Research
What we do
Spatial-temporal data, such as those coming from remote sensing techniques, mobile and ground monitoring sensors, numerical models, social media and citizen science, is growing in diversity and volume. These data provide unprecedent opportunities for novel applications. This calls for the representation of the potentially abstract spatiotemporal phenomena into a digital system and effectively manage, integrate, and analyse the data. Our group coined at statistical and machine learning methods for spatial and spatiotemporal data integration, analysis, and information extraction, agent-based modelling, and remote sensing.
Currently, we focus on two research themes: 1) air pollution mapping, exposure assessment, and the linkage to social inequity and health, and 2) urban and natural element extraction and classification from remote sensing imagery.
Geoinformatics is at the interface between cutting-edge technology and Geoscientific applications. Novel breakthroughs commonly occur when addressing domain-specific challenges. We have contributed and are keen on various real-life applications, for example, in forest dynamics monitoring, air quality prediction, environmental modelling, coastal geomorphology, and Geo-health. Please see below our ongoing projects and long-term passion project. You are welcome to join!
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Agent-based model development for human space-time activities and exposure assessment | ||||
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| Geohealth |
We collaborate closely with
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UU | ITC |
UMC |
Swiss THP |
KAUST |
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