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- W155397519 abstract "Keywords: Generalisation ontology, categorical maps, automated mapping, GIS, UML, OCL INTRODUCTION This research is concerned with the automatic derivation of multi scaled categorical maps from a single detailed database. The representation of categorical maps at increasing scales requires us to aggregate detailed categorical data, such as is found in capability maps or soil maps (Burrough 1991) in order to produce a series of simplified, visually effective maps. As a prerequisite to implementation within an OO GIS, a model is required that enables us to model these transitions in a meaningful way. Such a model must take into account the special characteristics unique to categorical maps. A categorical map is a space exhaustive tessellation of space. The discrete boundaries we see on the map are rarely found in the landscape The reality is that they represent inherently fuzzy phenomenon (Burrough and Frank 1996), and their form is very dependent on the classification used. Such characteristics present challenging environments for automated generalisation solutions, with strong spatial and semantic interdependencies existing between the polygons that define the various spatial extents. Various research has examined methods for generalising categorical data, in both the raster (Jaakkola, 1998), and vector domain. Generalisation methods have been implemented that deal with the generalisation of polygonal data, notably Muller and Wang (1992), and Bader and Weibel (1997). What is generally acknowledged amongst these researchers is that intelligent automated generalisation methods require a range of information in order to produce workable solutions. Specifically, information relating to metric qualities relating to each object (size, orientation, compactness, frequency of occurrence), topological qualities (the neighbourhood of objects), and semantic qualities (soil classification, typical associations between soils, and between soils and their geomorphological characteristics). These ideas are summarised in Figure 1, which generally reflects the idea of a phenomenological approach to map generalisation (Ormsby and Mackaness 1999)." @default.
- W155397519 created "2016-06-24" @default.
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- W155397519 date "2000-03-30" @default.
- W155397519 modified "2023-09-24" @default.
- W155397519 title "Modelling knowledge for automated generalisation of categorical maps—a constraint based approach" @default.
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- W155397519 doi "https://doi.org/10.1201/9781482268263-17" @default.
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