首页> 外文期刊>International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences >DSM AND DTM FOR EXTRACTING 3D BUILDING MODELS: ADVANTAGES AND LIMITATIONS
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DSM AND DTM FOR EXTRACTING 3D BUILDING MODELS: ADVANTAGES AND LIMITATIONS

机译:DSM和DTM用于提取3D建筑模型:优点和局限性

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Using multiple sources of 3D information over buildings to go from building footprints (LOD0) to higher LODs in CityGML models is a widely investigated topic. In this investigation we propose to use a very common 2.5D product, i.e. digital terrain and surface models (DTMs and DSMs), to test how much they can contribute to improve a CityGML model. The minimal information required to represents a 3 dimensional space in an urban environment is the combination of a DTM, the footprints of buildings and their heights; in this way a representation of urban environment to define LOD1 CityGML is guaranteed. In this paper we discuss the following research questions: can DTMs and DSMs provide significant information for modelling buildings at higher LODs? What characteristics can be extracted depending on the ground sampling distance (GSD) of the DTM/DSM? Results show that the used DTM/DSM at 1?m GSD provides potential significant information for higher LODs and that the conversion of the unstructured point cloud to a regular grid helps in defining single buildings using connected component analysis. Regularization of the original point cloud does loose accuracy of the source information due to smoothing or interpolation, but has the advantage of providing a predictable distance between points, thus allowing to join points belonging to the same building and provide initial primitives for further modelling.
机译:在CityGML模型中,使用建筑物上的多个3D信息源从建筑物占地面积(LOD0)到更高的LOD是一个广泛研究的话题。在这项调查中,我们建议使用一种非常常见的2.5D产品(即数字地形和地面模型(DTM和DSM))来测试它们可以为改善CityGML模型做出多少贡献。代表城市环境中3维空间所需的最少信息是DTM,建筑物的占地面积及其高度的组合。这样,可以保证定义LOD1 CityGML的城市环境的表示。在本文中,我们讨论以下研究问题:DTM和DSM能否为较高LOD的建筑物建模提供重要信息?根据DTM / DSM的地面采样距离(GSD),可以提取哪些特性?结果表明,在GSD 1?m处使用的DTM / DSM可为更高的LOD提供潜在的重要信息,并且将非结构化点云转换为规则网格有助于使用连接的组件分析来定义单个建筑物。原始点云的正则化由于平滑或插值而降低了源信息的准确性,但是具有在点之间提供可预测距离的优点,从而允许加入属于同一建筑物的点并提供用于进一步建模的初始图元。

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