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다운로드

Comparison of Point Cloud Data Distribution and Characteristics According to LiDAR Operation Techniques in Korean Pine Forests

원문정보

초록

한국어
Precise forest inventory is crucial for sustainable forest management. Recently, LiDAR technology has been widely applied to forest inventory as it provides highly accurate measurements of tree height, canopy structure, and terrain, enabling efficient data collection and analysis. This study aims to (i) determine point cloud density of ground and vegetation layers classified from Handheld Mobile Laser Scanning (HMLS), Airborne Laser Scanning (ALS), and Integrated ALS and HMLS; (ii) compare DBH and tree height derived from HMLS, ALS, and Integrated ALS and HMLS, and (iii) analyse applicability of integrating HMLS and ALS scanning methods in estimate individual tree attributes of pine forests in South Korea. As a forthcoming LiDAR application, the fusion of ALS and HMLS method could transform forest inventory methods, overcoming the challenges of traditional ground-based surveys and enabling faster and more precise forest evaluations, which contributes to forest ecosystem assessment and carbon stock estimation.

저자

  • Lan Thi Ngoc Tran [ Forest Environment & Geospatial Technology Research Institute, 58-3, Seongdeok 2-gil, Sejong, 30084, South Korea ]
  • Myeongjun Kim [ Forest Environment & Geospatial Technology Research Institute, 58-3, Seongdeok 2-gil, Sejong, 30084, South Korea ] Corresponding Author
  • Hongseok Bang [ Forest Environment & Geospatial Technology Research Institute, 58-3, Seongdeok 2-gil, Sejong, 30084, South Korea ]
  • Byung Bae Park [ Forest Resources Department, Chungnam National University, 99, Daehak-ro, Daejeon, 34134, South Korea ]
  • Sung-Min Choi [ Korea Forest Engineer Institute, 809, Hanbat-daero, Daejeon, 35209, South Korea ]

참고문헌

자료제공 : 네이버학술정보

    간행물 정보

    • 간행물
      한국산림공학회 학술대회
    • 간기
      연간
    • 수록기간
      2023~2025
    • 십진분류
      KDC 526 DDC 634