EnvirVis2022
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Item AtmoVis: Web Based Visualization of Air Quality Data with Interconnected Windows(The Eurographics Association, 2022) Powley, Benjamin T.; Anslow, Craig; Pearce, David James; Dutta, Soumya; Feige, Kathrin; Rink, Karsten; Zeckzer, DirkAir quality has an adverse impact on the health of people living in areas with poor quality air. Hence monitoring is needed to understand the extent of poor air quality. Little work has been done on the effectiveness of visualization techniques for air quality data analysis. Few tools are developed specifically for air quality analysis and many practitioners use general purpose tools, such as spreadsheets or programming. This paper investigates which visualization techniques are most effective in analysing air pollution data. A user study was performed with 20 experienced or expert participants. The participants used a domain specific prototype visualization tool we developed, AtmoVis, to compare spatio-temporal trends among air quality variables using preexisting visualization techniques. AtmoVis allows experts to explore data without the difficulties of programming, or working with spreadsheets. AtmoVis has a windowed layout that connects 6 different visualizations: heat calendar, line plot, monthly rose, site view, monthly averages, and data comparison. The results of the study demonstrated that the heat calendar, line plot, site view, monthly averages, and monthly rose visualizations were effective for analyzing the air quality through AtmoVis. The line plot and the heat calendar were particularly effective for temporal data analysis. AtmoVis was also effective for accessing air quality visualizations and inferring relationships among air quality variables at different monitoring sites. This research can help inform the design of future domain specific interactive tools for air quality analysis. AtmoVis could be extended to include other datasets in the future.Item EnvirVis 2022: Frontmatter(The Eurographics Association, 2022) Dutta, Soumya; Feige, Kathrin; Rink, Karsten; Zeckzer, Dirk; Dutta, Soumya; Feige, Kathrin; Rink, Karsten; Zeckzer, DirkItem FloodVis: Visualization of Climate Ensemble Flood Projections in Virtual Reality(The Eurographics Association, 2022) Oyshi, Marzan Tasnim; Maleska, Verena; Schanze, Jochen; Bormann, Franziskus; Dachselt, Raimund; Gumhold, Stefan; Dutta, Soumya; Feige, Kathrin; Rink, Karsten; Zeckzer, DirkAnthropogenic greenhouse gas emissions are leading to accelerating climate change, forcing politicians and administrations to take actions to mitigate climate change and adapt to its impacts, such as changes in flood regimes. For European countries, an increasing frequency and severity of extreme rainfall and flood events is expected. However, studies on future flood risks caused by climate change are associated with various uncertainties. The risk simulations are elaborate as they consider (i) climate data ensembles (temperature, precipitation), (ii) hydrological modeling (flood generation), (iii) hydrodynamic modeling (flood conveyance), and (iv) vulnerability modeling (damage assessment) involving a huge amount of data and their handling with Big Data methods. The results are difficult to understand for decision makers. Therefore, FloodVis offers a means of visualizing possible future flood risks in Virtual Reality (VR). The presentation of the results in a VR especially supports the user in understanding the complexity of the dynamics of the risk system enabling the feeling of presence. In FloodVis the user enters into a virtual surrounding to interact with the data, examine the temporal evolution, and compare alternative development pathways. Critical structures that require improved protection can be identified. The user can follow the inundation process in hourly resolution. We evaluated FloodVis through an online and offline user study on the context of whether VR can provide a better visualization of ensemble flood risk data and whether the sense of presence in VR can influence the decision making and help to raise awareness.Item LiDAR Operation and Digital Modeling Visualization to Communicate Stormwater Management at Green Spaces in Developing Regions(The Eurographics Association, 2022) Lin, Chien-Yu; Ackerman, Aidan; Johnston, Douglas; Tian, Guohang; Liu, Yang; Dutta, Soumya; Feige, Kathrin; Rink, Karsten; Zeckzer, DirkThis research involves the application of LiDAR modifications from China Meteorological Data Service Centre (CMDC) along with landscape digital modeling visualization tools to explore future climate change adaptation, potential landscape performance and strategic management at the Green Expo Park in Zhengzhou, China. In terms of yearly and numerical reports of weather conditions by CMDC, patterns of runoff distribution and detentions are highly correlated with leaf area index (LAI) and associated factors such as ground materials and physical characteristic. This observation is valuable as environmental inspection for stormwater management at green spaces in developing regions and further understanding of collaboration for landscape architects, urban designers, urban planners, stakeholders and government agencies. Using a combination of a Li- DAR360 along with terrain 3D modeling and parametric plugin software, we visualized several surface flow scenarios which were used to potentially inform land of recreation, green spaces and water quality management. Data collected from a LiBackpack 50 instrument was selected for initial reference and processed in LiDAR360, after which point the data was exported for 3D modeling. Parametric plugins were used to develop data supported computational simulation in order to visualize runoff dispersal and aggregation that occurred as a result of various site conditions. These visualizations, developed from LiDAR to digital modeling using parametric digital tools, allowed data-driven exploration of stormwater management and climate change.Item Tornado Visualizer: Analyzing the Destructive Impact of Tornadoes in the United States(The Eurographics Association, 2022) Hansen, Nikolaj; Lorentzen, Simon; Widell, Sofie; Kusnick, Jakob; Jänicke, Stefan; Dutta, Soumya; Feige, Kathrin; Rink, Karsten; Zeckzer, DirkWe present a visual exploration system that supports investigating multifarious inquiries on trends in the destructive impact of tornadoes in the United States. Based on the publicly available data on storm events from the National Oceanographic and Atmospheric Administration (NOAA), we designed linked views for all attributes that indicate destruction such as property damage, crop damage, and the numbers of deaths and injured people. Interactive filters support analyzing geospatial as well as temporal trends. The unique feature of our solution is our focus on the Enhanced Fujita (EF) scale, which has not yet been subject to related visual exploration environments. Our usage scenario documents the potential value of our system for a diversity of target users like urban planners or environmental scientists.