ACQUISITION OF RULES FOR THE TRANSITION BETWEEN MULTIPLE REPRESENTATIONS IN A GIS

摘要

Multiple or multi-scale representation is an issue of growing interest and importance in GIS. It deals with the representation of different spatial entities that describe the same physical objects in one common information system. The need for such a representation - instead of a description of objects on the most detailed level of resolution - results from various reasons. The main reason being the fact that spatial phenomena usually only occur on a certain scale - which is not necessarily the most detailed one. Changes in scale lead not only to changes in geometry, but also in topology and semantic. Multiple representations also result from different interpretations of the given reality according to scale or thematic emphasis, and also due to the date of capture. Since geographical phenomena have multiscale aspects, they should also be represented as such - and not only at one level. This then allows for an inspection of spatial data on various levels of detail - logically zooming in and out. Multiple representation affects data modelling and data capture, integration, storage, analysis and presentation, i.e. all parts of a GIS. Whereas multiple representation first was considered to be a mere cartographic problem, it is getting more and more obvious that it is an important issue in GIS as well. The paper first introduces into the problem of multiple representation and tries to clarify the terms used. The main emphasis is put on possible realizations of such a representation. This presumes to have a means to generate different levels of detail and provide links between these representations. The paper finally presents a concept for the transition between different scales based on an object-oriented representation. In order to go from one scale to the next, certain rules are required. These rules are partly given a prior, partly they are acquired automatically from given data sets with techniques from Machine Learning. The concept is a extension of a program developed for the derivation of object models for map and image interpretation.