Study on optimization-based layered classification for separation of wetlands

The classification and dynamics monitoring of wetlands using remotely sensed data is a complicated, time-consuming process involving high costs, and the accuracy varies depending on the techniques used for image processing and analysis, and the time and costs required for training, etc. This paper presents an optimization-based layered classification method for the classification and dynamics monitoring of wetlands based on a decision procedure of multiple objectives. Four driven factors including techniques to be used, classification accuracy, and the time and cost needed for the classification, were selected as the indicators of criteria in optimization of the layered classification. This method was applied to Thematic Mapper (TM) image classification of the wetlands in Minjiang River estuary and led to the overall correct percentage of 85.13% for seven categories of the wetlands.