Change detection of Hongze Lake wetland using rule-based inferring

The main purpose of the paper was to explore the potential of knowledge rules in inferring information classes of wetland on historical imagery. The western of Hongze Lake was taken as test area and raw data mainly comprised of several Landsat MSS and Landsat TM/ETM+ images acquired between 1979 and 2000. With the analysis of characteristics of wetland and the feature of wetland in imagery and extensive field work, the techniques of extraction of wetland were discussed. Moreover, based on scatterplot analysis of multispectral characteristics and K-T transformation, the information from latest remote sensing images were used to infer information classes of clusters derived from past remotely sensed data and change detection was carried out by using post-classification comparison. This laid down a sound foundation for wetland preserve. It is shown that rule-based inferring can solve the problem of labeling information classes of past remotely sensed data. The achievements and methods put forward and used in the paper can be used in similar researches and provide a basis for the preserve of Hongze lake wetland. The results can lay down a basis for the decision-making and the establishment of relative policy for the preserve of wetland resources.