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- W2489493656 abstract "With the advent of web mapping applications, today's users of geographic information are more aware of their requirements and are now for customized products specifically suited to their needs. These applications must, among other things, be able to present the same phenomenon at different levels of abstraction and according to different points of view. As with any web application, they must also provide fast response times. Automatic generalization mechanisms should form part of these applications. Given that such applications are web-based, response times must be very fast and generalization must take place on-the-fly. Unfortunately, there is no complete solution to automatic generalization. Although some operators require little control, complex ones still require human intervention. As an alternative, multiple representation databases have been proposed. This chapter presents an innovative strategy for multiscale on-demand mapping. This strategy is akin to data warehousing architecture where automatic cartographic generalization (CG) and multiple representations (MR) are distributed between the MR-centric warehouse and specialized CG-centric data marts. It also explains the underlying philosophy and the data warehousing architecture. The experiment in building a multiple representation data warehouse from eight data sources in the context of the GEMURE (Generalization and Multiple Representations for on-demand map production and delivery) project is also discussed. Finally, this chapter introduces UMapIT (Unrestricted MAPping Interactive Tool), a web-based on-demand mapping tool offering flexible seamless generalization." @default.
- W2489493656 created "2016-08-23" @default.
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- W2489493656 date "2007-01-01" @default.
- W2489493656 modified "2023-09-27" @default.
- W2489493656 title "A Data Warehouse Strategy for on-Demand Multiscale Mapping" @default.
- W2489493656 doi "https://doi.org/10.1016/b978-008045374-3/50011-9" @default.
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