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Detection of Surface Displacement in Timber Harvested Area and Mapping Erosion Risk by Classification Algorithm

첫 페이지 보기
  • 발행기관
    강원대학교 산림과학연구소 바로가기
  • 간행물
    강원대학교 산림과학연구소 학술대회 바로가기
  • 통권
    2022 International symposium of Institute of Forest Science for the 40th Anniversary of College of Forest and Environment Science (2022.10)바로가기
  • 페이지
    pp.136-136
  • 저자
    Jeongjae Kim, Ikhyun Kim, Eugene Ha, Byoungkoo Choi
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A450504

원문정보

초록

영어
Soil surface displacement occurs often following timber harvesting. This displacement is caused by canopy removal from the forest area which makes bare soil to be exposed directly to the rainfall. Thus, the displacement may differ in due to precipitation intensity, and this phenomenon results in the displacement prediction to be uncertain. In this study, we investigated on 1) calculating displacement on timber harvested area in research forest by photogrammetry method, and 2) assessing erosion risk of the area by using three different supervised machine learning classification models. Two time-series of point cloud data (PCD) were acquired by photogrammetry method from June 10, 2022 and July 9, 2022, respectively. These two PCD sets were registered by ground control point (GCP). For displacement estimation, DEM of difference (DoD) was calculated by subtracting DEMs from registered PCD sets. A total of nine terrain variables were generated for analyzing the spatial relationship between displacements and topographic features. Erosion risk was analyzed by three different classification algorithms: random forest (RF), extra gradient boost (XGB), logistic regression (LG). Best performed model was RF with overall accuracy (OA) of 72.9% followed by XGB model (72%), and LG model (71.7%). The results of this research indicate that machine learning based classification algorithms have better performances on erosion risk analysis than statistical algorithm through this research.

키워드

Surface Displacement Photogrammetry Timber harvesting Machine Learning Erosion Risk

저자

  • Jeongjae Kim [ Department of Forestry and Environmental Systems, Kangwon National University, Chuncheon 24341, Republic of Korea ]
  • Ikhyun Kim [ Department of Forestry and Environmental Systems, Kangwon National University, Chuncheon 24341, Republic of Korea ]
  • Eugene Ha [ Department of Forestry and Environmental Systems, Kangwon National University, Chuncheon 24341, Republic of Korea ]
  • Byoungkoo Choi [ Division of Forest Sciences, Kangwon National University, Chuncheon 24341, Republic of Korea ] Corresponding Author

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    강원대학교 산림과학연구소 [Institute of Forest Science Kangwon National University]
  • 설립연도
    1975
  • 분야
    농수해양>임학
  • 소개
    강원대학교부설산림과학연구소(이하 “연구소”라 한다)는 산림에 관한 제반 학술적 연구를 통하여 산림자원의 효용을 밝히고 임업 및 임산업의 발전에 기여함을 목적으로 한다.

간행물

  • 간행물명
    강원대학교 산림과학연구소 학술대회
  • 간기
    부정기
  • 수록기간
    2017~2024
  • 십진분류
    KDC 526 DDC 634

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