Abstract
In many GIS applications, it is necessary to identify the corresponding objects in the datasets with different sources, scales, and precisions. In this respect, similarity measures used to identify corresponding objects in the datasets with a high percentage of ambiguity might have low efficiency. Therefore, in this paper, we have tried to improve the precision of matching problems in complex conditions by presenting a polygon objects matching method based on the geographic context similarity. The proposed geographic context measure investigates the spatial relationships of the distance and the orientation of each object with the landmarks. Furthermore, instead of using all the identified landmarks for each object, only effective landmarks have been used while weights are assigned to them using the Inverse Distance Weighting (IDW) method. Implementation of the proposed method on three separate datasets shows the high efficiency of the proposed method in different spatial conditions. Finally, comparing the proposed method with the latest methods in the field of the study indicates an improvement according to the \({F}_{\mathrm{Score}}\) criterion. The results reveal that the matching precision has an average improvement of 10.43% on the studied datasets.
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Abbaspour, R.A., Chehreghan, A. & Chamani, M. Multi-scale polygons matching using a new geographic context descriptor. Appl Geomat 13, 885–899 (2021). https://doi.org/10.1007/s12518-021-00396-x
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DOI: https://doi.org/10.1007/s12518-021-00396-x