The crucial problem for integrating geospatial data is finding the corresponding objects (the counterpart) from different sources. Most current studies focus on object matching with individual attributes such as spatial, name, or other attributes, which avoids the difficulty of integrating those attributes, but at the cost of an ineffective matching. In this study, we propose an approach for matching instances by integrating heterogeneous attributes with the allocation of suitable attribute weights via information entropy. First, a normalized similarity formula is developed, which can simplify the calculation of spatial attribute similarity. Second, sound-based and word segmentation-based methods are adopted to eliminate the semantic ambiguity when there is a lack of a normative coding standard in geospatial data to express the name attribute. Third, category mapping is established to address the heterogeneity among different classifications. Finally, to address the non-linear characteristic of attribute similarity, the weights of the attributes are calculated by the entropy of the attributes. Experiments demonstrate that the Entropy-Weighted Approach (EWA) has good performance both in terms of precision and recall for instance matching from different data sets.

Four natural lakes in the middle and lower reaches of the Yangtze River—Dongting Lake, Poyang Lake, Chaohu Lake and Taihu Lake—play a key role in the climate, environment, and ecology of this area. Upstream of these lakes, the Three Gorges Dam Project has been storing water for 12 years. Future monitoring and management of rivers and lakes can certainly benefit from research on the patterns of variation of natural lakes downstream of the Three Gorges Project. This research applies Landsat TM/ETM data to evaluate water area changes in the four lakes from 2002 to 2013. The water area is estimated using AWEI (Automated Water Extraction Index) from satellite images. The average areas decreased respectively 452, 11, and 5 km² (29.6%, 1.4% and 0.2%) from 2002 to 2013 for Dongting, Chaohu, and Taihu Lakes. Meanwhile, it increased 300 km² (11.0%) for Poyang Lake. Precipitation and changes in river inflow may account for the fluctuation in the surface area to a large degree, especially between 2009 and 2013. The present study was undertaken to characterize the evolution of lakes and to explore the potential driving force of variation in order to assist the management of dams upstream in the river basin.