A recent study provides an assessment of pluvial flood risks in the Metropolitan City of Venice through an innovative Machine Learning methodology that considers spatio-temporal variables.
Geologists found deposits of volcanic rock and ash farther out from ubehebe than at similar volcanic craters because of better preservation, suggesting that similar volcanoes may have wider hazard zones than previously thought.
A new study has found that Individuals from disadvantaged backgrounds are more likely to experience disaster-related home loss, and they are also more likely to develop functional limitations following the disaster.
Global warming is expected to lead to an accumulation of particularly intense hurricanes in the United States. This may substantially increase the economic losses caused by these storms.
When tectonic plates collide and thrust over each other and cause an earthquake, a tsunami can occur. That should not happen in an earthquake where the plates slide past each other. A team of researchers has a new solution to the riddle.
New research in the Journal of the American Geriatrics Society found that nursing homes in California that face a greater risk of wildfire exposure have poorer compliance with Medicare’s emergency preparedness standards.
Researchers from Brown and MIT suggest how scientists can circumvent the need for massive data sets to forecast extreme events with the combination of an advanced machine learning system and sequential sampling techniques.
Research from the University of Washington shows that signals from the upper atmosphere could improve tsunami forecasting and, someday, help track ash plumes and other impacts after a volcanic eruption.
