Binary Logit Model을 이용한 신갈나무와 졸참나무의 출현확률 추정
Estimation of the Occurrence Probability for Quercus mongolica and Quercus serrata Using Binary Logit Model
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초록
본 연구에서는 신갈나무와 졸참나무 임분의 입지환경인자 및 기후인자 자료를 활용하여 출현확률을평가하였으며, 자료 분석은 Binary logit model을 이용하였다. 추정 결과, 신갈나무는 해발이 높고, 산복이나 산정의 지형에서 확률이 높게 나타난 반면 졸참나무는 대체로 해발고가 높지 않으며, 평탄지와완구릉지에 비하여 산록과 산복의 지형에서 확률이 증가되는 경향이 나타났다. 그 외 적색산림토양군의토성을 가지는 지형과 점토군이 아닌 미사군과 모래군으로 갈수록 출현확률이 높아지는 공통적인 특성이 나타났다. 본 연구의 결과는 장기적인 산림경영 측면에서 조림수종 선정에 유용하게 활용 될 수 있을 것으로 사료된다.
Abstract
This study was carried out to assess the occurrence probability for Q. mongolica and Q. serrata stands using environmental and climatic data. About the analysis method of data therewas used binary logit model analysis. As a result of estimation, the occurrence probability of Q. mongolica increased at high altitude and hillside-top of a mountain. On the other hand, the highoccurrence probability of Q. serrata had relatively not high altitude, and the foot and hillside ofa mountain had tended to increase compared with flat land and gentle hillside. Besides, it hadcommon feature that the probability of appearance increased when it came to land with redforest soil group, and tiny sand group and sand group rather than clay group. Result of thisstudy can be used as a useful resource for selecting afforestation tree in terms of long-termforest management.
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