![]() In order to address all four challenges, C1–C4, we introduce scale-aware maps, a process of presenting geo-spatial multivariate data based on a desired screen space, that enables dynamic modification to the level of detail shown using both zooming functions and custom scale options. This is the challenge of geo-spatial glyph-placement ( C4-glyph placement). However this common solution de-couples the glyphs from the original geospatial areas they intend to represent. Another option to address C3-occlusion is to employ structure-driven glyph placement guided by a Cartesian grid. Ellis and Dix state “a glyph representing multiple attributes may need simplifying when reduced in size, resulting in a loss of data", suggesting that reducing the size of a scalable multivariate glyph can be problematic ( C1-size perceivability). In other words, if we place a multivariate glyph at the center of each unit area on a map, the glyphs will either overlap in many cases or be too small to perceive, especially in densely populated areas (see Figure 1) ( C3-occlusion). If we plot glyphs in their geospatial context, then we risk overlap and over-plotting. However, even if we can present multivariate geospatial data using glyphs, we still run into challenges. One possibility is glyphs to support multivariate visualization options. This is a challenge for conveying of multi-variate geospatial data ( C2-multivariate geospatial data). For example, geo-spatial designs (choropleths, cartograms, symbol maps, etc.) only depict uni-variate or, occasionally, bivariate data. Even when trying to rectify this for a univariate map, few solutions enable opportunities to convey multivariate, high-dimensional data. The challenge of perception ( C1-size perceivability) is a fundamental one associated with digital maps. ![]() state, “A problem of choropleth maps is that the most interesting values are often concentrated in densely populated areas with small and barely visible polygons, and less interesting values are spread out over sparsely populated areas with large and visually dominating polygons". suggest scale, level of detail, and multivariate data as common challenges for the representation of geo-spatial data. There are many types of maps designed to present data but the underlying maps often come with other challenges such as the how the areas are segmented. Maps are useful for conveying information to both inexperienced and advanced users. The result is a novel glyph placement solution to support multi-variate maps. We also compare our placement algorithm with previous geo-spatial glyph placement algorithms. We present a selection of user options to facilitate the exploration process and provide case studies to support how the application can be used. The algorithm features a unique combination of guided glyph placement, level-of-detail, dynamic zooming, and smooth transitions. We develop an algorithm pipeline for this process and demonstrate how the user can adjust the level-of-detail of the resulting imagery. We present a multivariate map that uses geo-space to guide the position of multivariate glyphs and enable users to interact with the map and glyphs, conveying meaningful data at different levels of detail. ![]() However, the multivariate representation of data on maps is still considered an unsolved problem. ![]() Maps are one of the most conventional types of visualization used when conveying information to both inexperienced users and advanced analysts.
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