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A new geospatial overlay method for the analysis and visualization of spatial change patterns using object-oriented data modeling concepts

Traditional geographic information system (GIS)-overlay routines usually build on relatively simple data models. Topology is – if at all – calculated on the fly for very specific tasks only. If, for example, a change comparison is conducted between two or more polygon layers, the result leads mostly...

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Detalles Bibliográficos
Autor principal: Tiede, Dirk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4786846/
https://www.ncbi.nlm.nih.gov/pubmed/27019643
http://dx.doi.org/10.1080/15230406.2014.901900
Descripción
Sumario:Traditional geographic information system (GIS)-overlay routines usually build on relatively simple data models. Topology is – if at all – calculated on the fly for very specific tasks only. If, for example, a change comparison is conducted between two or more polygon layers, the result leads mostly to a complete and also very complex from–to class intersection. A lot of additional processing steps need to be performed to arrive at aggregated and meaningful results. To overcome this problem a new, automated geospatial overlay method in a topologically enabled (multi-scale) framework is presented. The implementation works with polygon and raster layers and uses a multi-scale vector/raster data model developed in the object-based image analysis software eCognition (Trimble Geospatial Imaging, Munich, Germany). Advantages are the use of the software inherent topological relationships in an object-by-object comparison, addressing some of the basic concepts of object-oriented data modeling such as classification, generalization, and aggregation. Results can easily be aggregated to a change-detection layer; change dependencies and the definition of different change classes are interactively possible through the use of a class hierarchy and its inheritance (parent–child class relationships). Implementation is exemplarily shown for a change comparison of CORINE Land Cover data sets. The result is a flexible and transferable solution which is – if parameterized once – fully automated.