Researchers at Los Alamos National Laboratory have developed a new approach that addresses the limitations of generative AI ...

Bayesian spatial statistics and modeling represent a robust inferential framework where uncertainty in spatial processes is explicitly quantified through probability distributions. This approach ...

Jeongwon is a Ph.D. student in the Department of Geography at the University at Buffalo. She has a background in GIS engineering, specializing in working with spatial big data and spatial data ...

Location data is critical to nearly all state and local government work — whether it’s responding to a public safety call, supporting community planning and development, or maintaining critical ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...