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Enhancing LiDAR-UAS Derived Digital Terrain Models with Hierarchic Robust and Volume-Based Filtering Approaches for Precision Topographic Mapping
被引:4
|作者:
Oniga, Valeria-Ersilia
[1
]
Loghin, Ana-Maria
[2
]
Macovei, Mihaela
[1
]
Lazar, Anca-Alina
[1
]
Boroianu, Bogdan
[3
]
Sestras, Paul
[4
,5
]
机构:
[1] Gheorghe Asachi Tech Univ Iasi, Fac Hydrotech Engn Geodesy & Environm Engn, Dept Terr Measurements & Cadastre, Prof Dimitrie Mangeron Blvd 67, Iasi 700050, Romania
[2] Fed Off Metrol & Surveying, Dept Remote Sensing, Schiffamtsgasse 1-3, A-1020 Vienna, Austria
[3] Geocad Profes SRL Smart Imaging & Mapping Serv SIM, Bucharest 022683, Romania
[4] Tech Univ Cluj Napoca, Fac Civil Engn, Dept Land Measurements & Cadastre, Cluj Napoca 400020, Romania
[5] Acad Romanian Scientists, Ilfov 3, Bucharest 050044, Romania
关键词:
LiDAR-UAS;
PPK;
DTM;
filtering approaches;
proposed method;
D O I:
10.3390/rs16010078
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
Airborne Laser Scanning (ALS) point cloud classification in ground and non-ground points can be accurately performed using various algorithms, which rely on a range of information, including signal analysis, intensity, amplitude, echo width, and return number, often focusing on the last return. With its high point density and the vast majority of points (approximately 99%) measured with the first return, filtering LiDAR-UAS data proves to be a more challenging task when compared to ALS point clouds. Various algorithms have been proposed in the scientific literature to differentiate ground points from non-ground points. Each of these algorithms has advantages and disadvantages, depending on the specific terrain characteristics. The aim of this research is to obtain an enhanced Digital Terrain Model (DTM) based on LiDAR-UAS data and to qualitatively and quantitatively compare three filtering approaches, i.e., hierarchical robust, volume-based, and cloth simulation, on a complex terrain study area. For this purpose, two flights over a residential area of about 7.2 ha were taken at 60 m and 100 m, with a DJI Matrice 300 RTK UAS, equipped with a Geosun GS-130X LiDAR sensor. The vertical and horizontal accuracy of the LiDAR-UAS point cloud, obtained via PPK trajectory processing, was tested using Check Points (ChPs) and manually extracted features. A combined approach for ground point classification is proposed, using the results from a hierarchic robust filter and applying an 80% slope condition for the volume-based filtering result. The proposed method has the advantage of representing with accuracy man-made structures and sudden slope changes, improving the overall accuracy of the DTMs by 40% with respect to the hierarchical robust filtering algorithm in the case of a 60 m flight height and by 28% in the case of a 100 m flight height when validated against 985 ChPs.
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页数:33
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