Optimal remote sensors trajectory planning for downscaling and assimilation problems

In this paper, our efforts focus on the downscaling problem in the framework of surface soil moisture. Our purpose is to introduce a new methodology to transform low-resolution remote sensing data (for example from a satellite) about soil moisture to higher resolution information that contains better information for use in hydrologic studies or water management decision making. Our goal is to obtain a high resolution data set with the help of a combination of ground measurements and low-altitude remote sensing (typically images obtained from a UAV). In the following, we first describe the methodology developed using only low-resolution information and ground truth. Then we introduce in two different way the optimal trajectories of remote sensors, first to solve the problem of maximum coverage knowing the location of ground measurements, then to solve the problem of optimal data assimilation to optimally improve the assimilation problem using remote sensors.