Knowledge-based classification of CZCS images and monitoring of red tides off the west Florida shelf

Red tides on the west Florida shelf have significant economic and public health effects. Tracking the phytoplankton bloom, known as red tide, is important to understanding the phenomena. In this paper, a knowledge-based approach to automatic classification of Coastal Zone Color Scanner satellite images is developed. The Coastal Zone Color Scanner or CZCS images are initially segmented by the unsupervised mr-FCM algorithm then an expert system utilizes rules, and an iterative clustering process, to recognize case I (deep) water, case II (shallow) water and red tide by searching for expected features. The results show that this system is effective in recognizing images with red tide and segmenting the red tide