Abstract
With increasing availability of network bandwidth, server side processing capacity and advancements regarding the standardization of Web Service technologies, it becomes feasible to process geodata over the Web. As a result, web-based geoinformation is generated, which supports in particular spatial decision making. However, existing Spatial Data Infrastructures (SDI) mainly address data retrieval and portrayal, but to provide web-based geoinformation through SDIs web-based geoprocessing is required. This was the starting point to develop a framework which integrates existing desktop Geographical Information System functionality in SDIs. Moreover, an approach will be introduced to improve complex and large-scale geoprocesses in two dimensions: On the vertical scale, by significantly increasing the performance of single processes by means of Grid Computing technology and by improving other Quality of Service aspects. On the horizontal scale, by chaining this highly efficient processing services in order to automate these business processes. The relevance of this work will be demonstrated in a real-world scenario focusing on air quality assessment based on real-time data with the help of open source components.
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Schaeffer, B., Baranski, B., Foerster, T., Brauner, J. (2012). A Service-Oriented Framework for Real-Time and Distributed Geoprocessing. In: Bocher, E., Neteler, M. (eds) Geospatial Free and Open Source Software in the 21st Century. Lecture Notes in Geoinformation and Cartography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10595-1_1
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