Creating Near Real-Time Decision Analytics

We harness data as they become available to support faster, better informed decisions. We turn complex models and simulations into user-friendly discovery tools by developing sophisticated back-end algorithms and interactive front-end dashboards that visualize data clearly and quickly.

Responding to Need

We believe that making discoveries through data should be possible for anyone, and that decision makers should have easy access to the robust scientific information they need to help them make tough choices.

Our scientists combine experience in computer-human interaction, modeling, programming and geovisualization to produce systems that display data clearly, allow for intuitive interaction and help compare what-if scenarios of alternative futures.

Learn more about the interdisciplinary researchers creating geospatial decision analytics:

Faculty at the Frontier

Controlling Pest Invasion with PoPS

Every six months, our researchers meet with officials from the US Department of Agriculture and state agencies to run new simulations with our Pest or Pathogen Spread (PoPS) framework, using an interactive, web-based dashboard to test control strategies aimed at preventing the spread of invasive pests like spotted lanternfly.

Watch PoPS in action

Postdoctoral Positions Available for Modeling the Spread of Invasive Species

The Biological Invasions group of the Landscape Dynamics Lab at NC State’s Center for Geospatial Analytics is seeking two postdoctoral scholars. Applications will be reviewed until the positions are filled.

GIS Service Learning to Support Public Lands, First Responders, City Planning and More

During the Fall 2022 semester, our graduating professional master’s students worked with industry, government and nonprofit partners to apply their knowledge and skills to pressing geospatial challenges.

an orange snow shovel cuts through a pile of snow

New Visualization Tool Helps Weather Forecasters and Researchers More Easily Identify and Study Bands of Heavy Snow

Geospatial Analytics Ph.D. candidate Laura Tomkins developed a new way for meteorologists and atmospheric scientists to quickly and easily distinguish heavy snow from mixed precipitation in weather radar imagery, to improve understanding of snowfall during winter storms.

A group of scientist testing out sensors for research

$1M NSF Grant Awarded to Help Better Predict Emerging Plant Disease Pandemics

Our researchers plan to use real-time analytics through sensor technology, data mining, remote sensing and modeling to better monitor and predict plant diseases.

Insect - Center for Geospatial Analytics at NC State University

Forecasting the Arrival of an Insect Pest

Invasive agricultural pests are a big problem, and the first step to preventing or minimizing their damage is determining whether an area is environmentally suitable for invasion. Predicting *when* a pest is likely to arrive, though, is just as important as anticipating *where*…