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Polygon similarity can play an important role in geographic information retrieval, map matching and updating, and spatial data mining applications. Geographic information science (GIS) represents various spatial objects as polygons, including simple polygons and polygons with holes, as well as multipolygons. Spatial objects of multipolygons possess complex structure which makes it difficult to assess their similarity. This study develops a method based on convex hulls and position graphs to measure the similarity between multipolygons. The proposed method first finds correspondences between subpolygons in the two multipolygons based on a control polygon. Thereafter, the method constructs a position graph to denote the distribution of these subpolygons and applies a turning function to compute the similarity between various graphs. Fourier transformation and moment invariants were combined to characterize the different matching relationships among subpolygons. The experiments involve three different kinds multipolygons to verify the effectiveness and robustness of proposed method. The experiments show that this approach effectively measures similarity between multipolygons. Moreover, the proposed method accounts for the relationships across the entire complex geometrical shape and components of multipolygon during measuring similarity.

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