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Prediction of Land Use Change in Long Island Sound Watersheds Using Nighttime Light Data

Author

Listed:
  • Ruiting Zhai

    () (Department of Geography, University of Connecticut, 215 Glenbrook Rd., Storrs, CT 06269, USA)

  • Chuanrong Zhang

    () (Department of Geography, University of Connecticut, 215 Glenbrook Rd., Storrs, CT 06269, USA
    Center for Environmental Sciences and Engineering, University of Connecticut, 3107 Horsebarn Hill Rd., U-4210, Storrs, CT 06269, USA)

  • Weidong Li

    () (Department of Geography, University of Connecticut, 215 Glenbrook Rd., Storrs, CT 06269, USA
    Center for Environmental Sciences and Engineering, University of Connecticut, 3107 Horsebarn Hill Rd., U-4210, Storrs, CT 06269, USA)

  • Mark A. Boyer

    () (Department of Geography, University of Connecticut, 215 Glenbrook Rd., Storrs, CT 06269, USA
    Center for Environmental Sciences and Engineering, University of Connecticut, 3107 Horsebarn Hill Rd., U-4210, Storrs, CT 06269, USA)

  • Dean Hanink

    () (Department of Geography, University of Connecticut, 215 Glenbrook Rd., Storrs, CT 06269, USA)

Abstract

The Long Island Sound Watersheds (LISW) are experiencing significant land use/cover change (LUCC), which affects the environment and ecosystems in the watersheds through water pollution, carbon emissions, and loss of wildlife. LUCC modeling is an important approach to understanding what has happened in the landscape and what may change in the future. Moreover, prospective modeling can provide sustainable and efficient decision support for land planning and environmental management. This paper modeled the LUCCs between 1996, 2001 and 2006 in the LISW in the New England region, which experienced an increase in developed area and a decrease of forest. The low-density development pattern played an important role in the loss of forest and the expansion of urban areas. The key driving forces were distance to developed areas, distance to roads, and social-economic drivers, such as nighttime light intensity and population density. In addition, this paper compared and evaluated two integrated LUCC models—the logistic regression–Markov chain model and the multi-layer perception–Markov chain (MLP–MC) model. Both models achieved high accuracy in prediction, but the MLP–MC model performed slightly better. Finally, a land use map for 2026 was predicted by using the MLP–MC model, and it indicates the continued loss of forest and increase of developed area.

Suggested Citation

  • Ruiting Zhai & Chuanrong Zhang & Weidong Li & Mark A. Boyer & Dean Hanink, 2016. "Prediction of Land Use Change in Long Island Sound Watersheds Using Nighttime Light Data," Land, MDPI, Open Access Journal, vol. 5(4), pages 1-16, December.
  • Handle: RePEc:gam:jlands:v:5:y:2016:i:4:p:44-:d:84636
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    References listed on IDEAS

    as
    1. Wenjie Wang & Chuanrong Zhang & Jenica M. Allen & Weidong Li & Mark A. Boyer & Kathleen Segerson & John A. Silander, 2016. "Analysis and Prediction of Land Use Changes Related to Invasive Species and Major Driving Forces in the State of Connecticut," Land, MDPI, Open Access Journal, vol. 5(3), pages 1-22, July.
    2. Keola, Souknilanh & Andersson, Magnus & Hall, Ola, 2015. "Monitoring Economic Development from Space: Using Nighttime Light and Land Cover Data to Measure Economic Growth," World Development, Elsevier, vol. 66(C), pages 322-334.
    3. Christopher D. Elvidge & Daniel Ziskin & Kimberly E. Baugh & Benjamin T. Tuttle & Tilottama Ghosh & Dee W. Pack & Edward H. Erwin & Mikhail Zhizhin, 2009. "A Fifteen Year Record of Global Natural Gas Flaring Derived from Satellite Data," Energies, MDPI, Open Access Journal, vol. 2(3), pages 1-28, August.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    land use/cover change; Long Island Sound Watersheds; nighttime lights; logistic regression; multi-layer perception; Markov chain;

    JEL classification:

    • Q15 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Land Ownership and Tenure; Land Reform; Land Use; Irrigation; Agriculture and Environment
    • Q2 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation
    • Q24 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Land
    • Q28 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Government Policy
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics
    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns
    • R52 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Land Use and Other Regulations

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