  Given the explosive growth of Internet of Things (IoT) devices ranging from
the two-dimensional (2D) ground to the three-dimensional (3D) space, it is a
necessity to establish a 3D spectrum map to comprehensively present and
effectively manage the 3D spatial spectrum resources in smart city
infrastructures. By leveraging the popularity and location flexibility of the
unmanned aerial vehicles (UAVs), we are able to execute spatial sampling with
these emerging flying spectrum-monitoring devices (SMDs) at will. In this
paper, we first present a brief survey to show the state-of-the-art studies on
spectrum mapping. Then, we introduce the 3D spectrum mapping model. Next, we
propose a 3D spectrum mapping framework which is composed of pre-sampling,
spectrum situation estimation, UAV deployment and spectrum recovery. Therein we
develop a Region of Interest (ROI)-driven UAV deployment scheme, which selects
new sampling points of the highest estimated interest and the lowest energy
cost iteratively. Meanwhile, we slice the entire 3D spectrum map into a series
of "images" and "repair" those unsampled locations. Furthermore, we provide an
exemplary case study on the 3D spectrum mapping, where, for example, an
important event is being held and the entire spectrum situation needs to be
monitored in real time to deal with malicious interference sources. Lastly, the
challenges and open issues are discussed.
