In order to solve the problems that how to mine and express classification knowledge and rules in current remote sensing image classification

this paper introduces a new data mining theory of formal concept analysis

and realizes the connotation reduction of concept based on the minimum coverage of sets for ensuring the simplicity of classification rules.Meanwhile

the Fang city of Hubei province is selected to carry out the formal concept analysis theory to mine the land-use types classification rules

and construct a heuristic classifier based on the mined classification rules.The result shows that the mined classification rules have higher credibility

and the constructed classifier has higher accuracy compared with supervision classification and C4.5 algorithm

which proves that the theory of formal concept analysis provides a new method to achieve remote sensing image classification.