‘Killer Lake’ in Africa Looks Like Paradise, But It’s Hiding a Deadly Secret

Science Alert  January 27, 2022 Lake Kivu one of Africa’s great Rift lakes lies between Rwanda and the Democratic Republic of Congo. Thousands of years of volcanic activity has caused a massive accumulation of methane and carbon dioxide to dissolve in the depths of Kivu. If triggered, a so-called limnic eruption would cause “a huge explosion of gas from deep waters to the surface” resulting in large waves and a poisonous gas cloud that would put the lives of millions at risk. A company called KivuWatty pumps water saturated with carbon dioxide and methane from around 350 meters (1,150 feet) […]

Tsunamis’ magnetic fields are detectable before sea level change

Phys.org  December 21, 2021 The motion of conductive seawater by tsunamis can generate magnetic fields in the presence of the background geomagnetic main field. Previous studies found that, using the tsunami-generated seafloor magnetic field, it is possible to predict the propagation direction and wave height prior to the actual arrivals of tsunamis. In this study researchers in Japan correlate the tsunami magnetic field and the tsunami sea level change using observed data and three-dimensional simulations of the 2009 Samoa and 2010 Chile tsunamis. Their direct comparison of the tsunami observed magnetic field and tsunami sea level change illustrated that the […]

AI system identifies buildings damaged by wildfire

Phys.org  September 16, 2021 Existing technologies lack accuracy and ability to scale to effectively aid disaster relief and recovery. Even today, most wildfire event inspectors visit sites and manually classify building damage using before and after images of the buildings. A team of researchers in the US (Stanford University, California Polytechnic State University) has developed DamageMap, an artificial intelligence-powered post-wildfire building damage classifier. It is a binary classifier. Unlike existing solutions DamageMap relies on post-wildfire images alone by separating the segmentation and classification tasks. The model has an overall accuracy of 98% on the validation set (five wildfire events all […]