Advancing Spatial Information Infrastructures
Innovating underlying methods and technologies
Spatial Information plays a key role in supporting environmental planning, disaster management, smart mobility, precision farming, risk assessment and many other application domains. Spatial Information Infrastructures comprise what it takes to collect, manage and share data in a secure way, to create understanding from data analysis and data visualization, and to support the use of spatial information for planning, controlling and decision making. These infrastructures exist on scales from the enterprise to supranational levels. Our goal is to advance Spatial Information Infrastructures by innovating the underlying methods and technologies.
We do applied research. Our work starts by targeting and understanding real world problems in selected application domains and understanding the related demands for innovating the information and communication technology (ICT) infrastructure. We identify and discuss new approaches and apply common research methods to validate our ideas. Much of this work is experimental software development resulting in prototypes, which may be matured to operational solutions in collaboration with the developer community. A special focus is on the evaluation and adaptation of new approaches associated with current GeoIT trends
We focus on the following topics:
In our current R&D projects, we work on:
- Improving dam monitoring through advanced sensor web technologies
- Enabling near real-time detection of surface water for large scale flood monitoring from Copernicus satellite and in situ data
- Advancing methods and technologies for providing a pan European near real-time air quality information service
- Improving the interoperability of sensor platforms in ocean science
- Improving communication between professional relief workers and citizens by combining automated communication workflow management (BPMN) & GIS
- Improving road safety by predicting risks through advanced data analytics
- Improving traffic flow by optimizing traffic light control based on the analysis of crowd sensed floating car data
- Advancing smart farming applications by enabling IoT and Big Data Infrastructures to manage and analyze streams of geospatial data
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