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Built-up Area Change Analysis in Hanoi Using Support Vector Machine Classification of Landsat Multi-Temporal Image Stacks and Population Data

Author

Listed:
  • Duong H. Nong

    (East-West Center, 1601 East-West Road, Honolulu, HI 96848, USA)

  • Jefferson Fox

    (East-West Center, 1601 East-West Road, Honolulu, HI 96848, USA)

  • Tomoaki Miura

    (Department of Natural Resources and Environmental Management, University of Hawaii, 1901 East-West Road, Honolulu, HI 96822, USA)

  • Sumeet Saksena

    (East-West Center, 1601 East-West Road, Honolulu, HI 96848, USA)

Abstract

In 1986, the Government of Vietnam implemented free market reforms known as Doi Moi (renovation) that provided private ownership of farms and companies, and encouraged deregulation and foreign investment. Since then, the economy of Vietnam has achieved rapid growth in agricultural and industrial production, construction and housing, and exports and foreign investments, each of which have resulted in momentous landscape transformations. One of the most evident changes is urbanization and an accompanying loss of agricultural lands and open spaces. These rapid changes pose enormous challenges for local populations as well as planning authorities. Accurate and timely data on changes in built-up urban environments are essential for supporting sound urban development. In this study, we applied the Support Vector Machine classification (SVM) to multi-temporal stacks of Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) images from 1993 to 2010 to quantify changes in built-up areas. The SVM classification algorithm produced a highly accurate map of land cover change with an overall accuracy of 95%. The study showed that most urban expansion occurred in the periods 2001–2006 and 2006–2010. The analysis was strengthened by the incorporation of population and other socio-economic data. This study provides state authorities a means to examine correlations between urban growth, spatial expansion, and other socio-economic factors in order to not only assess patterns of urban growth but also become aware of potential environmental, social, and economic problems.

Suggested Citation

  • Duong H. Nong & Jefferson Fox & Tomoaki Miura & Sumeet Saksena, 2015. "Built-up Area Change Analysis in Hanoi Using Support Vector Machine Classification of Landsat Multi-Temporal Image Stacks and Population Data," Land, MDPI, vol. 4(4), pages 1-19, December.
  • Handle: RePEc:gam:jlands:v:4:y:2015:i:4:p:1213-1231:d:60813
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    References listed on IDEAS

    as
    1. Miguel Castrence & Duong H. Nong & Chinh C. Tran & Luisa Young & Jefferson Fox, 2014. "Mapping Urban Transitions Using Multi-Temporal Landsat and DMSP-OLS Night-Time Lights Imagery of the Red River Delta in Vietnam," Land, MDPI, vol. 3(1), pages 1-19, February.
    2. Anne Welle-Strand & Monica Vlaicu & Arild Tjeldvoll, 2013. "Vietnam – A New Economic Dragon in Southeast Asia?," Journal of Developing Societies, , vol. 29(2), pages 155-187, June.
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    Cited by:

    1. Nguyen, Quang & Kim, Doo-Chul, 2020. "Reconsidering rural land use and livelihood transition under the pressure of urbanization in Vietnam: A case study of Hanoi," Land Use Policy, Elsevier, vol. 99(C).
    2. Duong H Nong & Christopher A Lepczyk & Tomoaki Miura & Jefferson M Fox, 2018. "Quantifying urban growth patterns in Hanoi using landscape expansion modes and time series spatial metrics," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-18, May.

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