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2024 Vol.66, Issue 3
Comparative Analysis of DTM Generation Method for Stream Area Using UAV-Based LiDAR and SfM

여름철 UAV 기반 LiDAR, SfM을 이용한 하천 DTM 생성 기법 비교 분석

Jaejun Goua
,
Hyeokjin Leeb
,
Jinseok Parkc
,
Seongju Jangd
,
Jonghyuk Leee
,
Dongwoo Kimf
,
Inhong Songg†
고 재준a
,
이 혁진b
,
박 진석c
,
장 성주d
,
이 종혁e
,
김 동우f
,
송 인홍g†
aM.S. Student, Department of Rural Systems Engineering, Global Smart Farm Convergence Major, Seoul National University
bPh.D. Student, Department of Rural Systems Engineering, Global Smart Farm Convergence Major, Seoul National University
cPh.D. Student, Department of Rural Systems Engineering, Global Smart Farm Convergence Major, Seoul National University
dPh.D. Student, Department of Rural Systems Engineering, Global Smart Farm Convergence Major, Seoul National University
ePh.D. Student, Department of Rural Systems Engineering, College of Agriculture and Life Sciences, Seoul National University
fM.S. Student, Department of Rural Systems Engineering, Global Smart Farm Convergence Major, Seoul National University
gAssociate Professor, Department of Rural Systems Engineering, Global Smart Farm Convergence Major, Research Institute of Agriculture and Life Sciences, Seoul National University
a서울대학교 농촌시스템공학과 글로벌스마트팜융합전공 M.S. 학생
b서울대학교 농촌시스템공학과 글로벌스마트팜융합전공 박사과정생
c서울대학교 농촌시스템공학과 글로벌스마트팜융합전공 박사과정생
d서울대학교 농촌시스템공학과 글로벌스마트팜융합전공 박사과정생
e서울대학교 농생명과학대학 농촌시스템공학과 박사과정 학생
f서울대학교 농촌시스템공학과 글로벌스마트팜융합전공 M.S. 학생
g서울대학교 농업생명과학연구소 농촌시스템공학과 글로벌스마트팜융합전공 부교수
† Corresponding author Tel.: +82-2-880-4581, Fax: +82-2-873-2087 E-mail: inhongs@snu.ac.kr
2024. pp. 1-14
PDF XML Citation
Abstract

Gaining an accurate 3D stream geometry has become feasible with Unmanned Aerial Vehicle (UAV), which is crucial for better understanding stream hydrodynamic processes. The objective of this study was to investigate series of filters to remove stream vegetation and propose the best method for generating Digital Terrain Models (DTMs) using UAV-based point clouds. A stream reach approximately 500 m of the Bokha stream in Icheon city was selected as the study area. Point clouds were obtained in August 1st, 2023, using Phantom 4 multispectral and Zenmuse L1 for Structure from Motion (SfM) and Light Detection And Ranging (LiDAR) respectively. Three vegetation filters, two morphological filters, and six composite filters which combined vegetation and morphological filters were applied in this study. The Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were used to assess each filters comparing with the two cross-sections measured by leveling survey. The vegetation filters performed better in SfM, especially for short vegetation areas, while the morphological filters demonstrated superior performance on LiDAR, particularly for taller vegetation areas. Overall, the composite filters combining advantages of two types of filters performed better than single filter application. The best method was the combination of Progressive TIN (PTIN) and Color Indicies of Vegetation Extraction (CIVE) for SfM, showing the smallest MAE of 0.169 m. The proposed method in this study can be utilized for constructing DTMs of stream and thus contribute to improving the accuracy of stream hydrodynamic simulations.

Keywords
DTM
LiDAR
morphological filter
SfM
vegetation filter
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Information
  • Publisher :The Korean Society of Agricultural Engineers
  • Publisher(Ko) :한국농공학회
  • Journal Title :Journal of Korean Society of Agricultural Engineers
  • Journal Title(Ko) :한국농공학회논문집
  • Volume : 66
  • No :3
  • Pages :1-14
  • Received Date : 2024-01-21
  • Revised Date : 2024-03-29
  • Accepted Date : 2024-04-01
  • DOI :https://doi.org/10.5389/KSAE.2024.66.3.001
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