Korean Journal of Agricultural and Forest Meteorology (한국농림기상학회지)

Korean Society of Agricultural and Forest Meteorology (한국농림기상학회)
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Analysis of Burn Severity in Large-fire Area Using SPOT5 Images and Field Survey Data

SPOT5영상과 현장조사자료를 융합한 대형산불지역의 피해강도 분석

  • Won, Myoungsoo (Division of Forest Disaster Management, Korea Forest Research Institute) ;
  • Kim, Kyongha (Division of Forest Disaster Management, Korea Forest Research Institute) ;
  • Lee, Sangwoo (Department of Environmental Science, Konkuk University)
  • 원명수 (국립산림과학원 산림방재연구과) ;
  • 김경하 (국립산림과학원 산림방재연구과) ;
  • 이상우 (건국대학교 환경과학과)
  • Received : 2014.05.30
  • Accepted : 2014.06.24
  • Published : 2014.06.30
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Abstract

For classifying fire damaged areas and analyzing burn severity of two large-fire areas damaged over 100 ha in 2011, three methods were employed utilized supervised classification, unsupervised classification and Normalized Difference Vegetation Index (NDVI). In this paper, the post-fire imageries of SPOT were used to compute the Maximum Likelihood (MLC), Minimum Distance (MIN), ISODATA, K-means, NDVI and to evaluate large-scale patterns of burn severity from 1 m to 5 m spatial resolutions. The result of the accuracy verification on burn severity from satellite images showed that average overall accuracy was 88.38 % and the Kappa coefficient was 0.8147. To compare the accuracy between burn severity and field survey at Uljin and Youngduk, two large fire sites were selected as study areas, and forty-four sampling plots were assigned in each study area for field survey. The burn severities of the study areas were estimated by analyzing burn severity (BS) classes from SPOT images taken one month after the occurrence of the fire. The applicability of composite burn index (CBI) was validated with a correlation analysis between field survey data and burn severity classified by SPOT5, and by their confusion matrix. The result showed that correlation between field survey data and BS by SPOT5 were closely correlated in both Uljin (r = -0.544 and p<0.01) and Youngduk (r = -0.616 and p<0.01). Thus, this result supported that the proposed burn severity analysis is an adequate method to measure burn severity of large fire areas in Korea.

본 연구는 2011년 100ha 이상의 대형산불 피해지인 울진과 영덕지역을 대상으로 하였으며 산불피해강도를 평가하기 위해 현장조사와 고해상도 위성영상자료 분석을 병행하였다. 위성영상자료 분석 시 산불피해지역의 피해강도를 가장 적절하게 평가할 수 있는 영상분류기법들을 비교 분석하여 최적의 피해강도 평가방법을 선정하였다. 대형산불 피해지역의 최적의 피해강도 평가기법으로는 현장조사에서 획득한 트레이닝 지역의 정보를 이용한 최대우도법을 적용하였을 때 가장 좋은 평가결과를 보였다. 산불피해강도의 정확도 검증 결과, 평균 전체정확도는 88.38%와 Kappa coefficient는 0.8147로 나타났다. 분류정확도는 최대우도법, NDVI, 최소거리법 순으로 나타났다. 산불피해강도 현장조사 결과와 위성영상자료에서 추출한 피해강도의 상관관계는 울진산불 피해지에서 r = -0.544, 영덕산불 피해지는 r = -0.616으로 나타났다.

Keywords

References

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