The existing methods for measuring the sag of power lines are cumbersome and lack a high level of automation. This paper proposes a power line sag measurement method that integrates monocular depth and RTK positioning. Firstly, unmanned aerial vehicles capture key images of power line routes, and these images are input into the constructed monocular depth estimation model, EleDep-Net, to generate corresponding depth maps. The model incorporates a strip-like pyramid module and a boundary fusion attention module to accurately capture semantic information in the context of the conductors. Secondly, a depth correction algorithm is introduced to further refine the depth values in the depth map, obtaining depth information for the key points. Finally, by combining UAV RTK positioning and key point depth information, spatial coordinates for the key points are generated in the reference coordinate system, and a parabolic formula is fitted to derive the sag of the power line. Tested in a real-world environment of distribution network lines, the results indicate that this method significantly improves operational efficiency while ensuring a relative measurement error of less than 5%, demonstrating its high engineering application value.