Landscape and Water Quality Change Detection in Urban Wetland: A Post-classification Comparison Method with IKONOS Data

摘要

Concerns are growing in recent years about wetland resources and their changes, especially in coastal urban areas. This study used IKONOS images to map an urban wetland and detect the changes of land-cover as well as general water quality with post-classification comparison method. The results indicated that an Optimal Iterative Unsupervised Classification (OIUC) method produced overall accuracy over 83% in land-cover classification. A decrease of 7.08% in water surface area and an increase of 31.35% in vegetations area had been found in the wetland for a period of 3 years. Also about 21.6% of the water was observed to change to worse quality. It shows IKONOS image is advanced in studying changes of an urban wetland at a local scale. Ground surveys that coinciding with satellite data and new classification algorithms are needed to achieve better results