised built-up areas (70.80%), green areas (20.78%), bare lands (6.37%), and water bodies (2.03%). The data were analysed using a change detection matrix and revealed an increase in built-up area at the expense of all other types, especially green areas. The results were in accordance with the prediction model created in two scenarios. Scenario 1 assumed city expansion following past trends, built-up areas (85.88%), green areas (11.67%), bare lands (2.15%), and water bodies (0.30%). Scenario 2 assumed city expansion in accordance with the national strategy, built-up areas (74.91%), green areas (15.77%), bare lands (8.48%), and water bodies (0.84%). The results indicated an expansion of built-up areas and a shrinking of green areas. In Scenario 2, urban expansion was less than in Scenario 1, and preserving the green area seemed more feasible due to governmental restrictions. The results indicated that planning the urbanisation according to the policies development plans, especially in specific areas, contributed to a more efficient urbanisation growth. The city should provide to promote the use of floor area ratio (FAR) and open space ratio (OSR) with urban planning measures as well as increasing the green areas.

Suggested Citation

  • Pakawan Chotchaiwong & Saowanee Wijitkosum, 2019. "Predicting Urban Expansion and Urban Land Use Changes in Nakhon Ratchasima City Using a CA-Markov Model under Two Different Scenarios," Land, MDPI, vol. 8(9), pages 1-16, September.
    • Handle: RePEc:gam:jlands:v:8:y:2019:i:9:p:140-:d:268069
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/8/9/140/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/8/9/140/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. K C Clarke & S Hoppen & L Gaydos, 1997. "A Self-Modifying Cellular Automaton Model of Historical Urbanization in the San Francisco Bay Area," Environment and Planning B, , vol. 24(2), pages 247-261, April.
    2. Chen Liping & Sun Yujun & Sajjad Saeed, 2018. "Monitoring and predicting land use and land cover changes using remote sensing and GIS techniques—A case study of a hilly area, Jiangle, China," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-23, July.
    3. R White & G Engelen & I Uljee, 1997. "The Use of Constrained Cellular Automata for High-Resolution Modelling of Urban Land-Use Dynamics," Environment and Planning B, , vol. 24(3), pages 323-343, June.
    4. Yang, Xin & Zheng, Xin-Qi & Lv, Li-Na, 2012. "A spatiotemporal model of land use change based on ant colony optimization, Markov chain and cellular automata," Ecological Modelling, Elsevier, vol. 233(C), pages 11-19.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yingting He & Chuyu Xia & Zhuang Shao & Jing Zhao, 2022. "The Spatiotemporal Evolution and Prediction of Carbon Storage: A Case Study of Urban Agglomeration in China’s Beijing-Tianjin-Hebei Region," Land, MDPI, vol. 11(6), pages 1-25, June.
    2. Qing Lu & Jing Ning & Hong You & Liyan Xu, 2023. "Urban Intensity in Theory and Practice: Empirical Determining Mechanism of Floor Area Ratio and Its Deviation from the Classic Location Theories in Beijing," Land, MDPI, vol. 12(2), pages 1-16, February.
    3. Wang, Quan & Wang, Haijun & Chang, Ruihan & Zeng, Haoran & Bai, Xuepiao, 2022. "Dynamic simulation patterns and spatiotemporal analysis of land-use/land-cover changes in the Wuhan metropolitan area, China," Ecological Modelling, Elsevier, vol. 464(C).
    4. Yang Chen & Wenze Yue & Xue Liu & Linlin Zhang & Ye’an Chen, 2021. "Multi-Scenario Simulation for the Consequence of Urban Expansion on Carbon Storage: A Comparative Study in Central Asian Republics," Land, MDPI, vol. 10(6), pages 1-17, June.
    5. Jing Liu & Chunchun Hu & Xionghua Kang & Fei Chen, 2023. "A Loosely Coupled Model for Simulating and Predicting Land Use Changes," Land, MDPI, vol. 12(1), pages 1-19, January.
    6. Xueru Zhang & Jie Zhou & Wei Song, 2020. "Simulating Urban Sprawl in China Based on the Artificial Neural Network-Cellular Automata-Markov Model," Sustainability, MDPI, vol. 12(11), pages 1-13, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liu, Dongya & Zheng, Xinqi & Zhang, Chunxiao & Wang, Hongbin, 2017. "A new temporal–spatial dynamics method of simulating land-use change," Ecological Modelling, Elsevier, vol. 350(C), pages 1-10.
    2. Cheechouyang Faichia & Zhijun Tong & Jiquan Zhang & Xingpeng Liu & Emmanuel Kazuva & Kashif Ullah & Bazel Al-Shaibah, 2020. "Using RS Data-Based CA–Markov Model for Dynamic Simulation of Historical and Future LUCC in Vientiane, Laos," Sustainability, MDPI, vol. 12(20), pages 1-20, October.
    3. Zaheer Abbas & Guang Yang & Yuanjun Zhong & Yaolong Zhao, 2021. "Spatiotemporal Change Analysis and Future Scenario of LULC Using the CA-ANN Approach: A Case Study of the Greater Bay Area, China," Land, MDPI, vol. 10(6), pages 1-26, June.
    4. Ruci Wang & Hao Hou & Yuji Murayama, 2018. "Scenario-Based Simulation of Tianjin City Using a Cellular Automata–Markov Model," Sustainability, MDPI, vol. 10(8), pages 1-20, July.
    5. Cong Cao & Suzana Dragićević & Songnian Li, 2019. "Short-Term Forecasting of Land Use Change Using Recurrent Neural Network Models," Sustainability, MDPI, vol. 11(19), pages 1-18, September.
    6. Auwalu Faisal Koko & Wu Yue & Ghali Abdullahi Abubakar & Roknisadeh Hamed & Akram Ahmed Noman Alabsi, 2020. "Monitoring and Predicting Spatio-Temporal Land Use/Land Cover Changes in Zaria City, Nigeria, through an Integrated Cellular Automata and Markov Chain Model (CA-Markov)," Sustainability, MDPI, vol. 12(24), pages 1-21, December.
    7. Sonam Wangyel Wang & Belay Manjur Gebru & Munkhnasan Lamchin & Rijan Bhakta Kayastha & Woo-Kyun Lee, 2020. "Land Use and Land Cover Change Detection and Prediction in the Kathmandu District of Nepal Using Remote Sensing and GIS," Sustainability, MDPI, vol. 12(9), pages 1-18, May.
    8. Wang, Han & Tian, Fuan & Wu, Jianxian & Nie, Xin, 2023. "Is China forest landscape restoration (FLR) worth it? A cost-benefit analysis and non-equilibrium ecological view," World Development, Elsevier, vol. 161(C).
    9. Youjung Kim & Galen Newman, 2019. "Climate Change Preparedness: Comparing Future Urban Growth and Flood Risk in Amsterdam and Houston," Sustainability, MDPI, vol. 11(4), pages 1-24, February.
    10. Michel Opelele Omeno & Ying Yu & Wenyi Fan & Tolerant Lubalega & Chen Chen & Claude Kachaka Sudi Kaiko, 2021. "Analysis of the Impact of Land-Use/Land-Cover Change on Land-Surface Temperature in the Villages within the Luki Biosphere Reserve," Sustainability, MDPI, vol. 13(20), pages 1-23, October.
    11. Meisam Jafari & Hamid Majedi & Seyed Masoud Monavari & Ali Asghar Alesheikh & Mirmasoud Kheirkhah Zarkesh, 2016. "Dynamic Simulation of Urban Expansion Based on Cellular Automata and Logistic Regression Model: Case Study of the Hyrcanian Region of Iran," Sustainability, MDPI, vol. 8(8), pages 1-18, August.
    12. Han, Yu & Jia, Haifeng, 2017. "Simulating the spatial dynamics of urban growth with an integrated modeling approach: A case study of Foshan, China," Ecological Modelling, Elsevier, vol. 353(C), pages 107-116.
    13. Yusuyunjiang Mamitimin & Zibibula Simayi & Ayinuer Mamat & Bumairiyemu Maimaiti & Yunfei Ma, 2023. "FLUS Based Modeling of the Urban LULC in Arid and Semi-Arid Region of Northwest China: A Case Study of Urumqi City," Sustainability, MDPI, vol. 15(6), pages 1-14, March.
    14. Shivangi S. Somvanshi & Oshin Bhalla & Phool Kunwar & Madhulika Singh & Prafull Singh, 2020. "Monitoring spatial LULC changes and its growth prediction based on statistical models and earth observation datasets of Gautam Budh Nagar, Uttar Pradesh, India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(2), pages 1073-1091, February.
    15. Brian Pickard & Joshua Gray & Ross Meentemeyer, 2017. "Comparing Quantity, Allocation and Configuration Accuracy of Multiple Land Change Models," Land, MDPI, vol. 6(3), pages 1-21, August.
    16. Eda Ustaoglu & Brendan Williams & Laura O. Petrov & Harutyun Shahumyan & Hedwig Van Delden, 2017. "Developing and Assessing Alternative Land-Use Scenarios from the MOLAND Model: A Scenario-Based Impact Analysis Approach for the Evaluation of Rapid Rail Provisions and Urban Development in the Greate," Sustainability, MDPI, vol. 10(1), pages 1-34, December.
    17. Harik, G. & Alameddine, I. & Zurayk, R. & El-Fadel, M., 2023. "Uncertainty in forecasting land cover land use at a watershed scale: Towards enhanced sustainable land management," Ecological Modelling, Elsevier, vol. 486(C).
    18. Vitus Tankpa & Li Wang & Alfred Awotwi & Leelamber Singh & Samit Thapa & Raphael Ane Atanga & Xiaomeng Guo, 2021. "Modeling the effects of historical and future land use/land cover change dynamics on the hydrological response of Ashi watershed, northeastern China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(5), pages 7883-7912, May.
    19. A’kif AL-FUGARA & Abdel Rahman AL-SHABEEB & Yahya AL-SHAWABKEH & Hani AL-AMOUSH & Rida AL-ADAMAT, 2018. "Simulation And Prediction Of Urban Spatial Expansion In Highly Vibrant Cities Using The Sleuth Model: A Case Study Of Amman Metropolitan, Jordan," Theoretical and Empirical Researches in Urban Management, Research Centre in Public Administration and Public Services, Bucharest, Romania, vol. 13(1), pages 37-56, February.
    20. Dawid Kudas & Agnieszka Wnęk & Ľubica Hudecová & Robert Fencik, 2024. "Spatial Diversity Changes in Land Use and Land Cover Mix in Central European Capitals and Their Commuting Zones from 2006 to 2018," Sustainability, MDPI, vol. 16(6), pages 1-16, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:8:y:2019:i:9:p:140-:d:268069. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.