Geodata are used in different branches of industry or academic fields, e.g. landscape planning, environmental protection, traffic, urbanism, economy, tourism et cetera. Depending on the objectives and applications, geodata will have to meet certain requirements in order to be utilised, e.g. concerning geometry and/or semantics. A frequent problem of geo information processing is to identify suitable datasets. The geometric requirements are often met, while this is not the case with semantic requirements. Sometimes geo datasets have similar geometric properties but different semantics. Generally, the acquisition of fresh geodata meeting the requirements defined is not an option. Instead, data mining concepts, as such as data fusion, provide an effective solution to this problem. The fundamental concept of data fusion is the extraction of the best-fit geometry data as well as the most suitable semantic data from existing datasets. The extracted data features are subsequently amalgamated into a newly created dataset. Data fusion can be applied to linear and polygonal data. This work introduces algorithms allowing for the joining of linear structures. The method discussed is based on the comparison of coordinates. The fusion process has been automated and implemented in the DataMerge software tool using the PERL scripting language and thus is not bound to any specific GIS software.
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- An Integrative Approach to Geospatial Data Fusion
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