여름철 UAV 기반 LiDAR, SfM을 이용한 하천 DTM 생성 기법 비교 분석
Comparative Analysis of DTM Generation Method for Stream Area Using UAV-Based LiDAR and SfM
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초록
Gaining an accurate 3D stream geometry has become feasible with Unmanned Aerial Vehicle (UAV), which is crucial for better understanding streamhydrodynamic processes. The objective of this study was to investigate series of filters to remove stream vegetation and propose the best method forgenerating Digital Terrain Models (DTMs) using UAV-based point clouds. A stream reach approximately 500 m of the Bokha stream in Icheon citywas selected as the study area. Point clouds were obtained in August 1st, 2023, using Phantom 4 multispectral and Zenmuse L1 for Structure fromMotion (SfM) and Light Detection And Ranging (LiDAR) respectively. Three vegetation filters, two morphological filters, and six composite filters whichcombined vegetation and morphological filters were applied in this study. The Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) wereused to assess each filters comparing with the two cross-sections measured by leveling survey. The vegetation filters performed better in SfM, especiallyfor 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 combinationof Progressive TIN (PTIN) and Color Indicies of Vegetation Extraction (CIVE) for SfM, showing the smallest MAE of 0.169 m. The proposed methodin this study can be utilized for constructing DTMs of stream and thus contribute to improving the accuracy of stream hydrodynamic simulations.
Abstract
Gaining an accurate 3D stream geometry has become feasible with Unmanned Aerial Vehicle (UAV), which is crucial for better understanding streamhydrodynamic processes. The objective of this study was to investigate series of filters to remove stream vegetation and propose the best method forgenerating Digital Terrain Models (DTMs) using UAV-based point clouds. A stream reach approximately 500 m of the Bokha stream in Icheon citywas selected as the study area. Point clouds were obtained in August 1st, 2023, using Phantom 4 multispectral and Zenmuse L1 for Structure fromMotion (SfM) and Light Detection And Ranging (LiDAR) respectively. Three vegetation filters, two morphological filters, and six composite filters whichcombined vegetation and morphological filters were applied in this study. The Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) wereused to assess each filters comparing with the two cross-sections measured by leveling survey. The vegetation filters performed better in SfM, especiallyfor 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 combinationof Progressive TIN (PTIN) and Color Indicies of Vegetation Extraction (CIVE) for SfM, showing the smallest MAE of 0.169 m. The proposed methodin this study can be utilized for constructing DTMs of stream and thus contribute to improving the accuracy of stream hydrodynamic simulations.
참고문헌 (34)
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