Accurate and timely information describing urban wetland resources and their changes over time, especially in rapidly urbanizing areas, is becoming more important. We applied an object-based image analysis and nearest neighbour classifier to map and monitor changes in land use/cover using multi-temporal high spatial resolution satellite imagery in an urban wetland area (Hangzhou Xixi Wetland) from 2000, 2005, 2007, 2009 and 2013. The overall eight-class classification accuracies averaged 84.47% for the five years. The maps showed that between 2000 and 2013 the amount of non-wetland (urban) area increased by approximately 100%. Herbaceous (32.22%), forest (29.57%) and pond (23.85%) are the main land-cover types that changed to non-wetland, followed by cropland (6.97%), marsh (4.04%) and river (3.35%). In addition, the maps of change patterns showed that urban wetland loss is mainly distributed west and southeast of the study area due to real estate development, and the greatest loss of urban wetlands occurred from 2007 to 2013. The results demonstrate the advantages of using multi-temporal high spatial resolution satellite imagery to provide an accurate, economical means to map and analyse changes in land use/cover over time and the ability to use the results as inputs to urban wetland management and policy decisions.