Data Science for Science

Courtesy: James Stuby (NASA) / Wikimedia Commons A crater is a structure or geological formation that is produced as a result of impact of a smaller body upon a larger heavenly body. Craters are found on all solid heavenly bodies such as Earth, the Moon, Mars, Mercury, Venus etc.  Studying craters is important because they are time capsules to how our Solar System evolved and gives us clues to the past, present and future of the evolution of planetary bodies without humans setting foot on them. Crater densities have been correlated with surface age and crater counts have been used used to estimate the relative age of the lunar surface. There are many other uses to studying craters, so it is important to be able to detect craters quickly in an automated fashion. This research uses a novel method of detecting craters by using multiple co-registered data sources: optical images, digital elevation maps (DEMs) and slope maps of the lunar surface. The method uses a deep learning architecture

Aloha! Today we have an entry in Geology. Earthquakes are notoriously difficult to predict. Now researchers have found a way, using AI techniques, to predict the occurrence of "slow" earthquakes. Slow earthquakes can last for a period of weeks or even months but because of their low intensity nature do not cause much damage. They may not even be felt by us. Continuous seismic waves carry the potential signature of an upcoming  slow slip  failure. These seismic waves can be analysed to find patterns and from the regularity in these patterns predictions can be made as to when an event could occur and its intensity. Credit: Earthquake Research Institute, University of Tokyo The researchers created a list of characteristics that precede the appearance of earthquakes. Among them, the researchers noted an exponential increase in seismic energy prior to rupture, as if more and more tiny seismic waves were being emitted from the seismic zone. These crackles were noticeable up to thre