Aiming at the optimal scale in multi-scale segmentation technology selection problem, a method is put forward based on fractal net evolution approach and improved fuzzy c-means of remote sensing image segmentation. In this method, the original image is segmented by small scale using fractal net evolution approach. The global search capability of the particle swarm method is used to determine the optimal initial clustering center from the pre-segmented small scale objects. When small scale objects are merged, the objective function of the object spatial information and the correlation information between objects is established. Ultimately, the segmentation results which can adapt to different scale features are obtained, and the excessive dependence on the scale parameters is reduced. Experimental results show that this method can obtain high quality segmentation results of remote sensing images.