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

While traditional compression tools often degrade visual quality—acting like the "MP3 of 3D"—Grenea's solution maintains professional-grade fidelity. This technological achievement has been recognized ...

Don Murray is cofounder of Safe Software and has spent his career helping organizations bring life to data to make better decisions. The world we live in is spatial. Think about how many times you use ...

Realsee3D is a large-scale multi-view RGB-D dataset designed to advance research in indoor 3D perception, reconstruction, and scene understanding.

In our data-rich world, here’s the most fascinating aspect of spatial analysis: The more complex the problem, the more multi-layered it is, the more powerful spatial analysis is. Understanding and ...

A research team introduces a hierarchical Bayesian spatial approach that integrates UAV and terrestrial LiDAR data to estimate AGB of individual trees in natural secondary forests of northeastern ...

This course covers specialized methods and models that have been created for performing statistical analysis on spatial data. Students will learn basic statistical concepts and how to apply them to ...

Jeremy Goecks (left) is the Assistant Center Director for Research Informatics at the Moffitt Cancer Center (FL, USA), where he is also an Associate Faculty Member in the Department of Machine ...

UVA doctoral student Musa Kazim Azimli uses spatial storytelling to reconstruct an Ottoman Empire slave market.

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 ...