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Abstract:With the rapid improvement of geospatial data acquisition and processing techniques, a variety of geospatial databases from public or private organizations have become available. Quite often, one dataset may be superior to other datasets in one, but not all aspects. In Germany, for instance, there were three major road network vector data, viz. Tele Atlas (which is now "TOMTOM"), NAVTEQ (which is now "here"), and ATKIS. However, none of them was qualified for the purpose of multi-modal navigation (e.g., driving + walking): Tele Atlas and NAVTEQ consist of comprehensive routing-relevant information, but many pedestrian ways are missing; ATKIS covers more pedestrian areas but the road objects are not fully attributed. To satisfy the requirements of multi-modal navigation, an automatic approach has been proposed to conflate different road networks together, which involves five routines: (a) road-network matching between datasets; (b) identification of the pedestrian ways; (c) geometric transformation to eliminate geometric inconsistency; (d) topologic remodeling of the conflated road network; and (e) error checking and correction. The proposed approach demonstrates high performance in a number of large test areas and therefore has been successfully utilized for the real-world data production in the whole region of Germany. As a result, the conflated road network allows the multi-modal navigation of "driving + walking".

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As one of the key operators of automated map generalization, algorithms for the line simplification have been widely researched in the past decades. Although many of the currently available algorithms have revealed satisfactory simplification performances with certain data types and selected test areas, it still remains a challenging task to solve the problems of (a) how to properly divide a cartographic line when it is too long to be dealt with directly; and (b) how to make adaptable parameterizations for various geo-data in different areas. In order to solve these two problems, a new line-simplification approach based on the Oblique-Dividing-Curve (ODC) method has been proposed in this paper. In this proposed model, one cartographic line is divided into a series of monotonic curves by the ODC method. Then, the curves are categorized into different groups according to their shapes, sizes and other geometric characteristics. The curves in different groups will trigger different strategies as well as the associated criteria for line simplification. Whenever a curve is simplified, the whole simplified cartographic line will be re-divided and the simplification process restarts again, i.e., the proposed simplification approach is iteratively operated until the final simplification result is achieved. Experiment evidence demonstrates that the proposed approach is able to handle the holistic bend-trend of the whole cartographic line during the simplification process and thereby provides considerably improved simplification performance with respect to maintaining the essential shape/salient characteristics and keeping the topological consistency. Moreover, the produced simplification results are not sensitive to the parameterizations of the proposed approach.

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