New Research
During Droughts, Thirstier Mountain Forests Could Mean Less Water Downstream
Research led by Geospatial Analytics Ph.D. student Katie McQuillan finds increased water use by upstream mountain forests could leave less water for other forests, cities and wildlife during drought.
Study: U.S. Flood Damage Risk Is Underestimated
A research team led by Geospatial Analytics Ph.D. student Elyssa Collins used artificial intelligence to predict where flood damage is likely to happen in the conterminous United States, suggesting that recent flood maps from the Federal Emergency Management Agency do not capture the full extent of flood risk.
KABOOM! Launches Playspace Mapping Program in Colorado
New research co-led by Assoc. Director Aaron Hipp will evaluate the locations and quality of playspaces to address racial and economic gaps in access to quality spaces for play.
Untangling the Complexity of Stormwater Problems
Research led by Geospatial Analytics Ph.D. student Corey White modeled stakeholders' perceptions of flooding problems and solutions in the Triangle Region of North Carolina to inform the development of an innovative serious game called TomorrowNow.
Keeping Track of Rare Mountaintop Plants with Drones
Researchers from the Center for Geospatial Analytics have devised a method to more safely and efficiently monitor endangered high-elevation plants, by predicting their likely locations and then flying drones in high-probability areas to collect imagery.
PoPS: The Data-Driven Decision-Making Tool
The US Department of Agriculture's Plant Protection and Quarantine program is using a forecasting framework developed at the Center for Geospatial Analytics to design and test control strategies for the invasive spotted lanternfly.
Seeing the Earth for the Forests
Geospatial Analytics Ph.D. student Ian McGregor is using satellite imagery and time series modeling to help conservation agencies detect illegal logging in near real-time in protected forests. Find out more in his guest post on the NC Space Grant news blog.
New PoPS Border Simulation Supports Front Lines of Pest Detection
Software developers at the Center for Geospatial Analytics have released the first version of a pest or pathogen spread (PoPS) simulation that can quantify the effectiveness of inspections at ports of entry and reveal how many pests are missed.
Observing Long-Term Annual Land Surface Phenology at Medium Spatial Resolution
Geospatial Analytics Ph.D. student Xiaojie Gao has developed a new approach to track landscape-scale changes in plant life cycles using Bayesian methods and 30-m-resolution Landsat imagery.
Researchers Design Simulation Tool to Predict Disease, Pest Spread
A team led by Research Scholar Chris Jones developed a computer simulation tool called PoPS to predict pest and disease attacks on crops or forests, and to test when and where to apply pesticides or other management strategies to contain them.