Spectral data is often characterized by multiple dimensions， such as frequency， time， space， and signal strength， which poses challenges for data acquisition and visualization. The electromagnetic spectrum situation is introduced to characterize the distribution of signal power spectral density in electromagnetic space to realize the spectrum situation awareness in the target region. At present， the acquisition method of spectrum data is usually to arrange a large number of discrete distributed sensors in the target area， which leads to low sampling efficiency and high sampling cost. In the case of limited resources， the above sampling method is not desirable. Therefore， on the basis of comprehensive consideration of sampling time and sampling coverage， in order to achieve electromagnetic spectrum posture cartography in the target region， a method of electromagnetic spectrum situation cartography based on hybrid model and data driven by UAV sampling is proposed. The simulation results show that the proposed method can effectively complete the electromagnetic spectrum situation mapping in the target region， and its completion accuracy and mapping effect are both better than the traditional interpolation algorithm and tensor completion algorithm.