The transmission line tree barrier is an important factor that threatens the safe operation of the transmission network. In order to achieve efficient and wide-area monitoring of the transmission line vegetation growth, vegetation type identification of tree barrier areas. In this paper, the vegetation type identification based on the hyperspectral image and the vegetation height detection based on the radar satellite image are studied. Firstly, the tree barrier distribution area is identified by airborne hyperspectral, and the type recognition of aerial image is completed. A transmission line is selected to verify the feasibility of hyperspectral to identify the vegetation type of tree barrier areas. Then, an improved three-stage vegetation height inversion algorithm is studied. Based on the algorithm, a transmission line vegetation height detection method is proposed. Using SAR image data, combined with the vegetation type identification results, an engineering application analysis is carried out. The results show that hyperspectral recognition accuracy of transmission line vegetation is up to 97.5%. The highest accuracy of SAR image detection vegetation height is 86.72%. And the proposed method can accurately detect the vegetation type and height of the transmission line tree barrier area.