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arXiv · 1204.4541

Automatic Sampling of Geographic objects

Patrick Taillandier·Julien Gaffuri
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Abstract

Today, one's disposes of large datasets composed of thousands of geographic objects. However, for many processes, which require the appraisal of an expert or much computational time, only a small part of these objects can be taken into account. In this context, robust sampling methods become necessary. In this paper, we propose a sampling method based on clustering techniques. Our method consists in dividing the objects in clusters, then in selecting in each cluster, the most representative objects. A case-study in the context of a process dedicated to knowledge revision for geographic data generalisation is presented. This case-study shows that our method allows to select relevant samples of objects.

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Patrick Taillandier, Julien Gaffuri. 2012-04-20. Automatic Sampling of Geographic objects. https://arxiv.org/abs/1204.4541

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