Journal of Korean Society of Forest Science (한국산림과학회지)

Korean Society of Forest Science (한국산림과학회)
권호 표지

Assessment of Forest Biomass using k-Neighbor Techniques - A Case Study in the Research Forest at Kangwon National University -

k-NN기법을 이용한 산림바이오매스 자원량 평가 - 강원대학교 학술림을 대상으로 -

  • Seo, Hwanseok (Department of Forest Management, Kangwon National University) ;
  • Park, Donghwan (Department of Forest Management, Kangwon National University) ;
  • Yim, Jongsu (Forest Investigation Team, Korea Forestry Promotion Institute) ;
  • Lee, Jungsoo (Department of Forest Management, Kangwon National University)
  • 서환석 (강원대학교 산림경영학과) ;
  • 박동환 (강원대학교 산림경영학과) ;
  • 임종수 (한국임업진흥원 산림조사팀) ;
  • 이정수 (강원대학교 산림경영학과)
  • Published : 2012.12.31
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Abstract

This study purposed to estimate the forest biomass using k-Nearest Neighbor (k-NN) algorithm. Multiple data sources were used for the analysis such as forest type map, field survey data and Landsat TM data. The accuracy of forest biomass was evaluated with the forest stratification, horizontal reference area (HRA) and spatial filtering. Forests were divided into 3 types such as conifers, broadleaved, and Korean pine (Pinus koriansis) forests. The applied radii of HRA were 4 km, 5 km and 10 km, respectively. The estimated biomass and mean bias for conifers forest was 222 t/ha and 1.8 t/ha when the value of k=8, the radius of HRA was 4 km, and $5{\times}5$ modal was filtered. The estimated forest biomass of Korean pine was 245 t/ha when the value of k=8, the radius of HRA was 4km. The estimated mean biomass and mean bias for broadleaved forests were 251 t/ha and -1.6 t/ha, respectively, when the value of k=6, the radius of HRA was 10 km. The estimated total forest biomass by k-NN method was 799,000t and 237 t/ha. The estimated mean biomass by ${\kappa}NN$method was about 1t/ha more than that of filed survey data.

본 연구는 강원대학교 학술림을 대상으로 현장조사자료와 Landsat TM-5 위성영상 정보를 이용하여 k-NN기법을 통해 산림바이오매스를 추정하는 것을 목적으로 하였다. 임상 층화 및 최소수평 참조거리(HRA)와 공간필터링의 조건변화에 따른 최적의 참조표본점 개수(k)를 검토하였으며, 이에 따른 산림바이오매스량 추정과 정확도를 비교 분석하였다. 침엽수는 $5{\times}5$ 필터링을 적용한 HRA 4 km와 k=8를 적용하였을 때 최소의 RMSE를 나타냈으며, 편차는 1.8 t/ha으로 과대추정되었다. 한편, 잣나무와 활엽수는 필터링을 적용하지 않은 HRA 4km의 k=8과 HRA 10 km의 k=6을 적용하였을 때 최소의 RMSE가 나타났으며, 편차는 각각 -1.6 t/ha, -5.2 t/ha로 과소추정되었다. k-NN기법에 의하여 추정된 총 바이오매스량은 799천t이며, ha당 평균 산림바이오매스량은 237 t/ha로서 표본점자료를 이용한 추정치보다 약 1 t/ha 높게 나타났다.

Keywords

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