Wireless Sensor Network Informed UAV Path Planning for Soil Moisture Mapping

Adaptive and targeted allocation of mobile sensing agents, in the form of unmanned aerial vehicles (UAVs) with software defined radar (UAV-SDRadar) payloads, enable mapping of surface soil moisture in regions where in situ wireless sensor networks (WSNs) undersample soil moisture or upscaling models perform poorly. This work presents an optimization-based UAV path planning methodology that seeks to maximize UAV flight coverage over areas where a complementing WSN yields upscaled soil moisture estimates with high uncertainty. By recursively mapping soil moisture over such areas, the combined UAV and WSN instrumentation can gradually capture the domain's true mean soil moisture. A series of numerical simulations are presented to demonstrate the algorithm's basic function while considering real-world and feasible operational scenarios.

Automated summary

This paper presents an optimization-based UAV path planning methodology aimed at maximizing UAV flight coverage over areas where a complementing WSN yields upscaled soil moisture estimates with high uncertainty, in order to gradually capture the true mean soil moisture of the region. A series of numerical simulations are conducted to demonstrate the algorithm's basic function under real-world and feasible operational scenarios.