Quality Assessment Method for Linear Feature Simplification Based on Multi-Scale Spatial Uncertainty
نویسندگان
چکیده
This study discusses a method for quantitative quality assessment for the simplification of linear features. Considering the multi-scale nature of linear features, this paper combines the improved Douglas–Peucker method without threshold and the multiway tree model to construct a weighted hierarchical linear feature representation model called the Douglas–Peucker Multiway Tree (DMC-tree). Subsequently, the uncertainty computation is conducted from the root of the DMC-Tree top-down level by level to obtain the quality indexes. Then, the quality index of the whole linear feature is obtained by combining the indexes of every layer together with their weights. The results of the presented method are compared with those of the length ratio method and the Hausdorff distance method. The results show the advantages of the presented method over the others, including (1) its sensitivity to feature points of multiple scales, (2) the quantitative characteristics of the indexes, and (3) the finer granularity in assessment.
منابع مشابه
Erratum: Zhai, J., et al. Quality Assessment Method for Linear Feature Simplification Based on Multi-Scale Spatial Uncertainty. ISPRS International Journal of Geo-Information 2017, 6, 184
The editorial team of the journal International Journal of Geo-Information (IJGI) would like to make the following corrections to the published paper [1]: In the last paragraph on page 1, “is accurate [2]” should be “is accurate [1]”. We apologize for any inconvenience caused to the readers. The changes do not affect the scientific results. The manuscript will be updated and the original will r...
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ورودعنوان ژورنال:
- ISPRS Int. J. Geo-Information
دوره 6 شماره
صفحات -
تاریخ انتشار 2017