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Mapping Urban Transitions Using Multi-Temporal Landsat and DMSP-OLS Night-Time Lights Imagery of the Red River Delta in Vietnam

Author

Listed:
  • Miguel Castrence

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

  • Duong H. Nong

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

  • Chinh C. Tran

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

  • Luisa Young

    (International Development, Community and Environment, Clark University, 950 Main Street, Worcester, MA 01610, USA)

  • Jefferson Fox

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

Abstract

The urban transition that has emerged over the past quarter century poses new challenges for mapping land cover/land use change (LCLUC). The growing archives of imagery from various earth-observing satellites have stimulated the development of innovative methods for change detection in long-term time series. We tested two different multi-temporal remote sensing datasets and techniques for mapping the urban transition. Using the Red River Delta of Vietnam as a case study, we compared supervised classification of dense time stacks of Landsat data with trend analyses of an annual series of night-time lights (NTL) data from the Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS). The results of each method were corroborated through qualitative and quantitative GIS analyses. We found that these two approaches can be used synergistically, combining the advantages of each to provide a fuller understanding of the urban transition at different spatial scales.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jlands:v:3:y:2014:i:1:p:148-166:d:32863
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    References listed on IDEAS

    as
    1. Jörn P W Scharlemann & David Benz & Simon I Hay & Bethan V Purse & Andrew J Tatem & G R William Wint & David J Rogers, 2008. "Global Data for Ecology and Epidemiology: A Novel Algorithm for Temporal Fourier Processing MODIS Data," PLOS ONE, Public Library of Science, vol. 3(1), pages 1-13, January.
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    Cited by:

    1. Shahtahmassebi, Amir Reza & Wu, Chun & Blackburn, George Alan & Zheng, Qing & Huang, Lingyan & Shortridge, Ashton & Shahtahmassebi, Golnaz & Jiang, Ruowei & He, Shan & Wang, Ke & Lin, Yue & Clarke, Ke, 2018. "How do modern transportation projects impact on development of impervious surfaces via new urban area and urban intensification? Evidence from Hangzhou Bay Bridge, China," Land Use Policy, Elsevier, vol. 77(C), pages 479-497.
    2. 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.
    3. Bhagawat Rimal & Lifu Zhang & Dongjie Fu & Ripu Kunwar & Yongguang Zhai, 2017. "Monitoring Urban Growth and the Nepal Earthquake 2015 for Sustainability of Kathmandu Valley, Nepal," Land, MDPI, vol. 6(2), pages 1-23, June.

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