EnvirVis16

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https://diglib.eg.org/handle/10.2312/15277

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Are Environmental RegulationsWorking? A Visual Analytic Approach To Answering Their Impact on Toxic Emissions
(The Eurographics Association, 2016) Burlinson, David; Koehrn, Kara; Subramanian, Kalpathi; Lu, Aidong; Karsten Rink and Ariane Middel and Dirk Zeckzer
Acquisition and analysis of environmental data are essential to the quality, safety and health of human life, and typically consist of heterogeneous, multivariate, and spatio-temporal information collected from different resources. In the United States, the Environmental Protection Agency (EPA) is responsible for protecting human health and the environment; it does so by developing and enforcing regulations to monitor the environment and reduce pollution. In this work, our goal is to obtain a deeper understanding of the effectiveness and impact of EPA regulations; we present preliminary work on an interactive visualization system that attempts to answer specific questions as a function of the dimensions of interest. We demonstrate our system on toxic chemical release reductions resulting from the Clean Air Interstate Rule (CAIR), focusing on the electric utilities sector.We have received positive feedback from our domain expert (toxicologist at the US EPA), indicating that our initial results can more effectively communicate the impacts of environmental regulations, through providing strong visual correlation tools that are currently not available.
A Data-Driven Approach to Categorize Climatic Microenvironments
(The Eurographics Association, 2016) Häb, Kathrin; Middel, Ariane; Ruddell, Benjamin L.; Hagen, Hans; Karsten Rink and Ariane Middel and Dirk Zeckzer
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.
EnvirVis 2016: Frontmatter
(Eurographics Association, 2016) Karsten Rink; Ariane Middel; Dirk Zeckzer;
Strategic Initiatives for Flow Visualization in Environmental Sciences
(The Eurographics Association, 2016) Bujack, Roxana; Middel, Ariane; Karsten Rink and Ariane Middel and Dirk Zeckzer
Flow plays a big role in the environmental sciences, but there are major differences between theoretically available and practically applied visualization techniques. This paper surveys various techniques in computational and environmental flow visualization, identifies challenges, and suggests strategic initiatives on how to bridge the gap.
Towards Visual Analytics for Multi-Sensor Analysis of Remote Sensing Archives
(The Eurographics Association, 2016) Eggert, Daniel; Sips, Mike; Köthur, Patrick; Karsten Rink and Ariane Middel and Dirk Zeckzer
To better detect and study processes on the Earth's surface, scientists want to combine various satellite data and extract potentially interesting patterns from the combined data. This analysis approach is called multi-sensor analysis. In this paper, we present an interactive visual exploration solution for the first important step of multi-sensor analysis: the assessment and selection of remote sensing scenes. This solution is the first step towards a larger Visual Analytics (VA) approach that turns multisensor analysis into a transparent and interactive analysis method. We conduct our research in the context of GeoMultiSens, which is an interdisciplinary research project between remote sensing, computer science and VA experts. To demonstrate the utility of our visual exploration solution, we use a real-world scenario: the assessment and selection of scenes in order to study the change of forest cover in Europe. The application example indicates that interactive visual exploration facilitates a structured assessment of the quantity and quality of remote sensing scenes and enables scientists to exclude low-quality scenes from subsequent multi-sensor analysis.
Visual Analysis of Reservoir Simulation Ensembles
(The Eurographics Association, 2016) Höllt, Thomas; Ravanelli, Fabio Miguel de Matos; Hadwiger, Markus; Hoteit, Ibrahim; Karsten Rink and Ariane Middel and Dirk Zeckzer
Hydrocarbon reservoir simulation models produce large amounts of heterogeneous data, combining multiple variables of different dimensionality, such as two or three-dimensional geospatial estimates with abstract estimates simulated for the complete field or different wells. In addition these simulations are nowadays often run as so-called ensemble simulations, to capture uncertainty of the model, as well as boundary conditions as variation in the output. The (visual) analysis of such data is a challenging process, due to the size and complexity of the data. In this paper we present an integrated system for the visual analysis of ensemble reservoir simulation data. We provide tools to inspect forecasts for multiple variables of complete fields, as well as different wells. Finally, we present a case study highlighting the effectiveness of the presented system.
Visual Monitoring of Photovoltaic Systems
(The Eurographics Association, 2016) Harder, Jannis; Riehmann, Patrick; Wörfel, Stefan; Krause, Tobias; Froehlich, Bernd; Karsten Rink and Ariane Middel and Dirk Zeckzer
We developed a scalable visual analytics framework for managing and analyzing hundreds of geographically distributed photovoltaic systems. These systems deliver performance parameters at different levels as well as environmental parameters. Our web-based framework gathers the data in a central server and allows comparisons of production values across time and photovoltaic systems, analysis of component failures and reporting errors. It is in daily use by a regional energy provider for over one year and its capabilities for fluent interaction and versatile configuration of visualizations from overviews to performance parameters of detailed components of individual systems are highly appreciated.
Visualization of Scanned Cave Data with Global Illumination
(The Eurographics Association, 2016) Schertler, Nico; Salm, Mirko; Staib, Joachim; Gumhold, Stefan; Karsten Rink and Ariane Middel and Dirk Zeckzer
3D scans of caves are acquired for virtual exploration, quantitative analysis, and communication purposes. Especially when presented to a non-professional audience, near realistic visualization is important because it improves acceptance and familiarity. A major part of realistic visualizations is the reasonable simulation of light transport, including global effects such as diffuse inter-reflections. In this paper, we present a direct visualization method for cave data that are represented as unstructured point clouds. Global light transport is approximated with a volumetric scene representation. Using hierarchical data structures, our system achieves interactive frame rates.
Visualizing Malaria Spread Under Climate Variability
(The Eurographics Association, 2016) Liang, Xing; Aggarwal, Rajat; Cherif, Alhaji; Gumel, Abba; Mascaro, Giuseppe; Maciejewski, Ross; Karsten Rink and Ariane Middel and Dirk Zeckzer
In order to better control and prevent the infectious diseases, measures of vulnerability and risk to increased infectious disease outbreaks have been explored. Research investigating possible links between variations in climate and transmission of infectious diseases has led to a variety of predictive models for estimating the future impact of infectious disease under projected climate change. Underlying all of these approaches is the connection of multiple data sources and the need for computational models that can capture the spatio-temporal dynamics of emerging infectious diseases and climate variability, especially as the impact of climate variability on the land surface is becoming increasingly critical in predicting the geo-temporal evolution of infectious disease outbreaks. This paper presents an initial visualization prototype that combines data from population and climate simulations as inputs to a patch-based mosquito spread model for analyzing potential disease spread vectors and their relationship to climate variability.

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