There is a gap between traditional neural network’s information process ability and amount information of remote sensing image recognition. Focusing on this problem

this paper proposes a method to combine rough set theory with neural network theory and uses it in remote sensing image recognition. First

this paper analyzes the feasibility and advantages of combination of neural network with rough set theory. Based on this analysis

a rough set theory based remote sensing image recognition model is presented. Furthermore

analysis on rough set module and remote sensing image recognition module are given in details. Finally

contrastive experiment data are given to prove that combining rough set theory with neural network theory for remote sensing image recognition has a high converging rate

shorter training time and more accuracy.The potential of this method

is also shown.