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Modeling Future Urban Sprawl and Landscape Change in the Laguna de Bay Area, Philippines

Author

Listed:
  • Kotaro Iizuka

    (Center for Southeast Asian Studies (CSEAS), Kyoto University, 46, Yoshida Shimoadachicho, Sakyo-ku Kyoto-shi, Kyoto 606-8501, Japan)

  • Brian A. Johnson

    (Institute for Global Environmental Strategies (IGES), 2108-11 Kamiyamaguchi, Hayama, Kanagawa 240-0115, Japan)

  • Akio Onishi

    (Faculty of Environmental Studies, Tokyo City University, 3-3-1 Ushikubo-nishi, Tsuzuki-ku, Yokohama, Kanagawa 224-8551, Japan)

  • Damasa B. Magcale-Macandog

    (Institute of Biological Sciences, University of the Philippines Los Baños, College, Laguna 4031, Philippines)

  • Isao Endo

    (Institute for Global Environmental Strategies (IGES), 2108-11 Kamiyamaguchi, Hayama, Kanagawa 240-0115, Japan)

  • Milben Bragais

    (Institute of Biological Sciences, University of the Philippines Los Baños, College, Laguna 4031, Philippines)

Abstract

This study uses a spatially-explicit land-use/land-cover (LULC) modeling approach to model and map the future (2016–2030) LULC of the area surrounding the Laguna de Bay of Philippines under three different scenarios: ‘business-as-usual’, ‘compact development’, and ‘high sprawl’ scenarios. The Laguna de Bay is the largest lake in the Philippines and an important natural resource for the population in/around Metro Manila. The LULC around the lake is rapidly changing due to urban sprawl, so local and national government agencies situated in the area need an understanding of the future (likely) LULC changes and their associated hydrological impacts. The spatial modeling approach involved three main steps: (1) mapping the locations of past LULC changes; (2) identifying the drivers of these past changes; and (3) identifying where and when future LULC changes are likely to occur. Utilizing various publically-available spatial datasets representing potential drivers of LULC changes, a LULC change model was calibrated using the Multilayer Perceptron (MLP) neural network algorithm. After calibrating the model, future LULC changes were modeled and mapped up to the year 2030. Our modeling results showed that the ‘built-up’ LULC class is likely to experience the greatest increase in land area due to losses in ‘crop/grass’ (and to a lesser degree ‘tree’) LULC, and this is attributed to continued urban sprawl.

Suggested Citation

  • Kotaro Iizuka & Brian A. Johnson & Akio Onishi & Damasa B. Magcale-Macandog & Isao Endo & Milben Bragais, 2017. "Modeling Future Urban Sprawl and Landscape Change in the Laguna de Bay Area, Philippines," Land, MDPI, vol. 6(2), pages 1-21, April.
    • Handle: RePEc:gam:jlands:v:6:y:2017:i:2:p:26-:d:95830
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    Citations

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    Cited by:

    1. Syed Amir Manzoor & Geoffrey Griffiths & David Christian Rose & Martin Lukac, 2021. "The Return of Wooded Landscapes in Wales: An Exploration of Possible Post-Brexit Futures," Land, MDPI, vol. 10(1), pages 1-15, January.
    2. Rifat, Shaikh Abdullah Al & Liu, Weibo, 2022. "Predicting future urban growth scenarios and potential urban flood exposure using Artificial Neural Network-Markov Chain model in Miami Metropolitan Area," Land Use Policy, Elsevier, vol. 114(C).
    3. Shigeaki F. Hasegawa & Takenori Takada, 2019. "Probability of Deriving a Yearly Transition Probability Matrix for Land-Use Dynamics," Sustainability, MDPI, vol. 11(22), pages 1-11, November.
    4. Syed Amir Manzoor & Aisha Malik & Muhammad Zubair & Geoffrey Griffiths & Martin Lukac, 2019. "Linking Social Perception and Provision of Ecosystem Services in a Sprawling Urban Landscape: A Case Study of Multan, Pakistan," Sustainability, MDPI, vol. 11(3), pages 1-15, January.
    5. Monika Kopecká & Harini Nagendra & Andrew Millington, 2018. "Urban Land Systems: An Ecosystems Perspective," Land, MDPI, vol. 7(1), pages 1-4, January.
    6. Kelsee Bratley & Eman Ghoneim, 2018. "Modeling Urban Encroachment on the Agricultural Land of the Eastern Nile Delta Using Remote Sensing and a GIS-Based Markov Chain Model," Land, MDPI, vol. 7(4), pages 1-21, October.
    7. Shamik Chakraborty & Ram Avtar & Raveena Raj & Huynh Vuong Thu Minh, 2019. "Village Level Provisioning Ecosystem Services and Their Values to Local Communities in the Peri-Urban Areas of Manila, The Philippines," Land, MDPI, vol. 8(12), pages 1-18, November.

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