Traditional methods of crop monitoring in the field need to lay various sensors and complex circuits in the field with a bad environment. Usually, the problems of time-consuming, labor-consuming, high maintenance cost and more or less damage to plants arise. Unmanned aerial vehicle (UAV) spectral imaging technology is a new and fast technology for monitoring farmland environment, which combines an unmanned aerial vehicle (UAV), remote sensing sensors, real-time image transmission and other means. It can quickly obtain real-time spectral images of farmland crops. Usually, it can analyze images to obtain the growth information of farmland crops. The application of this technology catches up with the above problems. Firstly, the spectrum imaging technology of UAV is summarized, and the advantages of UAV application are introduced. Compared with traditional satellite remote sensing monitoring platform, UAV can work at a lower altitude, i. e. 80～400 m. It can resist the disadvantage of adverse weather and clouds, and achieve fast and accurate acquisition of high-precision images. At present, the application of small UAVs at home and abroad mainly focuses on disaster monitoring, natural resources monitoring, urban planning and vegetation monitoring. In addition, due to its low cost, near real-time image acquisition and other characteristics, in the development of precision agriculture, unmanned aerial vehicle (UAV) spectral images are more commonly used. Secondly, the characteristics and application scenarios of common spectral images are analyzed. Panchromatic images are mostly used for data fusion because of their high resolution; multispectral and hypersecretion images are combined with spectral characteristics of crops due to their abundant spectral information, which can be used for the detection of biological and chemical indicators of crops, early warning of agricultural disasters, yield prediction and fine classification mapping; and thermal infrared images can be used for monitoring field drought because they can obtain crop temperature information. Then the main application ways of UAV spectral image technology in the field are summarized. At present, the main methods of monitoring crops using UAV spectral image technology are: using spectral reflectance to construct vegetation index or red edge parameters, or studying the reflection characteristics of vegetation, constructing crop growth model, using multiple linear regression, partial least squares method, in-depth learning and other biochemical parameters of crops to establish a model for inversion. Finally, shortcomings of UAV spectral imaging technology in the field application are discussed, and the future development prospects of this new technology have prospected, in order to provide a reference for the derivative application of UAV spectral imaging technology in the field.