Research on the Visualization System and Applications of Uncertainty in Remote Sensing Data Classification

Thematic mapping is one of the major application fields of remote sensing techniques. Data quality of the thematic data was concerned about. At present, there are a lot of researches that focus on the uncertainty measures, modeling and visualization. But lacking an easy-to-use visualization system of classification uncertainty. The research work toward how to use uncertainty, especially how to use it to improve the classification accuracy is few. Based on the review of existing visualization method and system of the uncertainty of remote sensing data classification, we developed an uncertainty visualization system for remote sensing data classification. In this system, the static gray, color, color-saturation combined and dynamic 3D visualization method were exploited. The system was developed using the IDL language. This system can be integrated with ENVI, an popular software for remote sensing image processing, to use its powerful image processing functions. The system provides users multiple choices of uncertainty measures, such as: absolute uncertainty, relative uncertainty, relative probability entropy, relative maximum deviation. Its data format is compatible with ENVI.