Techniques for Addressing Spatial Detail in Forest Planning

  • Howard Hoganson
  • Jose Borges
  • Dennis Bradley
Part of the Forestry Sciences book series (FOSC, volume 51)

Abstract

Specialized model solution approaches can be designed for forest management scheduling problems by utilizing an understanding of the problem. A specialized decomposition approach has made it possible to address larger problems. It has proven successful in applications. Concepts of moving windows from geographic information systems can be combined with dynamic programming (DP) techniques to address adjacency considerations in large problems. This DP approach and the specialized decomposition approach can likely be combined to help identify ways of sustaining both timber production and forest-wide spatial conditions such as the amount of forest edge or interior space. The specialized decomposition approach has been expanded to address spatial interactions between timber markets. Similar expansions seem plausible to address broader spatial environmental concerns related to forest biodiversity.

Keywords

Forest Management Forest Edge Management Unit Geographic Information System Forest Planning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Borges, J. 1994. A modelling approach to spatial management constraints in forest management. PhD dissertation. University of Minnesota. 117 pp.Google Scholar
  2. Church, R., A. Murray and K Barber. 1994. Designing a hierarchical planning model for USDA Forest Service planning. pp 401–409 in Proceedings of the 1994 Symposium on Systems Analysis in Forest Resources, Sept. 6–9, 1994, Pacific Grove, CA 482 p.Google Scholar
  3. Davis, L. S. and K. N. Johnson. 1987. Forest management. McGraw-Hill, New York. 790 p.Google Scholar
  4. Fisher, M. 1981. The Lagrangian relaxation method for solving integer programming problems. Management Science 27 (1): 1–18.CrossRefGoogle Scholar
  5. Hoganson, H. J. Borges and D. Rose. 1994. A dynamic programming approach to solving adjacency problems. in forest management. Paper presented at the 1994 Symposium on Systems Analysis in Forest Resources, September 6–9, 1994, Pacific Grove, California.Google Scholar
  6. Hoganson. H. and D. Kapple. 1995. Estimating impacts of extended rotation forestry. Final research report submitted to the Minnesota Department of Natural Resources. 170 pp.Google Scholar
  7. Hoganson, H. M. and D. C. Kapple. 1991. DTRAN 1.0: A multi-market timber supply model. College of Natural Resources and Agricultural Experiment Station, Department of Forest Resources Staff Paper Series Report No. 82, University of Minnesota, St. Paul. 66 pp.Google Scholar
  8. Hoganson, H., and M. McDill. 1993. Relating reforestation investments in northern Minnesota with forest industry needs, nontimber values and mitigation strategies. research report submitted to the Charles K. Blandin Foundation. 232 p.Google Scholar
  9. Hoganson, H. M. and D. W. Rose. 1984. A simulation approach for optimal timber management scheduling. Forest Science. 30 (1): 220–238.Google Scholar
  10. Hoganson, H. M. and D. W. Rose. 1989. DUALPLAN version 1.0 users manual. College of Natural Resources and Agricultural Experiment Station, Department of Forest Resources Staff Paper Series Report No. 73, University of Minnesota, St. Paul. 48 pp.Google Scholar
  11. Jaakko Pöyry Consulting, Inc. 1994. Generic Environmental Impact Statement on Timber Harvesting and Forest Management in Minnesota. Tarrytown, NY: Jaakko Pöyry Consulting, Inc. 813 p.Google Scholar
  12. Jones, J., J. Meneghin, and M. Kirby. 1991. Formulating adjacency constraints in optimization models for scheduling projects in tactical planning. Forest Science. 37 (5): 1283–1297.Google Scholar
  13. Mladenoff, D., G. Host, J. Boeder and T. Crow. 1996. A spatial model of forest landscape disturbance, succession and management. in: Goodchild, M. et al. eds. GIS and Environmental Modeling: progress and research issues. Fort Collins CO: GIS World Books: 175–179.Google Scholar
  14. Murray, A. T. and R. L. Church. 1994. Adjacency constraint aggregation. pp 131–138 in Proceedings of the International Symposium on Systems Analysis and Management Decisions in Forestry. March 9–12, 193, Valdivia, Chile. 482 p.Google Scholar
  15. Nelson, J., and D. Errico. 1993. Multiple pass harvesting and spatial constraints: an old technique applied to a new problem. Forest Science. 39 (1): 1–15.Google Scholar
  16. Paredes V., G., and J. Brodie. 1989. Land value and the linkage between stand and forest level analyses. Land Economics. 65 (2): 158–166.Google Scholar
  17. Sessions J. and J. Sessions. 1988. Scheduling and network analysis program (SNAP). User’s Guide. Dept. of Forest Management. Oregon State University. Corvallis OR.Google Scholar
  18. Snyder, S. and C. ReVelle. 1996. The grid packing problem: selecting a harvest pattern in an area with forbidden regions. Forest Science. 42 (1): 27–34.Google Scholar
  19. Weintraub, A., F. Barahona and R. Epstein. 1994. A column generation algorithm for solving general forest planning problems with adjacency constraints. Forest Science. 40 (1): 142–161.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 1998

Authors and Affiliations

  • Howard Hoganson
    • 1
  • Jose Borges
    • 2
  • Dennis Bradley
    • 3
  1. 1.Department of Forest ResourcesUniversity of MinnesotaGrand RapidsUSA
  2. 2.Departamento de Engenharia FlorestalInstituto Superior de AgronomiaLisboa CodexPortugal
  3. 3.North Central Forest Experiment StationUSDA Forest ServiceSt PaulUSA

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