Generalisation Of Geographic Information

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Generalisation of Geographic Information

Theoretical and Applied Solutions in Multi Scale Mapping Users have come to expect instant access to up-to-date geographical information, with global coverage--presented at widely varying levels of detail, as digital and paper products; customisable data that can readily combined with other geographic information. These requirements present an immense challenge to those supporting the delivery of such services (National Mapping Agencies (NMA), Government Departments, and private business. Generalisation of Geographic Information: Cartographic Modelling and Applications provides detailed review of state of the art technologies associated with these challenges, including the most recent developments in cartometric analysis techniques able to support high levels of automation among multi scale derivation techniques. The book illustrates the application of these ideas within existing and emerging technologies. In addition to providing a comprehensive theoretical underpinning, the book demonstrates how theoretical developments have translated into commercial systems deployed within NMAs. The book explores relevance of open systems in support of collaborative research and open source web based map services. State of the art review on multi scale representation techniques Detailed consideration of database requirements and object modeling in support of emerging applications (3D, mobile) and innovative delivery (map generalisation services) Illustration through existing map production environment implementations Consolidated bibliography (680 entries), 200 illustrations, author and subject index
GIS And Generalisation

This text is the inaugural book in Taylor and Francis's GISDATA series, and is derived from the specialist workshop convened under the auspices of the European Science Foundation's GISDATA Scientific Programme. Generalisation is an integrating tool for the analysis and presentation of spatial data. Effective spatial data analysis requires multiple views of the world at various scales with different thematic layers of representation. Generalisation is a key mechanism in this process, as it filters out information which is required for particular scales or layers; hence it is critical to implement full and comprehensive generalisation capabilities in a GIS, something with which few current GIS are equipped.; This book overviews the core and as-yet unresolved issues surrounding the achievement of this goal, and presents various alternatives - both speculative views and practical examples - in the areas of automated generalisation, vis-a-vis problems such as object simplification and placement. At the same time it distinguishes between modelling with generalisation and graphical representation, and adopts a model-building perspective. It also describes artificial intelligence techniques for implementing automated generalised routines, and addresses issues of data quality and production.; The text is organized into six parts: an introduction; generic issue; object-orientated methods and knowledge-based modelling; knowledge acquisition and representation; data quality; and operation and implementation.
GIS And Generalisation

This text is the inaugural book in Taylor and Francis's GISDATA series, and is derived from the specialist workshop convened under the auspices of the European Science Foundation's GISDATA Scientific Programme. Generalisation is an integrating tool for the analysis and presentation of spatial data. Effective spatial data analysis requires multiple views of the world at various scales with different thematic layers of representation. Generalisation is a key mechanism in this process, as it filters out information which is required for particular scales or layers; hence it is critical to implement full and comprehensive generalisation capabilities in a GIS, something with which few current GIS are equipped.; This book overviews the core and as-yet unresolved issues surrounding the achievement of this goal, and presents various alternatives - both speculative views and practical examples - in the areas of automated generalisation, vis-a-vis problems such as object simplification and placement. At the same time it distinguishes between modelling with generalisation and graphical representation, and adopts a model-building perspective. It also describes artificial intelligence techniques for implementing automated generalised routines, and addresses issues of data quality and production.; The text is organized into six parts: an introduction; generic issue; object-orientated methods and knowledge-based modelling; knowledge acquisition and representation; data quality; and operation and implementation.