Analytically Yours: Spatial Data Analysis (original) (raw)
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Geographic visualizations always played an important role in human history, especially in the earth sciences, long before computer visualizations became popular. The earliest examples of geographic visualization even date back to the stone age with map-like wall paintings depicting the surroundings of our ancestors. Since then cartography, the art and science of map-making, has evolved continuously until today. This is why computer-based geographic visualization can build upon a large base of established cartographic knowledge. Well-known examples of static visualizations beyond geographic maps are thematic maps that display the spatial pattern of a theme such as climate characteristics or population density. Moreover, the use of modern visualization technology offers many new possibilities for geographical visualization tasks. These visualizations may help to explore, understand, and communicate spatial phenomena. Many readers will have a vague idea of what geographic visualization is about. Nonetheless, to avoid misconceptions, the most common definitions of the term geovisualization (short for geographic visualization) will be given. The following notion according to the 2001 research agenda of the International Cartographic Association (ICA) Commission on Visualization and Virtual Environments is most widely accepted today: " Geovisualization integrates approaches from visu-alization in scientific computing (ViSC), cartography, image analysis, information visualization, exploratory data analysis (EDA), and geographic information systems (GISystems) to provide theory, methods and tools for visual exploration, analysis, synthesis, and presentation of geospatial data " [530]. Others take a more human-centered view and describe geovisualization as " the creation and use of visual representations to facilitate thinking, understanding, and knowledge construction about geospatial data " [515] or as " the use of visual geospatial displays to explore data and through that exploration to generate hypotheses, develop problem solutions and construct knowledge " [474]. There are a few immediate observations from these definitions. It is clear that geovisualization research is a multidisciplinary task. Since it is the human who uses visualizations to explore data and construct knowledge, effective geovisualization techniques must above all take the user needs into account. The chapter is structured as follows. First, the range of possible goals of geovisualization and its driving forces are described in Section 6.1 and 6.2, respectively. Then, Section 6.3 looks at some perceptual issues and theoretical results in geovisualization. The main part of the survey, Section 6.4, covers a va