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Copyright of Geomatics & Information Science of Wuhan University is the property of Geomatics & Information Science of Wuhan University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Geomatics & Information Science of Wuhan University is the property of Geomatics & Information Science of Wuhan University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Concerning the dissimilarity between original spatial data and progressively transmitted spatial data, this paper proposes a model for measuring the similarity of curve datasets. After curve similarity is measured based on differences of the topological and geometric characteristics, the weighted similarity and the similarity precision for curve datasets are computed. The model uses weighted similarity to assess the overall degree of similarity for curve datasets and uses similarity precision to assess the similarity differences between curves. Finally, the model was used in an experiment and verified for effectiveness. [ABSTRACT FROM AUTHOR]