Fuzzy logic applied in remote sensing image classification

Fuzzy logic, a knowledge-based method and widely used in control systems, is proposed to be applied in remote sensing image classification. Fuzzy logic makes no assumption about statistical distribution of the data and it provides more complete information for a thorough image analysis, such as fuzzy classification results. It is interpretable and can use expert knowledge and training data at the same time. In this paper, a hierarchical fuzzy expert system is developed for the remote sensing image classification and tested on the land cover classification of Landsat 7 ETM+ over the Rio Rancho area, New Mexico incorporated area. The classification result is compared with that of maximum likelihood classifier and back-propagation neural network classification and it can get better classification performance.