Matching of Datasets.

Abstract

A multiple representation database contains several geographic datasets defined at different resolutions covering the same area. Objects within the different datasets that represent the same real world feature are connected. This paper presents a method to build a multiple representation database by automatically creating these connections. First an analysis is made of how cartographic generalisation changes object representation and the impact this has on automated matching. Based on this discussion a method for automated matching is proposed. The matching process starts with an object in the small scale dataset and selects a set of possible matches in the large scale dataset. To find the best match, different measures based on semantics, geometry, topology and inter-object relationships are used. These measures form an n-dimensional space and the object(s) in the large scale dataset that is closest to the current small scale object is considered to be the best match. The different measures are given different importance using weights acquired by analysing a manually matched multiple representation database.

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