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Texas A&M researchers aim to create a future where data science and artificial intelligence are used to predict, prepare for and respond to natural hazards, from hurricanes to earthquakes.
Meteorologists have gotten a lot better at forecasting the conditions that make tornadoes more likely. But predicting exactly which thunderstorms will produce a tornado and when is harder, and that’s where a lot of severe weather research is focused today
Information about past outlier conditions could provide valuable context to help operators better manage the grid during extreme weather.
The experiences of incarcerated people in Texas prisons, vulnerable to heat-related illnesses, illuminate systemic issues and patterns across units and expand the understanding of heat-related illness and death as an ongoing but preventable disaster.
New research from Texas A&M's Hazard Reduction and Recovery Center underscores how incarcerated individuals are disproportionately affected by record-high heat.
A Texas A&M study found Houston residents who experienced two or more hazardous events in the past five years had a reduction in mental health scores.
Texas A&M researchers have mined location-based data to essential establishments during Hurricane Harvey to develop a framework for monitoring communities’ resilience.
Texas A&M researcher Martial Ndeffo is applying mathematical programs and new approaches to find ways to prevent the spread of diseases.
Voluntary Commitments
The organization has no registered commitments.
The Sendai Framework Voluntary Commitments (SFVC) online platform allows stakeholders to inform the public about their work on DRR. The SFVC online platform is a useful toolto know who is doing what and where for the implementation of the Sendai Framework, which could foster potential collaboration among stakeholders. All stakeholders (private sector, civil society organizations, academia, media, local governments, etc.) working on DRR can submit their commitments and report on their progress and deliverables.
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