EnvirVis2025

Permanent URI for this collection

https://diglib.eg.org/handle/10.2312/3607187
EnvirVis 2025 colocated with EuroVis 2025 - 27th EG Conference on Visualization
Luxembourg City, Luxembourg | June 2 - 6, 2025
Table of Contents
Session I
DeepSwitch - A Web-based Tool for the Introduction to Visual Analysis of Spatiotemporal Processes in Oceanographic Data
[full paper Image] [meta data Image]
Christian Hörath, David Derichs, Lara Eyl, Oliver Kallenberg, and Tim Gerrits
Evolution of Extreme Dust Events in 3D Environment
[full paper Image] [meta data Image]
James Kress, Wenqiang Cui, Shehzad Afzal, Sohaib Ghani, Loka B. Karumuri, and Ibrahim Hoteit
Enhancing Apple Variety Testing with Ontology-Enriched Visual Analytics: A Decision-Support Framework
[full paper Image] [meta data Image]
Ekaterina Chuprikova, Walter Guerra, Robert Stocker, Abraham Mejia-Aguilar, and Roberto Monsorno
Session II
High-Resolution Urban Climate Visualization: A Dual-Screen Approach for Public Engagement
[full paper Image] [meta data Image]
Christoph Huber, Till Nagel, and Heiner Stuckenschmidt

BibTeX (EnvirVis2025)
@inproceedings{
10.2312:envirvis.20252011,

booktitle = {
Workshop on Visualisation in Environmental Sciences (EnvirVis)},

editor = {
Feige, Kathrin
 and 
Nsonga, Baldwin
 and 
Rink, Karsten
},
title = {{
EnvirVis 2025: Frontmatter}},

author = {
Feige, Kathrin
 and 
Nsonga, Baldwin
 and 
Rink, Karsten
},
year = {
2025},

publisher = {
The Eurographics Association},


ISBN = {978-3-03868-287-5},

DOI = {
10.2312/envirvis.20252011}

}
@inproceedings{
10.2312:envirvis.20251146,

booktitle = {
Workshop on Visualisation in Environmental Sciences (EnvirVis)},

editor = {
Feige, Kathrin
 and 
Nsonga, Baldwin
 and 
Rink, Karsten
},
title = {{
DeepSwitch - A Web-based Tool for the Introduction to Visual Analysis of Spatiotemporal Processes in Oceanographic Data}},

author = {
Hörath, Christian
 and 
Derichs, David
 and 
Eyl, Lara
 and 
Kallenberg, Oliver
 and 
Gerrits, Tim
},
year = {
2025},

publisher = {
The Eurographics Association},


ISBN = {978-3-03868-287-5},

DOI = {
10.2312/envirvis.20251146}

}
@inproceedings{
10.2312:envirvis.20251147,

booktitle = {
Workshop on Visualisation in Environmental Sciences (EnvirVis)},

editor = {
Feige, Kathrin
 and 
Nsonga, Baldwin
 and 
Rink, Karsten
},
title = {{
Evolution of Extreme Dust Events in 3D Environment}},

author = {
Kress, James
 and 
Cui, Wenqiang
 and 
Afzal, Shehzad
 and 
Ghani, Sohaib
 and 
Karumuri, Rama Krishna
 and 
Hoteit, Ibrahim
},
year = {
2025},

publisher = {
The Eurographics Association},


ISBN = {978-3-03868-287-5},

DOI = {
10.2312/envirvis.20251147}

}
@inproceedings{
10.2312:envirvis.20251148,

booktitle = {
Workshop on Visualisation in Environmental Sciences (EnvirVis)},

editor = {
Feige, Kathrin
 and 
Nsonga, Baldwin
 and 
Rink, Karsten
},
title = {{
Enhancing Apple Variety Testing with Ontology-Enriched Visual Analytics: A Decision-Support Framework}},

author = {
Chuprikova, Ekaterina
 and 
Guerra, Walter
 and 
Stocker, Robert
 and 
Mejia-Aguilar, Abraham
 and 
Monsorno, Roberto
},
year = {
2025},

publisher = {
The Eurographics Association},


ISBN = {978-3-03868-287-5},

DOI = {
10.2312/envirvis.20251148}

}
@inproceedings{
10.2312:envirvis.20251149,

booktitle = {
Workshop on Visualisation in Environmental Sciences (EnvirVis)},

editor = {
Feige, Kathrin
 and 
Nsonga, Baldwin
 and 
Rink, Karsten
},
title = {{
High-Resolution Urban Climate Visualization: A Dual-Screen Approach for Public Engagement}},

author = {
Huber, Christoph
 and 
Nagel, Till
 and 
Stuckenschmidt, Heiner
},
year = {
2025},

publisher = {
The Eurographics Association},


ISBN = {978-3-03868-287-5},

DOI = {
10.2312/envirvis.20251149}

}

Browse

Recent Submissions

Now showing 1 - 5 of 5
  • Thumbnail Image
    Item
    EnvirVis 2025: Frontmatter
    (The Eurographics Association, 2025) Feige, Kathrin; Nsonga, Baldwin; Rink, Karsten; Feige, Kathrin; Nsonga, Baldwin; Rink, Karsten
  • Thumbnail Image
    Item
    DeepSwitch - A Web-based Tool for the Introduction to Visual Analysis of Spatiotemporal Processes in Oceanographic Data
    (The Eurographics Association, 2025) Hörath, Christian; Derichs, David; Eyl, Lara; Kallenberg, Oliver; Gerrits, Tim; Feige, Kathrin; Nsonga, Baldwin; Rink, Karsten
    Oceanographic data comprises a multitude of information, such as concentrations of materials, temperature, or the movement of water over time. The interpretation and analysis of such data is useful for a large number of domains which all contribute to the understanding of dynamic environmental processes. Complex visual analysis applications are typically handcrafted for the needs of domain scientists and are thus powerful tools for experts, but often require a steep learning curve and involved setups. Visualization used for education and science communication on the other hand is often limited to simplistic 2D views, where temporal aspects are mainly communicated via flip-book animation or side-by-side comparisons, thus limiting the interactive exploration of data and ease of connecting temporal and spatial features. We present DeepSwitch - a web-based visual analysis tool tailored towards an accessible exploration of dynamic processes in oceanographic data. Its design is based on requirements that make it applicable to classroom environments and its central paradigm introduces a fast switch between fixed-time and fixed-depth representation of the data, aiming to minimize cognitive load while providing versatile exploration options for dynamic processes. We demonstrate its usefulness in two analysis scenarios and present preliminary feedback from teachers.
  • No Thumbnail Available
    Item
    Evolution of Extreme Dust Events in 3D Environment
    (The Eurographics Association, 2025) Kress, James; Cui, Wenqiang; Afzal, Shehzad; Ghani, Sohaib; Karumuri, Rama Krishna; Hoteit, Ibrahim; Feige, Kathrin; Nsonga, Baldwin; Rink, Karsten
    Dust is one of the main components of atmospheric particles in desert regions. The concentration, composition, and spatial distribution of these dust particles in the atmosphere vary over time and could significantly impact the weather, climatological conditions, radiative forcing and transfer, and ecosystem dynamics. Scientists and decision-makers are interested in analyzing the evolution of dust events (including their formation, dynamics, and interactions with the environment), understanding the main contributing factors and atmospheric conditions that intensify these events and lead to extreme dust events, examining the role of topographic features, and gaining insights into their relationship with global teleconnections. Scientists use highresolution simulation models (such as WRF-Chem) to simulate the prevalent atmospheric conditions centered around extreme events and examine the model outputs to understand such events better. These simulation datasets are extremely large in scale, depending on the spatial domain, spatiotemporal resolutions, simulation duration, and number of atmospheric parameters. They need a specialized environment that facilitates analyzing such datasets. To this end, we provide a 3D visualization system that facilitates the analysis of dust simulation model outputs and provides information about dust loading, transport, evolution, deposition, and intensification into an extreme event. This system also aids in understanding the interactions between different atmospheric parameters, the impact of terrain surface characteristics, and more, providing a holistic view of the dust events. We present a case study demonstrating the system's capabilities in analyzing extreme dust events and also include feedback from the domain experts, along with a discussion on future extensions.
  • Thumbnail Image
    Item
    Enhancing Apple Variety Testing with Ontology-Enriched Visual Analytics: A Decision-Support Framework
    (The Eurographics Association, 2025) Chuprikova, Ekaterina; Guerra, Walter; Stocker, Robert; Mejia-Aguilar, Abraham; Monsorno, Roberto; Feige, Kathrin; Nsonga, Baldwin; Rink, Karsten
    In this work, we propose an ontology-driven visual analytics approach to support apple variety testing by integrating heterogeneous data sources, including climate records and both qualitative and quantitative agronomic observations. Our methodology includes the development of the Apple Trait Ontology, which standardizes trait definitions and enhances semantic interoperability during data integration, and the implementation of an interactive visual analytics system. This system offers an in-depth overview of apple variety performance over the years by examining key attributes-such as red over color, size, firmness, acidity, starch content, and sugar levels-along with other qualitative and quantitative characteristics. By leveraging ontology-enriched data structuring, the system enables expert-driven interpretation of variety performance, providing a comprehensive decision-support tool for agricultural domain experts. The apple variety-testing visual analytics system integrates spatiotemporal analytics, multimodal visual representations, and interactive filtering, allowing users to explore trait performance trends, climate resilience, and overall suitability under different environmental conditions. The findings demonstrate that combining semantic models with visual analytics enhances the accessibility and usability of complex agricultural data, ultimately improving breeding strategies and decision-making in apple variety selection. This research contributes to the broader field of agricultural informatics by showcasing the potential of knowledge-based systems to support precision farming.
  • Thumbnail Image
    Item
    High-Resolution Urban Climate Visualization: A Dual-Screen Approach for Public Engagement
    (The Eurographics Association, 2025) Huber, Christoph; Nagel, Till; Stuckenschmidt, Heiner; Feige, Kathrin; Nsonga, Baldwin; Rink, Karsten
    Rising urban temperatures and climate variability increasingly affect city residents, yet accessible tools for understanding local climate dynamics remain scarce. This paper presents an interactive visualization of Mannheim's urban microclimate, designed primarily for citizens to explore climate patterns in their neighbourhood. The system is based on a high-resolution, AI-supported climate model that integrates real-time sensor data on temperature, perceived temperature, humidity, wind conditions, and global radiation. To provide intuitive access to climate variability, the visualization presents data for a full summer week, revealing diurnal patterns and variations across different weather conditions. The system aims to balance context and detail and is deployed on an interactive touch-table, complemented by an auxiliary screen in order to display the entire city for an overview, allowing users to focus on selected districts while maintaining comparability and contextualization. By mapping fine-scale climate variations onto familiar administrative units, the tool enables citizens to better understand microclimatic changes and their local implications. This work contributes to environmental visualization by combining geospatial modelling with intuitive visual representations to foster climate literacy and informed urban adaptation strategies. We discuss design choices, user engagement considerations, and the potential for extending the system to predictive modelling and scenario-based exploration.