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- W1968253124 abstract "With rapidly widening access to high-capacity geospatial data via high-speed Internet, user demand for multiform and accurate information has increased. Correspondingly, there is a growing need for hybrid map services that can combine heterogeneous data. Conflation, defined as the combining of information from diverse sources so as to reconcile spatial inconsistencies, has emerged to meet that need. In this research, we developed an approach that conflates road maps with aerial images using road intersections as conjugate features. The method has a three-process workflow including preprocessing for road candidate identification, spatial inconsistency removal, and shape disagreement removal. On the basis of overall comparative evaluations of the experimental results with a reference, it was found that the correctness of the conflated road was 36.6% better than that of the original road." @default.
- W1968253124 created "2016-06-24" @default.
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- W1968253124 date "2013-01-11" @default.
- W1968253124 modified "2023-09-25" @default.
- W1968253124 title "Removal of spatial inconsistency and shape disagreement for conflation of road maps with aerial images" @default.
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- W1968253124 doi "https://doi.org/10.5589/m13-001" @default.
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