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Remote Sensing for Natural Resources    2023, Vol. 35 Issue (3) : 107-115     DOI: 10.6046/zrzyyg.2022300
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Factors influencing the terrain modeling accuracy of UAV photogrammetry based on Monte Carlo tests of control points
CHEN Kai1,2(), WANG Chun1,2,3(), DAI Wen1, SHENG Yehua4,5, LIU Aili1, TANG Guoan4,5
1. School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China
2. School of Geographic Information and Tourism, Chuzhou University, Chuzhou 239000, China
3. Anhui Province Key Laboratory of Physical Geographic Environment, Chuzhou 239000, China
4. School of Geography, Nanjing Normal University, Nanjing 210023, China
5. Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210023, China
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Abstract  

Consumer-grade unmanned aerial vehicles (UAVs) each have a single camera and high lens distortion. The accuracy of terrain modeling using UAVs is influenced by route design and control surveys. By designing different data collection schemes and Monte Carlo tests, this study investigated the influence of the camera’s tilt angle, flight height, and the number of ground control points (GCPs) on terrain modeling accuracy in three small river basins on the Loess Plateau. The results are as follows: ① Before the processing of UAV photogrammetry data, it is necessary to analyze the quality of GCPs through Monte Carlo tests to eliminate GCP errors. ② The effects of the tilt angles of cameras include: in the case of no available GCPs, tilt photogrammetry with tilt angles of cameras can both improve the overall accuracy of the sampling area and optimize the spatial distribution of errors, with these advantages related to the optimization of the camera distortion model; in the case of available GCPs, the camera tilt angle has minor influence on elevation accuracy but affects the saturation number of GCPs. Compared with vertical photogrammetry, tilt photogrammetry requires slightly more GCPs to achieve the optimal accuracy. ③ The effects of the flight height include: in the case of no available GCPs, tilt photogrammetry can reduce the sensitivity of elevation accuracy to flight height; in the case of available GCPs, flight heights of 60~160 m have no significant influence on elevation accuracy, and the change in flight height does not affect the saturation number of GCPs.
Keywords UAV photogrammetry      terrain modeling      tilt photogrammetry      Monte Carlo test      route design      number of ground control points     
ZTFLH:  TP79  
Issue Date: 19 September 2023
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Kai CHEN
Chun WANG
Wen DAI
Yehua SHENG
Aili LIU
Guoan TANG
Cite this article:   
Kai CHEN,Chun WANG,Wen DAI, et al. Factors influencing the terrain modeling accuracy of UAV photogrammetry based on Monte Carlo tests of control points[J]. Remote Sensing for Natural Resources, 2023, 35(3): 107-115.
URL:  
https://www.gtzyyg.com/EN/10.6046/zrzyyg.2022300     OR     https://www.gtzyyg.com/EN/Y2023/V35/I3/107
Fig.1  Flight design and distribution of control points in the study area
Fig.2  Flowchart of UAV photogrammetry technology
样区 相机倾角/(°) 航高/m 飞行
架次		 地面分
辨率/cm
T1 0, 5, 10, 20, 30, 40, 50 100 7 2.7
T2 0, 5, 10, 20, 30, 40, 50 70 7 1.9
T3 0, 10, 20, 30, 40 80 5 2.2
Tab.1  Camera angle experiment of UAV photogrammetry
样区 航高/m 相机倾
角/(°)		 飞行
架次		 地面分
辨率/cm
T1 60, 80, 100, 120, 140, 160 0 7 1.6 ~ 4.4
T2 60, 80, 100, 120, 140, 160 15 6 1.6 ~ 4.4
Tab.2  UAV photogrammetry altitude experiment
Fig.3  Quality analysis of control points
Fig.4  Effect of camera inclination on RMSEZ
样区 相机倾角/(°)
0 10 30 40
T1
T2
Tab.3  Spatial distribution of check point error under different camera inclination
Tab.4  Autocorrelation model of camera parameters under different camera inclination
倾角/(°) T1样区 T2样区 T3样区
0
10
20
30
40
Tab.5  Monte Carlo test results of control points under different camera inclination in T1,T2,T3 sample area
Fig.5  Effect of altitude on RMSEZ
Fig.6  Monte Carlo test results of control points at different altitudes
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