I. Introduction
Land-cover classification is one of the most important applications of remote sensing. Crucial information on urban and environmental studies can be obtained by accurate land-cover maps, such as urban planning [1], carbon-cycle monitoring [2], and urban heat islands [3]. However, land-cover maps consist of misclassification and these errors might affect downstream studies and mislead the results [4]. Therefore, there has been enormous effort to improve the accuracy of land-cover map for a long time in the remote-sensing society [5], [6].