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논문 기본 정보

자료유형
학술저널
저자정보
Yeom, Junho (Gyeongsang National University) Han, Youkyung (Kyungpook National University) Kim, Taeheon (Kyungpook National University) Kim, Yongmin (LX Spatial Information Research Institute)
저널정보
한국측량학회 한국측량학회지 한국측량학회지 제37권 제5호
발행연도
2019.10
수록면
351 - 357 (7page)

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초록· 키워드

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UAV (Unmanned Aerial Vehicle) images can be exploited for rapid forest fire damage assessment by virtue of UAV systems’ advantages. In 2019, catastrophic forest fire occurred in Goseong and Sokcho, Korea and burned 1,757 hectares of forests. We visited the town in Goseong where suffered the most severe damage and conducted UAV flights for forest fire damage assessment. In this study, economic and rapid damage assessment method for forest fire has been proposed using UAV systems equipped with only a RGB sensor. First, forest masking was performed using automatic elevation thresholding to extract forest area. Then ExG (Excess Green) vegetation index which can be calculated without near-infrared band was adopted to extract damaged forests. In addition, entropy filtering was applied to ExG for better differentiation between damaged and non-damaged forest. We could confirm that the proposed forest masking can screen out non-forest land covers such as bare soil, agriculture lands, and artificial objects. In addition, entropy filtering enhanced the ExG homogeneity difference between damaged and non-damaged forests. The automatically detected damaged forests of the proposed method showed high accuracy of 87%.

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Abstract
1. Introduction
2. Methods
3. Results and Discussion
4. Conclusion
Reference

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UCI(KEPA) : I410-ECN-0101-2019-533-001289075