Contextual Building Typification in Automated Map Generalization
Contextual Building Typification in Automated Map Generalization
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DOI：
10.1007/s00453-001-0008-8
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发表时间：
2001-06
期刊：
影响因子：
1.1
通讯作者：
N. Regnauld
中科院分区：
文献类型：
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作者：
N. Regnauld
制图综合的目的是将地理信息表示在与原始数据库不同规格的地图上。泛化通常意味着规模缩小，这会产生易读性问题。为了在较小的比例尺下可读，地理对象通常需要放大，这产生了重叠特征或地图拥塞的问题。为了管理这个问题，相对于建筑物，我们提出了一种选择方法的基础上的典型化原则，创建一个结果与较少的对象，但保留了初始的分布模式。为此，我们使用的图形上的建筑集，这是分析和分割的各种标准，从完形理论。该分析提供了与每个建筑物组相关的地理信息，例如建筑物的平均大小、组的形状和密度。这些信息与规模无关。来自分析阶段的信息用于定义以目标尺度表示它们的方法。其目的是尽可能地保留格局，保留各组之间在建筑物密度、大小和方向方面的相似性和差异性。我们提出了一些结果，已经获得了使用platformStratège，在COGIT实验室在国家地理研究所，巴黎。
Cartographic generalization aims to represent geographical information on a map whose specifications are different from those of the original database. Generalization often implies scale reduction, which generates legibility problems. To be readable at smaller scale, geographical objects often need to be enlarged, which generates problems of overlapping features or map congestion. To manage this problem with respect to buildings, we present a method of selection based on the typification principle that creates a result with fewer objects, but preserves the initial pattern of distribution. For this we use a graph of proximity on the building set, which is analysed and segmented with respect to various criteria, taken from gestalt theory. This analysis provides geographical information that is attached to each group of buildings such as the mean size of buildings, shape of the group, and density. This information is independent of scale. The information from the analysis stage is used to define methods to represent them at the target scale. The aim is to preserve the pattern as far as possible, preserve similarities and differences between the groups with regard to density, size and orientation of buildings. We present some results that have been obtained using the platformStratège, developed in the COGIT laboratory at the Institut Géographique National, Paris.