A Data-Driven Approach to Categorize Climatic Microenvironments
| dc.contributor.author | Häb, Kathrin | en_US |
| dc.contributor.author | Middel, Ariane | en_US |
| dc.contributor.author | Ruddell, Benjamin L. | en_US |
| dc.contributor.author | Hagen, Hans | en_US |
| dc.contributor.editor | Karsten Rink and Ariane Middel and Dirk Zeckzer | en_US |
| dc.date.accessioned | 2016-06-09T09:31:32Z | |
| dc.date.available | 2016-06-09T09:31:32Z | |
| dc.date.issued | 2016 | en_US |
| dc.description.abstract | In urban climatology, identifying areas of similar microclimatic conditions helps to relate fine-scale urban morphology variations to their impact on atmospheric surroundings. Mobile transect measurements yield high-resolution microclimate data that allow for the delineation of these areas at a fine scale. However, the resulting spatio-temporal multivariate data is complicated and requires careful analysis and visualization to identify the emergent climatic microenvironments. Our previous work used a glyph-based visualization to comprehensively visualize spatially aggregated multivariate data from mobile measurements over diverse routes. This aggregation was conducted over a regular grid, and the utilized glyphs encoded multivariate relationships, average wind direction during data collection, number of transects traversing a grid cell, and grid cell size. In this paper, we reduce the visual complexity of the resulting map by coloring the background of the grid cells based on a comparison of the glyphs. The result is a gridded map that visually emphasizes spatial zones of similar multivariate relationships and that takes the information encoded by the glyphs into account. A preliminary evaluation shows that the described approach yields zones that line up with the physical structure of the study site. | en_US |
| dc.description.sectionheaders | Session 3 | en_US |
| dc.description.seriesinformation | Workshop on Visualisation in Environmental Sciences (EnvirVis) | en_US |
| dc.identifier.doi | 10.2312/envirvis.20161105 | en_US |
| dc.identifier.isbn | 978-3-03868-018-5 | en_US |
| dc.identifier.issn | - | en_US |
| dc.identifier.pages | 35-39 | en_US |
| dc.identifier.uri | https://doi.org/10.2312/envirvis.20161105 | en_US |
| dc.identifier.uri | https://diglib.eg.org:443/handle/10 | |
| dc.publisher | The Eurographics Association | en_US |
| dc.subject | Computer Graphics [I.3.8] | en_US |
| dc.subject | Applications | en_US |
| dc.subject | en_US | |
| dc.subject | Computer Applications [J.2] | en_US |
| dc.subject | Earth and atmospheric sciences | en_US |
| dc.title | A Data-Driven Approach to Categorize Climatic Microenvironments | en_US |
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