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

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.

저자정보

  • 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
  • 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

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