Geology Today 

About: Geology Today is an academic journal published by Geological Society of London. The journal publishes majorly in the area(s): Geology & Volcano. It has an ISSN identifier of 0266-6979. Over the lifetime, 793 publications have been published receiving 4979 citations.

Low Grade Metamorphism

Abstract: Diagenesis refers to those changes which take place in sediments after sedimentation but before lithification (the conversion to solid rock), while metamorphism is defined as the process whereby alterations to the composition, texture or mineralogy take place in consolidated rocks. However, the boundary between diagenesis and metamorphism is gradual/transitional and somewhat arbitrary; it cannot be sharply defined. A consequence of this is that studies of rocks affected by alteration at low temperatures and pressures have been neglected. Within the last decade, however, more attention has been focused on this type of alteration and significant advances have been made in the field of low-grade metamorphism, particularly over the last five years or so. The Caledonide rocks of Wales have been at the forefront of such investigations.

Google Earth: a new geological resource

Abstract: Since its release in June 2005, Google Earth has been bringing satellite images of our planet into our homes, or at least to those homes with broadband connections. Computer users, excited by seeing their own houses from on high, or even their cars parked in the drive, have been raving about this impressive piece of software which can be downloaded to your PC (but not, as yet, your Mac) free of charge. After a weekend playing around with Google Earth, I can confirm that there is a whole range of potential applications for this software in teaching Earth science.

Landslide prediction from machine learning

Abstract: Predicting where and when landslides are likely to occur in a specific region of interest remains a key challenge in natural hazards research and mitigation. While the basic mechanics of slope-failure initiation and runout can be cast into physical and numerical models, a scarcity of sufficiently detailed and real-time measurements of soil, rock-mass and groundwater conditions prohibits accurate landslide forecasting. Researchers are therefore increasingly exploring multivariate data analysis techniques from the fields of data mining or machine learning in order to approximate future occurrences of landslides from past distribution patterns. This work has elucidated patterns of spatial susceptibility, but temporal forecasts have remained largely empirical. Most machine learning techniques achieve overall success rates of 75–95 percent. Whilst this may seem very promising, issues remain with data input quality, potential overfitting and commensurate inadequate choice of prediction models, inadvertent inclusion of redundant or noise variables, and technical limits to predicting only certain types and sizes of landslides. Simpler models provide only slightly inferior predictions to more complex models, and should guide the way for a more widespread application of data mining in regional landslide prediction. This approach should especially be communicated to planners and decision makers. Future research may want to develop: (1) further best-practice guidelines for model selection; (2) predictions of occurrence and runout of large slope failures at the regional scale; and (3) temporal forecasts of landslides.

The Scandinavian Caledonides: a complexity of collisions

Abstract: Thrust sheets dominate the structural framework of the Scandinavian Caledonides. Sheets at lower tectonostratigraphic levels comprise the shortened margin of the continent Baltica and, at higher levels, terranes derived outboard from this continent in oceanic or foreign continental environments. Amalgamation of these terranes with the margin of Baltica occurred during closure of the Iapetus Ocean in the early Palaeozoic. Closure involved subduction of oceanic crust, extensional tectonics and continent-arc collisions during the late Cambrian and early Ordovician, and ultimate continent-continent collision during the Silurian and Devonian.

Unlocking the applications of automated mineral analysis

Abstract: Identifying and quantifying the relative abundance of minerals is a fundamental part of many aspects of both pure and applied geology. Historically, quantitative mineralogy could be achieved using optical microscopy and point counting. This is a slow and operator dependent process, and practically impossible to achieve in, for example, very fine grained samples. Over the last decade a range of automated mineralogy technologies have arisen from the global mining industry and are being increasingly used in other branches of geology. These technologies, based on scanning electron microscopy with linked energy dispersive spectrometers, have the potential to revolutionise how we quantify mineralogy. In addition, during measurement, the sample textures are also captured, providing a wealth of valuable data for the geologist. In this article we review the current state of automated mineralogy and highlight the many areas of application for this technology.