赵彬彬, 邓敏, 彭东亮, 朱建军. 基于整体极优对应的不同比例尺线目标一致化处理方法[J]. 武汉大学学报 ( 信息科学版), 2016, 41(8): 1046-1054. DOI: 10.13203/j.whugis20140430
引用本文: 赵彬彬, 邓敏, 彭东亮, 朱建军. 基于整体极优对应的不同比例尺线目标一致化处理方法[J]. 武汉大学学报 ( 信息科学版), 2016, 41(8): 1046-1054. DOI: 10.13203/j.whugis20140430
ZHAO Binbin, DENG Min, PENG Dongliang, ZHU Jianjun. A Methodology of Handling Inconsistencies Between Line Objects in Multi-scale Maps Based on the Optimum Correspondence Algorithm[J]. Geomatics and Information Science of Wuhan University, 2016, 41(8): 1046-1054. DOI: 10.13203/j.whugis20140430
Citation: ZHAO Binbin, DENG Min, PENG Dongliang, ZHU Jianjun. A Methodology of Handling Inconsistencies Between Line Objects in Multi-scale Maps Based on the Optimum Correspondence Algorithm[J]. Geomatics and Information Science of Wuhan University, 2016, 41(8): 1046-1054. DOI: 10.13203/j.whugis20140430

基于整体极优对应的不同比例尺线目标一致化处理方法

A Methodology of Handling Inconsistencies Between Line Objects in Multi-scale Maps Based on the Optimum Correspondence Algorithm

  • 摘要: 空间数据不一致性问题是国际地理信息科学领域长期关注的一项基础研究课题。不一致性是衡量空间数据质量高低的一个基本指标,亦是多源、多尺度数据集成、空间数据合并的重要研究内容,其存在直接影响空间数据分析、管理和增值应用。当前有关线目标不一致性的处理研究主要针对相同(或相近)比例尺目标,采用局部简化处理方法,缺乏对空间目标整体形状结构的考虑,对不同比例尺地图数据之间的不一致性处理问题几乎没有涉及。为此,顾及不同比例尺地图空间线目标表达的详细程度差异,提出了一种基于整体极优对应的不同比例尺线目标几何特征不一致性的处理新方法,进而通过对多组不同比例尺线目标不一致性处理的对比实验验证了该方法的有效性和实用性。

     

    Abstract: As one of the five indicators for measuring spatial data quality, consistency plays a key role in the processes of spatial analysis, spatial query, and spatial decision-making. It is also a focus in multi-scale data integration and spatial data conflation research among the international GIS community. In an ideal situation, GIS applications with consistent spatial data could provide reliable results. In actuality, spatial data cannot be perfect because of all kinds of deficiencies, such as different data sources, and different resolutions. In addition, operations as cartographic generalization may affect the consistency of spatial data, thus affecting spatial relations, spatial representation, geometric graphics, attributes, and semantics. This will further lead to difficulties when dealing with multi-source data or multi-scale data integration. This inconsistenvy cannot be simply handled by just deletion or inclusion remaining the other, because each object has some advantages. Line objects at a larger scale are more detailed, and have higher accuracy in general, and those at smaller scale have better integrity and generality. So, the most reasonable solution to this inconsistency is to take advantages of both line objects. For this purpose, a novel method based on the object-level optimum correspondence (OLOC) is proposed to handle geometric inconsistencies between line objects at different scales. As opposed to the projection method, not only the exact vertices but also whole line objects are considered. This new method uses a recursive strategy to find a mapping relation between elements such as vertices, segments and sequence of segments of both line objects by searching from one endpoint to the other, and then an OLOC is constructed. The generalized algorithm for node snapping is employed to generate a sequence of vertexes for a new line object. Three sets of line objects at different scales were tested with the projection method and OLOC method, respectively. The results show that the OLOC method effectively handles inconsistency between line objects at different scales.

     

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