Geographic Data Sciences

Geographic Data Sciences

Research in this area encompasses geographic data analysis, spatiotemporal data mining to explore spatiotemporal database capabilities with management of uncertainties.  Drawing expertise from interdisciplinary areas such as statistics, data mining, nonlinear dynamics, risk analysis, and optimization, we focus on knowledge discovery from multisensory, diverse, and disparate data streams. National and global priority areas addressed include climate change, energy, critical infrastructures, resources management, and social behavioral models.

Publications

Publications Related to Geographic Data Sciences

Highlights

Scientists Develop Method to Quantify Climate Modeling Uncertainty
ORNL researchers have identified a new method for quantifying uncertainty in climate modeling projections.

Mapping Technology Aids Tsunami Recovery. . .
Relief agencies assist victims of the Asian tsunami using a demographic database developed at ORNL.

LandScan Global Population Database . . .
Accurate depictions of global population distribution are critical for a wide variety of research needs.