Accuracy of Digital Surface Models and Orthophotos Derived from Unmanned Aerial Vehicle Photogrammetry

被引:105
作者
Aguera-Vega, Francisco [1 ,2 ]
Carvajal-Ramirez, Fernando [1 ,2 ]
Martinez-Carricondo, Patricio [3 ]
机构
[1] Univ Almeria, Dept Engn, La Canada De San Urbano 04120, Almeria, Spain
[2] Campus Excelencia Int Agroalimentario CeiA3, Cordoba 14005, Spain
[3] Drones Ingn Medioambiente & Arquitectura SL, Almeria 04120, Spain
关键词
Unmanned aerial vehicle (UAV); Photogrammetry; Digital surface model (DSM); Orthophoto; STRUCTURE-FROM-MOTION; UAV IMAGERY; LOW-COST; AIRCRAFT; SYSTEMS; TOOL; SFM;
D O I
10.1061/(ASCE)SU.1943-5428.0000206
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This paper explores the influence of flight altitude, terrain morphology, and the number of ground control points (GCPs) on digital surface model (DSM) and orthoimage accuracies obtained with unmanned aerial vehicle (UAV) photogrammetry. For this study, 60 photogrammetric projects were carried out considering five terrain morphologies, four flight altitudes (i.e., 50, 80, 100, and 120 m), and three different numbers of GCPs (i.e., 3, 5, and 10). The UAV was a rotatory wing platform with eight motors, and the sensor was a nonmetric mirrorless reflex camera. The root-mean-square error (RMSE) was used to assess the accuracy of the DSM (Z component) and orthophotos (X, Y, and XY components RMSEX, RMSEY, and RMSEXY, respectively). The results show that RMSEX, RMSEY, and RMSEXY were not influenced by flight altitude or terrain morphology. For horizontal accuracy, differences between terrain morphologies were observed only when 5 or 10 GCPs were used, which were the best accuracies for the flattest morphologies. Nevertheless, the number of GCPs influenced the horizontal accuracy; as the number of GCPs increased, the accuracy improved. Vertical accuracy was not influenced by terrain morphology, but both flight altitude and the number of GCPs had significant influences on RMSEZ; as the number of GCPs increased, the accuracy improved. Regarding flight altitude, vertical accuracy decreased as flight altitude increased. The most accurate combination of flight altitude and number of GCPs was 50 m and 10 GCPs, respectively, which yielded RMSEX, RMSEY, RMSEXY, and RMSEZ values equal to 0.038, 0.035, 0.053, and 0.049 m, respectively. In view of these results, the map scale according to the legacy American Society for Photogrammetry and Remote Sensing map standard of 1990 will be approximately 1:150, and an equivalent contour interval of 0.150 m is sufficient for most civil engineering projects. (C) 2016 American Society of Civil Engineers.
引用
收藏
页数:10
相关论文
共 40 条
[11]   Multi-temporal UAV data for automatic measurement of rill and interrill erosion on loess soil [J].
Eltner, Anette ;
Baumgart, Philipp ;
Maas, Hans-Gerd ;
Faust, Dominik .
EARTH SURFACE PROCESSES AND LANDFORMS, 2015, 40 (06) :741-755
[12]   IMAGE-BASED MODELLING FROM UNMANNED AERIAL VEHICLE (UAV) PHOTOGRAMMETRY: AN EFFECTIVE, LOW-COST TOOL FOR ARCHAEOLOGICAL APPLICATIONS [J].
Fernandez-Hernandez, J. ;
Gonzalez-Aguilera, D. ;
Rodriguez-Gonzalvez, P. ;
Mancera-Taboada, J. .
ARCHAEOMETRY, 2015, 57 (01) :128-145
[13]   Accurate, Dense, and Robust Multiview Stereopsis [J].
Furukawa, Yasutaka ;
Ponce, Jean .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2010, 32 (08) :1362-1376
[14]  
Hartley R., 2003, Multiple view geometry in computer vision
[15]   The Impact of the Calibration Method on the Accuracy of Point Clouds Derived Using Unmanned Aerial Vehicle Multi-View Stereopsis [J].
Harwin, Steve ;
Lucieer, Arko ;
Osborn, Jon .
REMOTE SENSING, 2015, 7 (09) :11933-11953
[16]   Assessing the Accuracy of Georeferenced Point Clouds Produced via Multi-View Stereopsis from Unmanned Aerial Vehicle (UAV) Imagery [J].
Harwin, Steve ;
Lucieer, Arko .
REMOTE SENSING, 2012, 4 (06) :1573-1599
[17]   Earthwork Volumetrics with an Unmanned Aerial Vehicle and Softcopy Photogrammetry [J].
Hugenholtz, Chris H. ;
Walker, Jordan ;
Brown, Owen ;
Myshak, Steve .
JOURNAL OF SURVEYING ENGINEERING, 2015, 141 (01)
[18]   Geomorphological mapping with a small unmanned aircraft system (sUAS): Feature detection and accuracy assessment of a photogrammetrically-derived digital terrain model [J].
Hugenholtz, Chris H. ;
Whitehead, Ken ;
Brown, Owen W. ;
Barchyn, Thomas E. ;
Moorman, Brian J. ;
LeClair, Adam ;
Riddell, Kevin ;
Hamilton, Tayler .
GEOMORPHOLOGY, 2013, 194 :16-24
[19]   High-resolution monitoring of Himalayan glacier dynamics using unmanned aerial vehicles [J].
Immerzeel, W. W. ;
Kraaijenbrink, P. D. A. ;
Shea, J. M. ;
Shrestha, A. B. ;
Pellicciotti, F. ;
Bierkens, M. F. P. ;
de Jong, S. M. .
REMOTE SENSING OF ENVIRONMENT, 2014, 150 :93-103
[20]   Acquisition, Orthorectification, and Object-based Classification of Unmanned Aerial Vehicle (UAV) Imagery for Rangeland Monitoring [J].
Laliberte, Andrea S. ;
Herrick, Jeffrey E. ;
Rango, Albert ;
Winters, Craig .
PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2010, 76 (06) :661-672