Areal feature matching algorithm based on spatial similarity

Disparities of features that represent the same real world entity from disparate sources usually occur, thus their identification or matching is crucial to map compilation. Areal features possess much in maps' representation. Motivated by the idea of identifying the same entity through integrating known information by eyes, an areal feature matching algorithm based on spatial similarity is proposed in this paper. Regarding the areal feature as a whole entity, the total similarity is obtained by integrating positional similarity, shape similarity and size similarity with a weighted average algorithm. Then the matching entities are achieved according to the maximum total similarity. The proposed algorithm identifies an areal feature by its shape-center point in order to calculate positional similarity. The shape similarity is given by the function of describing the shape, which ensures its precision not be effected by all interference and avoids the loss of shape information. Furthermore, the size of areal features is measured by its covered area. Test results show the stability and reliability of the proposed algorithm.