A framework of optimal remote sensing using small unmanned aircraft systems

The use of small Unmanned Aircraft Systems (UAS) for remote sensing applications have increased significantly over the past decade. However, effective and efficient data collection methods and strategies are still being developed. The use of an effective small UAS methodology has become necessary, but it has additionally become important to also examine optimal remote sensing with respect to data quality. In this paper, a framework for the optimization of collecting remote sensing aerial imagery with small UAS is presented. Compared to other remote sensing techniques, the use of small UAS introduces several new tunable parameters that may have significant impact on data quality and the resulting analysis. The framework presented is a conceptual structure that describes optimal remote sensing with regard to the spatial, spectral, and temporal factors that provide the greatest signal-to-noise ratio for the desired application or purpose. Each of these factors are introduced and discussed as they pertain to a variety of parameters enabled by small UAS.