A spatial approach to forest-management optimization: Linking GIS and multiple objective genetic algorithms

International Journal of Geographical Information Science

Volumn 20, Issue 8, 2006, Pages 917-928

  Ducheyne, E I ^a   De Wulf, R R ^b   De Baets, B ^b  

^a AVIA GIS   (Belgium)

^b GHENT UNIVERSITY   (Belgium)

Author keywords

Forest management optimization; Multiple objective genetic algorithms; Spatial approach

Indexed keywords

ENVIRONMENTAL PLANNING; FOREST MANAGEMENT; GENETIC ALGORITHM; GIS; OPTIMIZATION; REMOTE SENSING;

ABERDEEN [SCOTLAND]; EURASIA; EUROPE; SCOTLAND; UNITED KINGDOM; WESTERN EUROPE;

EID: 33749020276     PISSN: 13658816     EISSN: 17417546     Source Type: Journal    
DOI: 10.1080/13658810600711287     Document Type: Article

References (29)

1. Afdeling Bos en Groen. (2000). Beheersvisie voor de Domeinbossen, Andere Openbare Bossen en Bossen Gelegen in het VEN. Ministerie van de Vlaamse Gemeenschap, Brussels
2. Afdeling Bos en Groen. (2001). De Bosinventarisatie van het Vlaamse Gewest. Resultaten van de Eerste Inventarisatie 1997-1999. Ministerie van de Vlaamse Gemeenschap, Brussels
3. Baker, W. L. and Cai, Y. M. (1992) The R.Le. programs for multiscale analysis of landscape structure using the GRASS GIS geographical information system. Landscape Ecology, 7, pp. 291-302.
4. Baskent, E. Z. and Jordan, G. A. (1991) Spatial wood supply simulation modelling. The Forestry Chronicle, 67, pp. 610-621.
5. Brookes, C. J. (2001) A genetic algorithm for designing optimal patch configurations in GIS. International Journal of Geographical Information Science, 15, pp. 539-559.
6. Cameron, A. (2000). In Inventory Data Kirkhill Forest, Unpublished data
7. Chuvieco, E. (1993) Integration of linear programming and GIS for land-use modelling. International Journal of Geographic Information Systems, 7, pp. 71-83.
8. Cresswell, P. and Harris, S. and Jefferies, D. J. (1990). In The History, Distribution, Status and Habitat Requirements of the Badger in Britain. Peterborough: Nature Conservancy Council.
9. Davis, L. (1991). In Handbook of Genetic Algorithms. New York: Van Nostrand Reinhold.
10. Davis, L. S. and Johnson, K. N. and Bettinger, P. S. and Howard, T. E. (2001). In Forest Management. Boston MA: McGraw Hill.
11. Deb, K. and Agrawal, S. and Pratab, A. and Meyarivan, T. (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation 6, pp. 182-197.
12. Densham, P. J. (1991) Spatial decision support systems. In Geographical Information Systems. (pp. 403-413). London: Longman Scientific Technical.
13. Ducheyne, E. (2003) Multiple objective forest management using GIS and genetic optimisation techniques. In. PhD, University of Ghent
14. Ducheyne, E. and De Baets, B. and De Wulf, R. R. (2004a) Even flow scheduling problems in forest management. In Applications in Multiple Objective Evolutionary Computation. (pp. 701-727). World Scientific Press.
15. Ducheyne, E. and De Wulf, R. R. and De Baets, B. (2001) Bi-objective genetic algorithms for forest management: A comparative study. In Late Breaking Papers at the Genetic and Evolutionary Computation Conference. (pp. 63-66). San Francisco: AAAI.
16. Ducheyne, E. and De Wulf, R. R. and De Baets, B. (2004b) Single versus multiple objective genetic algorithms for solving the even-flow forest management problem. Forest Ecology and Management, 201, pp. 259-273.
17. Falçao, A.O. and Borges, J. G. (2001) Designing an evolution program for solving integer forest management scheduling models: An application in Portugal. Forest Science, 47, pp. 158-168.
18. Goldberg, D. E. (1989). In Genetic Algorithms in Search, Optimization, and Machine Learning. Reading MA: Addison-Wesley.
19. Hof, J. G. and Joyce, L. A. (1993) A mixed integer linear programming approach for spatially optimizing wildlife and timber in managed forest ecosystems. Forest Science, 39, pp. 816-834.
20. Holland, J. H. (1975). In Adaptation in Natural and Artificial Systems. Ann Arbor MI: University of Michigan Press.
21. Kurttila, M. (2001) The spatial structure of forests in the optimization calculations of forest planning - a landscape ecological perspective. Forest Ecology and Management, 142, pp. 129-142.
22. Matthews, K. B. and Craw, S. and Elder, S. and Sibbald, A. R. and MacKenzie, I. (2000). Applying genetic algorithms to multi-objective land use planning. In Proceedings of the 2001 Genetic and Evolutionary Computation Conference [pp. 613-620].
23. Matthews, K. B. and Sibbald, A. R. and Craw, S. (1999) Implementation of a spatial decision support system for rural land use planning: integrating geographic information systems and environmental models with search and optimisation models. Computer and Electronics in Agriculture, 23, pp. 9-26.
24. Misund, G. and Johansen, B. and Hasle, G. (1995). Integration of geographical information technology and constraint reasoning - a promising approach to forest management. In Proceedings of the 5th Research Conference on GIS [pp. 42-56].
25. Naesset, E. (1997a) A spatial decision support sytem for long-term forest management planning by means of linear pogramming and a geographical information system. Scandinavian Journal of Forest Research, 12, pp. 77-88.
26. Naesset, E. (1997b) Geographical information systems in long-term forest management and planning with special reference to preservation of biological diversity: A review. Forest Ecology and Management, 93, pp. 121-136.
27. Neteler, M. and Mitasova, H. (2002). In Open Source GIS: A GRASS GIS Approach. Boston MA: Kluwer Academic.
28. Olson, C. M. and Orr, B. (1999) Combining tree growth, fish and wildlife habitat, mass wasting, sedimentation, and hydrologic models in decision analysis and long-term forest planning. Forest Ecology and Management, 114, pp. 339-348.
29. Twery, M. J. and Rauscher, H. M. and Bennet, D. J. and Thomasma, S. A. and Stout, S. L. and Palmer, J. F. and Hoffman, R. E. and DeCalesta, D. S. and Gustafson, E. and Cleveland, H. and Grove, H. M. and Nute, D. and Kim, G. and Kullasch, R. P. (2000) NED-1: Integrated analyses for forest stewardship decisions. Computers and Electronics in Agriculture, 27, pp. 167-193.