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An assessment of spatial similarity degree between polylines on multi-scale, multi-source maps
Similarity between the objects has close association with the geometrical structure and details of the objects. Therefore, in this study, a framework was presented based on the geometric criteria, the fuzzy Membership Functions (MF) and human spatial cognition. To increase the efficiency of MF and for the problem to get closer to reality, 1 K, 2 K, 5 K, 10 K, 25 K, 50 K, and 100 K data were used in this framework. The results showed that the degree of spatial similarity is specific to the objects themselves and their geometric structure. No linear or non-linear relationship could be found between scale changes and degree of spatial similarity of the objects, because the geometry of any object independently affects its degree of similarity to other objects in different scales and sources.
An assessment of spatial similarity degree between polylines on multi-scale, multi-source maps
Similarity between the objects has close association with the geometrical structure and details of the objects. Therefore, in this study, a framework was presented based on the geometric criteria, the fuzzy Membership Functions (MF) and human spatial cognition. To increase the efficiency of MF and for the problem to get closer to reality, 1 K, 2 K, 5 K, 10 K, 25 K, 50 K, and 100 K data were used in this framework. The results showed that the degree of spatial similarity is specific to the objects themselves and their geometric structure. No linear or non-linear relationship could be found between scale changes and degree of spatial similarity of the objects, because the geometry of any object independently affects its degree of similarity to other objects in different scales and sources.
An assessment of spatial similarity degree between polylines on multi-scale, multi-source maps
Chehreghan, Alireza (Autor:in) / Ali Abbaspour, Rahim
2017
Aufsatz (Zeitschrift)
Englisch
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