 A novel remote sensing image change detection method called entropy query by fuzzy art map object-wise joint classification comparison, Ekfamo BJCC, is presented in this article, which reduces cumulative error and salt and pepper effect by integrating entropy query by measurement of active learning with fuzzy art map neural network, introducing joint classification comparison, and using super pixel segmentation method, majority voting rule, and comparison of each super pixels. The proposed method was used to monitor the reclamation status of Liaha S. Jury wetland via 10-time series remote sensing images from 1987 to 2014, achieving an average classification accuracy of 94.12% and a total detection error of 27.03%. This article was authored by Min It-Han, Chen Kun-Jong, and Yang Jiu.