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Addressing risks and uncertainty in forest land use modeling

Author

Listed:
  • Alan T. Murray

    (University of California at Santa Barbara)

  • Ran Wei

    (University of California at Riverside)

  • Richard L. Church

    (University of California at Santa Barbara)

  • Matthew R. Niblett

    (University of California at Santa Barbara)

Abstract

The management of competing land uses is complicated by a range of issues and considerations. This is the case because of a concern for the long-term health of the earth and the obvious negative impacts of past and present human activities. Land use planning and management efforts have recognized this broader context and accordingly have devoted much care and attention to operational-level planning support. Spatial restrictions have long been recognized as central to limiting local impacts as well as ensuring landscape shape and structure irregularity. Unfortunately, planning to meet spatial restrictions may be disrupted, by fire, pests, or even on-the-ground conditions. For example, what if a fire destroys resources in a management unit that are adjacent to a unit(s) scheduled for harvest. In fact, this new opening/disruption may prevent the planned activity of any of its neighboring units. Disruptions do occur, but have rarely been addressed in any meaningful way in planning optimization problems. This paper details spatial optimization approaches to support better understanding of the range of potential outcomes when disruption and uncertainty are taken into account in land use planning involving forest resources. Application results highlight the significance of handling disruption risk and spatial data uncertainty, indicating that identifying and selecting planning alternatives that are consistent with goals and intended outcomes are a difficult task. However, improved modeling approaches are possible that better support land use decision making.

Suggested Citation

  • Alan T. Murray & Ran Wei & Richard L. Church & Matthew R. Niblett, 2019. "Addressing risks and uncertainty in forest land use modeling," Journal of Geographical Systems, Springer, vol. 21(3), pages 319-338, September.
  • Handle: RePEc:kap:jgeosy:v:21:y:2019:i:3:d:10.1007_s10109-019-00302-5
    DOI: 10.1007/s10109-019-00302-5
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    References listed on IDEAS

    as
    1. Mikael Rönnqvist & Sophie D’Amours & Andres Weintraub & Alejandro Jofre & Eldon Gunn & Robert Haight & David Martell & Alan Murray & Carlos Romero, 2015. "Operations Research challenges in forestry: 33 open problems," Annals of Operations Research, Springer, vol. 232(1), pages 11-40, September.
    2. Erkut, E. & ReVelle, C. & Ulkusal, Y., 1996. "Integer-friendly formulations for the r-separation problem," European Journal of Operational Research, Elsevier, vol. 92(2), pages 342-351, July.
    3. Marcos Goycoolea & Alan T. Murray & Francisco Barahona & Rafael Epstein & Andrés Weintraub, 2005. "Harvest Scheduling Subject to Maximum Area Restrictions: Exploring Exact Approaches," Operations Research, INFORMS, vol. 53(3), pages 490-500, June.
    4. I. Douglas Moon & Sohail S. Chaudhry, 1984. "An Analysis of Network Location Problems with Distance Constraints," Management Science, INFORMS, vol. 30(3), pages 290-307, March.
    5. Alan T. Murray & Tony H. Grubesic, 2012. "Spatial Optimization and Geographic Uncertainty: Implications for Sex Offender Management Strategies," International Series in Operations Research & Management Science, in: Michael P. Johnson (ed.), Community-Based Operations Research, chapter 0, pages 121-142, Springer.
    6. Alan Murray & Hyun Kim, 2008. "Efficient identification of geographic restriction conditions in anti-covering location models using GIS," Letters in Spatial and Resource Sciences, Springer, vol. 1(2), pages 159-169, December.
    7. Downs, Joni A. & Gates, Robert J. & Murray, Alan T., 2008. "Estimating carrying capacity for sandhill cranes using habitat suitability and spatial optimization models," Ecological Modelling, Elsevier, vol. 214(2), pages 284-292.
    8. Ran Wei & Alan Murray, 2015. "Spatial uncertainty in harvest scheduling," Annals of Operations Research, Springer, vol. 232(1), pages 275-289, September.
    9. Niblett, Matthew R. & Church, Richard L., 2015. "The disruptive anti-covering location problem," European Journal of Operational Research, Elsevier, vol. 247(3), pages 764-773.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Land use management; Adjacency; Disruption; Multiobjective optimization;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • Q15 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Land Ownership and Tenure; Land Reform; Land Use; Irrigation; Agriculture and Environment
    • Q23 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Forestry
    • R32 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Other Spatial Production and Pricing Analysis

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