Research on areal feature matching algorithm based on spatial similarity

The disparities of features that represent the same real world entities from disparate sources usually occur, thus the identification or matching of features is crucial to the map conflation. Motivated by the idea of identifying the same entities through integrating known information by eyes, the areal feature matching algorithm based on spatial similarity is proposed in this paper. Regarding the areal feature as a whole, the proposed algorithm identifies an areal feature by its shape-center point in order to calculate positional similarity, and shape similarity is given by the function of describing the shape, which ensures its precision not be affected by interferes and avoids the loss of shape information, furthermore the size of areal feature is measured by its covered area. Total similarity is obtained by integrating positional similarity, shape similarity and size similarity with a weighted average algorithm, and then the matching entities are achieved according to the maximum total similarity. Test results show the stability and reliability of the proposed algorithm, and its precision and recall are higher than other matching algorithm.