LAUSR

Information on height of pylon is important when planning the routes of unmanned aerial vehicles. This paper proposes a new automatic method for estimating pylon height using shadow differences between GF-2 satellite images taken at different times. Initially, the spectral distribution features and triangular shape of pylon shadows are used for shadow detection to enhance the difference from other land objects using images taken at a greater sun elevation angle. Then, the difference in the shadows of the same pylon in images taken at different times and shadow-imaging principles are used to estimate the vertical of the pylon top to avoid interference from complex land objects. Finally, the height of the pylon is approximated using the distance from the vertical projection point to the shadow point of the pylon top and sun elevation angle. GF-2 images were selected and included five pylons in the target area. The average error of the estimated height was 1.56 m, and the relative error was only 2.74%.