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Detection of Trees with Pine Wilt Disease Using Object-based Classification Method

원문정보

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영어

In this study, regions infected by pine wilt disease were extracted by using object-based classification method (OB-infected region), and the characteristics of special distribution about OB-infected region were figured out. Scale 24, Shape 0.1, Color 0.9, Compactness 0.5, and Smoothness 0.5 was selected as the objected-based, optimal weighted value of OB-infected region classification. The total accuracy of classification was high with 99% and Kappa coefficient was also high with 0.97. The area of OB-infected region was approximately 90 ha, 16% of the total area. The OB-infected region in Age class V and VI was intensively distributed with 97% of the total. Also, The OB-infected region in Middle and Large DBH class was intensively distributed with 99% of the total. In terms of the topographic characteristics of OB-infected region, the damages occurred approximately 86% below the altitude of 200 m, and occurred 91% with a slope less than 10 degree. The damage occurred a lot in low hilly mountain and undulating slope. In addition, the accessibility to road and residential area from OB-infected region was less than 300 m in large part. Overall, it was figured out that artificial effect is stronger than natural effect with regard to the spread of pine wilt disease.

목차

Abstract
 Introduction
 Materials and Methods
  Study area
  Study data
  Method
 Results and Discussion
  Classification of OB-infected region
 Conclusion
 References

저자정보

  • Jeongmook Park Department of Forest Management, College of Forest and Environmental Sciences, Kangwon National University, Chuncheon 24341, Republic of Korea
  • Woodam Sim Department of Forest Management, College of Forest and Environmental Sciences, Kangwon National University, Chuncheon 24341, Republic of Korea
  • Jungsoo Lee Department of Forest Management, College of Forest and Environmental Sciences, Kangwon National University, Chuncheon 24341, Republic of Korea

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