Estimation of Surface Soil Moisture by a Multi‐Elevation UAV‐Based Ground Penetrating Radar. Issue 2 (3rd February 2023)

• Record Type: Journal Article
• Authors: Cheng, Qinbo; Su, Qiuju; Binley, Andrew; liu, Jintao; Zhang, Zhicai; Chen, Xi
• Is Part Of: Water resources research. Volume 59:Issue 2(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-02-03
• Subjects: UAV -- GPR -- reflectivity -- permittivity -- soil moisture; Hydrology -- Periodicals; 333.91
• DOI: 10.1029/2022WR032621
• Languages: English
• ISSNs: 0043-1397

Abstract

Abstract: The measurement of soil moisture is important for a wide range of applications, including ecosystem conservation and agricultural management. However, most traditional measurement methods, for example, time‐domain reflectometry (TDR), are unsuitable for mapping field scale variability. In this study, we propose a method that uses an unmanned aerial vehicle (UAV) to support a ground penetrating radar (GPR) system for spatial scanning investigation at different elevations above ground level. This method measures the surface reflectivity to estimate the soil moisture, exploiting the linear relationship between the ratio of the reflected and the direct wave amplitudes along with the reciprocal of GPR antenna height. This relationship is deduced in this study based on the point source assumptions of a transmitter antenna and ground reflections, which is confirmed by numerical simulation results using the gprMax software. Unlike previous air‐launched GPR methods, the UAV‐GPR method presented here removes the limitations of a steady transmitter power and a fixed GPR survey height and the need for calibration of antenna transfer functions and geophysical inversion calculations, and thus is simpler and more convenient for field applications. We test the method at field sites within the riparian zone and a river‐island grassland adjacent to the Yangtze River. The results from the field study illustrate comparable measured soil moisture to those obtained invasively using TDR. The root mean square error of surface reflectivity and soil moisture values between UAV‐GPR with eight antenna height investigations and TDR in the grassland are 0.03 and 0.05 cm 3 /cm 3, respectively. Key Points: A multi‐elevation unmanned aerial vehicle‐ground penetrating radar (UAV‐GPR) system is proposed to measure soil moisture at the field (and larger) scale A linear relationship between the ratio of the reflected and the direct wave amplitudes along with the reciprocal of GPR height is deduced The UAV‐GPR method offers a higher resolution than remote sensing method and better working efficiency than conventional in situ methods