赵彬彬, 彭东亮, 张山山, 刘姗姗, 熊旭平, 戴全发. 顾及空间关系约束的不同比例尺面目标不一致性同化处理[J]. 武汉大学学报 ( 信息科学版), 2016, 41(7): 911-917. DOI: 10.13203/j.whugis20140011
引用本文: 赵彬彬, 彭东亮, 张山山, 刘姗姗, 熊旭平, 戴全发. 顾及空间关系约束的不同比例尺面目标不一致性同化处理[J]. 武汉大学学报 ( 信息科学版), 2016, 41(7): 911-917. DOI: 10.13203/j.whugis20140011
ZHAO Binbin, PENG Dongliang, ZHANG Shanshan, LIU Shangshang, XIONG Xuping, DAI Quanfa. An Assimilation Method of Inconsistency Between Area Objects at Different Scales with Respect to Spatial Relation Constraints[J]. Geomatics and Information Science of Wuhan University, 2016, 41(7): 911-917. DOI: 10.13203/j.whugis20140011
Citation: ZHAO Binbin, PENG Dongliang, ZHANG Shanshan, LIU Shangshang, XIONG Xuping, DAI Quanfa. An Assimilation Method of Inconsistency Between Area Objects at Different Scales with Respect to Spatial Relation Constraints[J]. Geomatics and Information Science of Wuhan University, 2016, 41(7): 911-917. DOI: 10.13203/j.whugis20140011

顾及空间关系约束的不同比例尺面目标不一致性同化处理

An Assimilation Method of Inconsistency Between Area Objects at Different Scales with Respect to Spatial Relation Constraints

  • 摘要: 不一致性问题是长期困扰地理信息科学领域的一个难题,亦是衡量空间数据质量的基本指标。不一致性问题直接影响空间数据集成、制图综合和空间数据更新。当前研究较多关注于相同或相近比例尺线目标之间的不一致性问题,而对不同比例尺地图数据或制图综合过程中不一致性处理问题的研究甚少。为此,本文顾及空间目标之间拓扑和距离关系约束,提出了一种基于Morphing变换的不同比例尺地图面目标之间不一致性的同化处理方法,通过对两组不一致性同化处理的对比实验验证了该方法的有效性和实用性。

     

    Abstract: Consistency is a basic indicator of spatial data quality assessment. As an opposite of consistency, inconsistency of spatial data refers to the conflicts or contradictions between spatial objects at the same scale or different scales. Spatial data inconsistency is a common concern in the international geographical information community since 1990's, and will have a direct effect on spatial data integration, cartographic generalization and spatial data updating. Previous studies mainly focus on handling inconsistencies between line objects with the same scale. Less attention is paid to the problem of handling inconsistencies between objects from maps with different scales or related issues about “a building dropped in a river” in the process of cartographic generalization while deriving a smaller scale map from a larger scale map. Hence, this paper proposes an approach based on data assimilation principles for handling inconsistency between rivers and buildings. The proposed method first extracts boundaries of both rivers at different scales by means of spatial operations (e.g. split, intersection). Then, morphing transformations are performed from a larger-scale river boundary to the other one. Finally, with respect to topological and distance constraints between river boundary and a building, an optimal assimilated river boundary is determined. Experiments demonstrate that the proposed method is able to handle inconsistency between generalized river and buildings at a larger-scale effectively, providing a promising solution for eliminating topological conflicts while deriving consistently a smaller-scale map from a larger-scale map.

     

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