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Journals / İstatistik Araştırma Dergisi / 2008 / Cilt: 6 - Sayı: 1

A Boolean Approach in Forest Management

Orman Yönetiminde Boolean Yaklaşımı

Nurcan TEMİZ
Vahap TECİM
Pages
111–122
Publication Date
2008-07-15
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

IDRISI Software Package is used for all analyses.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Multi criteria analyses have been used mostly to deal with spatial decision problems since their emergence.
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Key Findings & Data:Spatial multi criteria analysis is different from conventional multi criteria decision analysis (MCDA).
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Conclusion & Impact:IDRISI Software Package is used for all analyses.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Boolean analizi · Orman yangını yönetimi · Coğrafi bilgi sistemleri

Abstract

Multi criteria analyses have been used mostly to deal with spatial decision problems since their emergence. Spatial multi criteria analysis is different from conventional multi criteria decision analysis (MCDA). Because it includes a geographic component. Multi criteria evaluation (MCE) and multi criteria decision making (MCDM) are very important concepts in Geographical Information Systems (GIS). Many spatial decision problems entail GIS and MCDA integration. GIS-MCDM integration can be thought of a process that uses value judgements and then represents results of these judgements spatially on a digital map. Forestry decision problems involve many alternatives and evaluation criteria. Most of the forest management problems are spatial in their nature and usually involve multi criteria. Fire management is an important component of forest management. In this study Boolean approach is used for the fire management. The areas that can cope with fire effectively are examined according to their distances from water resources, streams and settlement areas criteria for İzmir Forest Administration Chief Office by using Boolean approach. IDRISI Software Package is used for all analyses.

Özet

Çok kriterli karar problemleri ortaya çıkışlarından beri büyük ölçüde konumsal (mekansal) karar problemlerini çözmek için kullanılmıştır. Konumsal çok kriterli karar analizi, klasik Çok Kriterli Karar Analizi (ÇKKA)’dan farklıdır. Çünkü coğrafi bileşen içermektedir. Çok Kriterli Değerlendirme (ÇKD) ve Çok Kriterli Karar Verme (ÇKKV, Coğrafi Bilgi Sistemleri (CBS) oldukça önemli kavramlardır. Birçok konumsal karar problemi CBS ve ÇKKA’nın entegrasyonunu gerektirmektedir. CBS-ÇKKV entegrasyonu, çıkarımları kullanan ve daha sonra bu çıkarımların sonuçlarını konumsal olarak sayısal harita üzerinde gösteren bir süreç olarak düşünülebilir. Ormancılıkla ilgili karar problemleri birçok alternatifi ve değerlendirme kriterini içermektedir. Çoğu orman yönetimi problemi yapısal olarak konumsaldır ve genellikle çoklu kriter içermektedir. Yangın yönetimi, orman yönetiminin önemli bir bileşenidir. Bu çalışmada yangın yönetiminde Boolean yaklaşımı kullanılmıştır. İzmir Orman İşletme Şefliği için yangınla etkin olarak mücadele edebilen alanlar; su kaynaklarından uzaklık, akarsulardan uzaklık, yerleşim birimlerinden uzaklık kriterlerine göre incelenmiştir. Tüm analizler için IDRISI paket programı kullanılmıştır

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Cite This Article

TEMİZ, N., TECİM, V. (2008). A Boolean Approach in Forest Management. İstatistik Araştırma Dergisi, Cilt: 6 - Sayı: 1, 111–122. https://ajindex.com/articles/853680

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References (11)

  1. Ananda, J., Herath, G., 2003. The use of analytic hierarchy process to incorporate stakeholder preferences into regional forest planning. Forest Policy and Economics, 5, 13–26.
  2. Aronoff, S., 1995. Geographic information systems: A management perspective. WDL Publications, Ottawa. Banai, R., 1993. Fuzziness in geographical information systems: Contributions from an analytic hierarchy process. International Journal of Geographical Information Systems, 7, 315–329.
  3. Carver, S.J., 1991. Integrating multi criteria evaluation with geographical information systems. International Journal of Geographical Information Systems, 5, 321-339.
  4. Chakhar, S., Martel, J-M., 2003. Enhancing geographical information systems capabilities with multi criteria evaluation functions. Journal of Geographic Information and Decision Analysis, 7 (2), 47-71.
  5. DeMers, M., 1997. Fundamentals of geographic information systems. John Wiley&Sons Inc., New York. Eastman, J. Ronald., 2003. Idrisi Klimanjaro tutorial. Clark Labs Clark University. Worchester, USA. Evans, A.J., Kingston, R., Carver, S., 2004. Democratic input into the nuclear waste disposal problem: The influence of geographical data on decision making examined through a Web-based GIS. Journal of Geographical Systems, 6, 117–132.
  6. Franklin, S.E., 2001. Remote sensing for sustainable forest management. CRC Press LLC., USA. Goodchild, M.F., 2003. Geographic information science and systems for environmental management. Annual Review of Environment and Resources, 28, 493-519.
  7. Heywood, I., Cornelius, S., Carver, S., 2002. An introduction to geographical information systems (2nd Edition). Prentice Hall, Inc., United Kingdom. Jankowski, P., 1995. Integrating geographical information systems and multiple criteria decision-making methods. International Journal of Geographical Information Science, 9, 251-273.
  8. Jiang, H., Eastman, J.R., 2000. Application of fuzzy measures in multi criteria evaluation in GIS. International Journal of Geographical Information Systems. 14, 173–184.
  9. Jumppanen, J., Kurttila, M., Pukkala, T., Uuttera, J., 2003. Spatial harvest scheduling approach for areas involving multiple ownership. Forest Policy and Economics, 5, 27-38.
  10. Kangas, J., Store, R., Leskinen, P., Mehtätalo, L., 2000. Improving the quality of landscape ecological forest planning by utilising advanced decision support tools. Forest Ecology and Management, 132, 157-171.
  11. Kazana, V., Fawcett, R.H., Mutch, W.E.S., 2003. A decision support modeling framework for mu