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머신러닝기법을 활용한 가리왕산과 유명산 지역 주요 밀원수의 서식지 적합성 평가
Evaluation of Habitat Suitability of Major Honey Trees in the Mt. Gariwang and Mt. Yumeong through Machine Learning Approach 원문보기

한국농림기상학회지 = Korean Journal of Agricultural and Forest Meteorology, v.25 no.4, 2023년, pp.311 - 325  

이용주 (국민대학교 산림자원학과) ,  이민기 (국민대학교 산림자원학과) ,  이해인 (국민대학교 탄소흡수원 특성화대학원) ,  이창배 (국민대학교 산림자원학과) ,  심형석 (국민대학교 산림자원학과)

초록
AI-Helper 아이콘AI-Helper

본 연구는 가리왕산, 유명산에 자생하는 주요 밀원수종인 음나무, 벚나무류, 피나무류 및 쪽동백나무를 대상으로 머신러닝기법(i.e., MaxEnt)을 활용하여 서식지 적합성 분석을 수행하였다. 분석 결과, 모형의 예측정확도인 AUC 값은 대부분의 밀원수종이 0.7 이상이었으며, 주요 환경 변수에 대한 반응 곡선 결과 주요 밀원수종의 서식지 적합성에 영향을 미치는 환경적 요인은 고도, 연평균 강수량, 연평균 기온으로 나타났다. 이는 고도 구배에 따른 기후 인자가 주요 밀원수종의 분포 패턴 설명에 있어 주요한 환경 변수임을 의미한다. 본 연구는 우리나라 밀원수림의 조성 및 관리 전략수립 뿐만 아니라 밀원수종의 분포도 제작 시 근거 자료로써 기여할 수 있을 것이다. 향후 다양한 층위에서의 꿀과 화분의 생산량 증대 및 꿀의 주년 생산을 위해서는 생물학적 변수를 반영한 다양한 지역 단위의 추가적인 데이터 수집 및 분석이 필요할 것이다.

Abstract AI-Helper 아이콘AI-Helper

This study was conducted to analyze the habitat suitability of the major honey trees including Kalopanax septemlobus Koidz., Prunus spp., Tilia spp., and Styrax obassia Siebold & Zucc. indigenous to mountain Gariwang and Yumeong using the machine learning approach (i.e., MaxEnt model). The AUC value...

주제어

표/그림 (9)

참고문헌 (56)

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