Abstract The near shore water intake pollutants from the land area and is heavily polluted. In order to assess such impact efficiently, the focus of marine environmental monitoring is shifting from inspecting pollutants in a water body to the measurement of pollutants adhered to sediments on seabed. The statistical methods are then used to analyze survey data for the purpose of interpretation. As for the problem of identifying the spatial distributions of classified pollutants over the water around Kaohsiung harbor, the result from the commonly used K-Means Cluster Analysis is not very satisfactory. It is therefore that the proposed research is trying to use the Fuzzy Cluster Method (FCM) to achieve better results. Through adaptive searching approach, the FCM should be able to generate the appropriate cluster centers for discerning the pollutants¡¦ spatial distribution, which in turn would convey more meaning to support feasible interpretation. The FCM model developed by this research will also help to trace the most suspicious or new pollutant source with the assistance from the domain expertise if an unusual pollutant were found in the study area. The benefit is therefore obvious that the authority in charge of marine environment can respond efficiently and correctly against such pollution event and take appropriate actions. FCM has been heavily applied to the research on computer vision and pattern recognition with great success. Recently quite amounts of literatures in the environmental and natural resource management study, including geo-statistical modeling, pollution mitigation, and groundwater quality management, have probed into the applications of cluster analysis using FCM. The problems of marine environment are highly complex and full of uncertainty in nature. Nevertheless by introducing advanced analysis techniques, such as FCM, for tackling such problems, the overall managerial efficiency of marine environment will be improved.