Field trials to detect drainage pipe networks using thermal and RGB data from unmanned aircraft.

• High resolution (4 cm/pixel) UAS visible imagery identified tile networks. • UAS visible imagery elucidated micro topographic highs revealing drier soil. • Optimal field conditions for data acquisition were better constrained. • UAS sensors show promise for transformative agricultural water management solutions. The use of drainage pipe is documented as far back as 200 B. C. and continues to be used in poorly drained agricultural regions throughout the world. While good for crop production, the eco-hydrologic impacts of this modification have been shown to adversely affect natural drainage networks. Identifying the exact location of drainage pipe networks is essential to developing groundwater and surface water models. The geometry of drainage pipe networks installed decades ago has often been lost with time or was never well documented in the first place. Previous work has recognized that drainage pipes can be observed for certain soil types in visible spectrum (RGB) remote sensing data due to changes in soil albedo. In this work, small Unmanned Aerial Systems (sUAS) were used to collect high resolution RGB and thermal data to map subsurface drainage pipe. Within less than 96 h of a small (< 1.3 cm) rain event, a total of approximately 60 ha of sUAS thermal and RGB data were acquired at two different locations in the IML-CZO in Illinois. The thermal imagery showed limited evidence of thermal contrast related to the drainage pipe. If the data were acquired immediately after a rain event it is more likely a temperature contrast would have been detected due to lower soil moisture proximal to the drainage pipe network. The RGB data, however, elucidated the drainage pipe entirely at one site and elucidated traces of the drainage pipe at the other site. These results illustrate the importance of the timing of sUAS data collection with respect to the precipitation event. Ongoing related work focusing on laboratory and numerical experiments to better quantify feedbacks between albedo, soil moisture, and heat transfer will help predict the optimal timing of data collection for applications such as drainage pipe mapping. [ABSTRACT FROM AUTHOR]