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Projecting Urbanization and Landscape Change at Large Scale Using the FUTURES Model

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  • Derek Van Berkel

    (Center for Geospatial Analytics, North Carolina State University, Raleigh, NC 27695, USA
    School for Environment and Sustainability, University of Michigan, Ann Arbor, MI 48109, USA
    Current address: School for Environment and Sustainability, University of Michigan, Dana Building, 440 Church Street Ann Arbor, MI 48109, USA.)

  • Ashwin Shashidharan

    (Center for Geospatial Analytics, North Carolina State University, Raleigh, NC 27695, USA
    Department of Computer Science, North Carolina State University, Raleigh, NC 27695, USA)

  • Rua S. Mordecai

    (U.S. Fish & Wildlife Service, South Atlantic Landscape Conservation Cooperative, Raleigh, NC 27699, USA)

  • Raju Vatsavai

    (Center for Geospatial Analytics, North Carolina State University, Raleigh, NC 27695, USA
    Department of Computer Science, North Carolina State University, Raleigh, NC 27695, USA)

  • Anna Petrasova

    (Center for Geospatial Analytics, North Carolina State University, Raleigh, NC 27695, USA)

  • Vaclav Petras

    (Center for Geospatial Analytics, North Carolina State University, Raleigh, NC 27695, USA)

  • Helena Mitasova

    (Center for Geospatial Analytics, North Carolina State University, Raleigh, NC 27695, USA
    Department of Marine, Earth and Atmospheric Sciences, North Carolina State University, Raleigh, NC 27695, USA)

  • John B. Vogler

    (Center for Geospatial Analytics, North Carolina State University, Raleigh, NC 27695, USA)

  • Ross K. Meentemeyer

    (Center for Geospatial Analytics, North Carolina State University, Raleigh, NC 27695, USA
    Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC 27695, USA)

Abstract

Increasing population and rural to urban migration are accelerating urbanization globally, permanently transforming natural systems over large extents. Modelling landscape change over large regions, however, presents particular challenges due to local-scale variations in social and environmental factors that drive land change. We simulated urban development across the South Atlantic States (SAS), a region experiencing rapid population growth and urbanization, using FUTURES—an open source land change model that uses demand for development, local development suitability factors, and a stochastic patch growing algorithm for projecting alternative futures of urban form and landscape change. New advances to the FUTURES modelling framework allow for high resolution projections over large spatial extents by leveraging parallel computing. We simulated the adoption of different urban growth strategies that encourage settlement densification in the SAS as alternatives to the region’s increasing sprawl. Evaluation of projected patterns indicate a 15% increase in urban lands by 2050 given a status quo development scenario compared to a 14.8% increase for the Infill strategy. Status quo development resulted in a 3.72% loss of total forests, 2.97% loss of highly suitable agricultural land, and 3.69% loss of ecologically significant lands. An alternative Infill scenario resulted in similar losses of total forest (3.62%) and ecologically significant lands (3.63%) yet consumed less agricultural lands (1.23% loss). Moreover, infill development patterns differed qualitatively from the status quo and resulted in less fragmentation of the landscape.

Suggested Citation

  • Derek Van Berkel & Ashwin Shashidharan & Rua S. Mordecai & Raju Vatsavai & Anna Petrasova & Vaclav Petras & Helena Mitasova & John B. Vogler & Ross K. Meentemeyer, 2019. "Projecting Urbanization and Landscape Change at Large Scale Using the FUTURES Model," Land, MDPI, vol. 8(10), pages 1-28, September.
    • Handle: RePEc:gam:jlands:v:8:y:2019:i:10:p:144-:d:270144
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    References listed on IDEAS

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    1. Brian Pickard & Joshua Gray & Ross Meentemeyer, 2017. "Comparing Quantity, Allocation and Configuration Accuracy of Multiple Land Change Models," Land, MDPI, vol. 6(3), pages 1-21, August.
    2. Magliocca, Nicholas & McConnell, Virginia & Walls, Margaret, 2015. "Exploring sprawl: Results from an economic agent-based model of land and housing markets," Ecological Economics, Elsevier, vol. 113(C), pages 114-125.
    3. Robert Pontius & Wideke Boersma & Jean-Christophe Castella & Keith Clarke & Ton Nijs & Charles Dietzel & Zengqiang Duan & Eric Fotsing & Noah Goldstein & Kasper Kok & Eric Koomen & Christopher Lippitt, 2008. "Comparing the input, output, and validation maps for several models of land change," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(1), pages 11-37, March.
    4. Neumann, Kathleen & Verburg, Peter H. & Stehfest, Elke & Müller, Christoph, 2010. "The yield gap of global grain production: A spatial analysis," Agricultural Systems, Elsevier, vol. 103(5), pages 316-326, June.
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    Cited by:

    1. Yang Gao & Zhen Shen & Yuexin Liu & Chaoyue Yu & Lihan Cui & Cuiling Song, 2023. "Optimization of differentiated regional land development patterns based on urban expansion simulation—A case in China," Growth and Change, Wiley Blackwell, vol. 54(1), pages 45-73, March.
    2. Syafri Syafri & Batara Surya & Ridwan Ridwan & Syamsul Bahri & Emil Salim Rasyidi & Sudarman Sudarman, 2020. "Water Quality Pollution Control and Watershed Management Based on Community Participation in Maros City, South Sulawesi, Indonesia," Sustainability, MDPI, vol. 12(24), pages 1-39, December.

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