A Newly Developed Unmanned Aerial Vehicle (UAV) Imagery Based Technology for Field Measurement of Water Level
Ang Gao 1,2,*, Shiqiang Wu 1,2,*, Fangfang Wang 2, Xiufeng Wu 2, Peng Xu 2, Lei Yu 2 and Senlin Zhu 2
1
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
2
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing 210029, China
*
Authors to whom correspondence should be addressed.
Water 2019, 11(1), 124; https://doi.org/10.3390/w11010124
Received: 16 November 2018 / Revised: 30 December 2018 / Accepted: 8 January 2019 / Published: 11 January 2019
(This article belongs to the Special Issue Water Management Using Drones and Satellites in Agriculture)
Abstract
Field measurement of water level is important for water conservancy project operation and hydrological forecasting. In this study, we proposed a new measuring technique by integrating the advantages of unmanned aerial vehicle (UAV) photogrammetry and image recognition technology. Firstly, the imagery of water fluctuation process was captured by an UAV airborne camera, and water surface line in the imagery was recognized and extracted using image recognition technology. Subsequently, successive water levels at a measuring section were calculated by parameter calibration. Statistical parameters of water levels, such as maximum, average, and minimum values during the capturing period were also calculated. Additionally, we introduced a correction method to offset the error caused by UAV drift. The newly proposed method was tested in field measurement for Miaowei hydropower station, China, and the results showed that the method is reliable and adoptable. View Full-TextKeywords:
water level; water fluctuation; unmanned aerial vehicle; photogrammetry; image recognition; offset correction
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Gao, A.; Wu, S.; Wang, F.; Wu, X.; Xu, P.; Yu, L.; Zhu, S. A Newly Developed Unmanned Aerial Vehicle (UAV) Imagery Based Technology for Field Measurement of Water Level. Water 2019, 11, 124.
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