News

Dimitris Papanikolaou at CAGIS (McEniry 307) Wednesday, February 27 1:00

Are Mobility on Demand (MoD) systems more sustainable?

Please join us on February 27th to hear Dr. Dimitris Papanikolaou present his comparative analyses of MoDs and traditional ride hailing services. Are Mobility on Demand (MoD) systems more sustainable? Read more >>

The Where and When of Hay Fever

Charlotte, December 2018. Allergic rhinitis (or hay fever) effects roughly 15 out of 100 Americans, but sufferers have had little guidance on how to avoid the pollen outbreaks that aggrevate thier symptoms. Blooms of trees, grasses and herbaceous plants are to blame, but seasonality and variations in climate have made it hard to understand where it will be, and how long it will last. Add to that... The Where and When of Hay Fever Read more >>

Call for Book Chapter: High-performance Computing for Geospatial Applications

An edited book entitled “High Performance Computing for Geospatial Applications” has been approved by Springer. Editors are Drs. Wenwu Tang (University of North Carolina at Charlotte) and Shaowen Wang (University of Illinois at Urbana-Champaign). Here is the background information of the book. High Performance Computing (HPC) allows for the use of advanced computer systems to accelerate and... Call for Book Chapter: High-performance Computing for Geospatial Applications Read more >>

CAGIS researcher uses space-time visualizations to target outbreaks of mosquito-borne illnesses in Colombia

Charlotte, October 2018. In a new paper, CAGIS researcher and lead author Michael Desjardins describes new methods to visualize the complex, spatio-temporal dynamics of outbreaks in mosquito-born illnesses in Colombia. Outbreaks of chikungunya and dengue fever (both transmitted by the same two mosquitoes) occur unevenly across municipalities both geographically and in... CAGIS researcher uses space-time visualizations to target outbreaks of mosquito-borne illnesses in Colombia Read more >>

Call for Paper: Sustainability Special Issue: Applications of Artificial Intelligence in the Study of Land Use and Land Cover Change

Artificial intelligence has been increasingly used to support the study of coupled land systems, which are complex adaptive spatial systems driven by land use and land cover change. These artificial intelligence approaches comprise: 1)      Machine learning (e.g., artificial neural networks, decision trees), 2)      Evolutionary computation (e.g., genetic algorithms, evolutionary algorithms), 3... Call for Paper: Sustainability Special Issue: Applications of Artificial Intelligence in the Study of Land Use and Land Cover Change Read more >>