IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2020i1p308-d473041.html
   My bibliography  Save this article

Predictive Modeling of Transport Infrastructure Space for Urban Growth Phenomena in Developing Countries’ Cities: A Case Study of Kano — Nigeria

Author

Listed:
  • Suleiman Hassan Otuoze

    (Department of Civil Engineering, University of Birmingham, Edgbaston B15-2TT, UK
    Department of Civil Engineering, Ahmadu Bello University, Zaria 810107, Nigeria)

  • Dexter V. L. Hunt

    (Department of Civil Engineering, University of Birmingham, Edgbaston B15-2TT, UK)

  • Ian Jefferson

    (Department of Civil Engineering, University of Birmingham, Edgbaston B15-2TT, UK)

Abstract

Global urbanization has the most tremendous negative effects on the changing landscapes in many developing countries’ cities. It is necessary to develop appropriate monitoring techniques for tracking transport space evolution. The work explores the impacts of urban growth dynamics of transport space over the past decades as a basis for predicting future space demands in Kano, Nigeria. Three epochs of Landsat images from 1984, 2013 and 2019 were processed, classified and analyzed. Spatial classifications of land-use/land-cover (LULC) types in Kano include transport space, built-up areas, vegetation, farmland, bare land and water. The data analysis involves model calibration, validation and prediction using areas using the hybrid modeling techniques—cellular automata-Markov (CA-Markov) in IDIRISI SELVA 17.0 and remote-sensing ARC-GIS 10.7 softwares. The result finds significant expansion of transport and built-up areas while other LULC receded throughout the entire study period. Predictive modeling of transport infrastructure shows spatial expansion by 345 km 2 (3.9%) and 410 km 2 (11.7%) in 2030 and 2050 respectively. Kappa reliability indices of agreement ( K IA ) classified images and ground maps were 85%, 86% and 88%, respectively, for 1984, 2013 and 2019 time series. The calibration quality met the 80% minimum suggested in literature for the spatial-temporal track and prediction of urban growth phenomena.

Suggested Citation

  • Suleiman Hassan Otuoze & Dexter V. L. Hunt & Ian Jefferson, 2020. "Predictive Modeling of Transport Infrastructure Space for Urban Growth Phenomena in Developing Countries’ Cities: A Case Study of Kano — Nigeria," Sustainability, MDPI, vol. 13(1), pages 1-20, December.
    • Handle: RePEc:gam:jsusta:v:13:y:2020:i:1:p:308-:d:473041
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/1/308/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/1/308/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Bhagawat Rimal & Lifu Zhang & Nigel Stork & Sean Sloan & Sushila Rijal, 2018. "Urban Expansion Occurred at the Expense of Agricultural Lands in the Tarai Region of Nepal from 1989 to 2016," Sustainability, MDPI, vol. 10(5), pages 1-19, April.
    Full references (including those not matched with items on IDEAS)

    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. Md Fazlul Karim & Xiang Zhang & Ru Li, 2019. "Dynamics of Shrimp Farming in the Southwestern Coastal Districts of Bangladesh Using a Shrimp Yield Dataset (SYD) and Landsat Satellite Archives," Sustainability, MDPI, vol. 11(17), pages 1-24, August.
    2. Srijana Shrestha & Khem Narayan Poudyal & Nawraj Bhattarai & Mohan B. Dangi & John J. Boland, 2022. "An Assessment of the Impact of Land Use and Land Cover Change on the Degradation of Ecosystem Service Values in Kathmandu Valley Using Remote Sensing and GIS," Sustainability, MDPI, vol. 14(23), pages 1-18, November.
    3. Arturo Sanchez-Porras & María Guadalupe Tenorio-Arvide & Ricardo Darío Peña-Moreno & María Laura Sampedro-Rosas & Sonia Emilia Silva-Gómez, 2018. "Evaluation of the Potential Change to the Ecosystem Service Provision Due to Industrialization," Sustainability, MDPI, vol. 10(9), pages 1-20, September.
    4. 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).
    5. Kaize Zhang & Juqin Shen & Ran He & Bihang Fan & Han Han, 2019. "Dynamic Analysis of the Coupling Coordination Relationship between Urbanization and Water Resource Security and Its Obstacle Factor," IJERPH, MDPI, vol. 16(23), pages 1-16, November.
    6. 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.
    7. 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.
    8. Chengjie Yang & Ruren Li & Zongyao Sha, 2020. "Exploring the Dynamics of Urban Greenness Space and Their Driving Factors Using Geographically Weighted Regression: A Case Study in Wuhan Metropolis, China," Land, MDPI, vol. 9(12), pages 1-21, December.
    9. Muhammad Ishfaq Khan & Shahbaz Khalid & Umer Zaman & Ana Ercília José & Paulo Ferreira, 2021. "Green Paradox in Emerging Tourism Supply Chains: Achieving Green Consumption Behavior through Strategic Green Marketing Orientation, Brand Social Responsibility, and Green Image," IJERPH, MDPI, vol. 18(18), pages 1-24, September.
    10. Fuli Wang & Wei Fu & Jiancheng Chen, 2022. "Spatial–Temporal Evolution of Ecosystem Service Value in Yunnan Based on Land Use," Land, MDPI, vol. 11(12), pages 1-15, December.
    11. Bhanage Vinayak & Han Soo Lee & Shirishkumar Gedem, 2021. "Prediction of Land Use and Land Cover Changes in Mumbai City, India, Using Remote Sensing Data and a Multilayer Perceptron Neural Network-Based Markov Chain Model," Sustainability, MDPI, vol. 13(2), pages 1-22, January.
    12. Mohan Kumar Rai & Basanta Paudel & Yili Zhang & Pashupati Nepal & Narendra Raj Khanal & Linshan Liu & Raju Rai, 2023. "Appraisal of Empirical Studies on Land-Use and Land-Cover Changes and Their Impact on Ecosystem Services in Nepal Himalaya," Sustainability, MDPI, vol. 15(9), pages 1-19, April.
    13. Bao Meng & Xuxi Wang & Zhifeng Zhang & Pei Huang, 2022. "Spatio-Temporal Pattern and Driving Force Evolution of Cultivated Land Occupied by Urban Expansion in the Chengdu Metropolitan Area," Land, MDPI, vol. 11(9), pages 1-17, September.
    14. Muhammad Hadi Saputra & Han Soo Lee, 2019. "Prediction of Land Use and Land Cover Changes for North Sumatra, Indonesia, Using an Artificial-Neural-Network-Based Cellular Automaton," Sustainability, MDPI, vol. 11(11), pages 1-16, May.
    15. Zhongqi Deng & Qianyu Zhao & Helen X. H. Bao, 2020. "The Impact of Urbanization on Farmland Productivity: Implications for China’s Requisition–Compensation Balance of Farmland Policy," Land, MDPI, vol. 9(9), pages 1-24, September.
    16. Chen, Qi & Li, Xinyuan & Zhang, Zhengjia & Zhou, Chao & Guo, Zhiling & Liu, Zhengguang & Zhang, Haoran, 2023. "Remote sensing of photovoltaic scenarios: Techniques, applications and future directions," Applied Energy, Elsevier, vol. 333(C).
    17. Olayungbo, Adenike Anike, 2021. "Land Use Land Cover Change Detection Using Remote Geospatial Techniques: A Case Study of an Urban City in Southwestern, Nigeria," Problems of World Agriculture / Problemy Rolnictwa Światowego, Warsaw University of Life Sciences, vol. 21(2), June.
    18. Sushila Rijal & Bhagawat Rimal & Sean Sloan, 2018. "Flood Hazard Mapping of a Rapidly Urbanizing City in the Foothills (Birendranagar, Surkhet) of Nepal," Land, MDPI, vol. 7(2), pages 1-13, May.
    19. Raju Rai & Yili Zhang & Basanta Paudel & Narendra Raj Khanal, 2019. "Status of Farmland Abandonment and Its Determinants in the Transboundary Gandaki River Basin," Sustainability, MDPI, vol. 11(19), pages 1-18, September.
    20. Kun Wang & Yingkai Tang & Yaozhi Chen & Longwen Shang & Xuanming Ji & Mengchao Yao & Ping Wang, 2020. "The Coupling and Coordinated Development from Urban Land Using Benefits and Urbanization Level: Case Study from Fujian Province (China)," IJERPH, MDPI, vol. 17(16), pages 1-18, August.

    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:jsusta:v:13:y:2020:i:1:p:308-:d:473041. 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.