The natural forest areas in China are widely distributed and the terrain is complex. Relying on the traditional patrol detection method of forest rangers to prevent and control forest diseases and insect pests is inefficient, so it is difficult to find early forest diseases and insect pests in time, which may miss the best time for prevention and control. In view of this problem, a deep learning network based on multispectral image detection of forest diseases and insect pests was designed, and a set of detection software was developed. Through the UAV hanging flight experiment, the built deep learning network was used to complete the detection of infected areas in forest areas, and the detection results were analyzed.