We introduce GeaVR, an open-source package containing tools for geological-structural exploration and mapping in Immersive Virtual Reality (VR). GeaVR also makes it possible to carry out quantitative data collection on 3D realistic, referenced and scaled Virtual Reality scenarios. Making use of Immersive Virtual Reality technology through the Unity game engine, GeaVR works with commercially ava…
Inland water bodies play a vital role at all scales in the terrestrial water balance and Earth’s climate variability. Thus, an inventory of inland waters is crucially important for hydrologic and ecological studies and management. Therefore, the main aim of this study was to develop a deep learning-based method for inventorying and mapping inland water bodies using the RGB band of high-resolu…
In the field of geosciences, the integration of artificial intelligence is transitioning from perceptual intelligence to cognitive intelligence. The simultaneous utilization of knowledge and data in the geoscience domain is a universally addressed concern. In this paper, based on the interpretability of deep learning models for rock images, rock features such as structure, texture, mineral and …
The challenges faced by science, engineering, and society are increasingly complex, requiring broad, cross-disciplinary teams to contribute to collective knowledge, cooperation, and sensemaking efforts. However, existing approaches to collaboration and knowledge sharing are largely manual, inadequate to meet the needs of teams that are not closely connected through personal ties or which lack t…
Controlled vocabularies are critical to constructing FAIR (findable, accessible, interoperable, re-useable) data. One of the most widely required, yet complex, vocabularies in earth science is for rock and sediment type, or ‘lithology’. Since 1999 the British Geological Survey has used its own Rock Classification Scheme in many of its workflows and products including the national digital ge…
Lake Chad is facing critical situations since the 1960s due to the effects of climate change and anthropogenic activities. The statistical analyses of remote sensing climate variables (i.e., evapotranspiration, specific humidity, soil temperature, air temperature, precipitation, soil moisture) and remote sensing and ground-truth lake level applied to the period 1993–2012 reveal that remote se…
Missing values in rainfall records might result in erroneous predictions and inefficient management practices with significant economic, environmental, and social consequences. This is particularly important for rainfall datasets in Peninsular Malaysia (PM) due to the high level of missingness that can affect the inherent pattern in the highly variable time series. In this work, 21 target rainf…
Unit hydrographs (UH) are widely used in scientific research and engineering projects to simulate rainfall-runoff processes. There are four main approaches for calculating UH: the traditional, the conceptual, the probabilistic, and the geomorphological approaches. Most software designed to facilitate the estimation of UH is usually based on only one UH approach, limiting its applicability for s…
In the present study, we co-simulate hydrofacies and piezometric data in order to construct geostatistical realizations of underground geology in an area of the West Thessaly basin. This basin is of great importance in terms of sustainable water management and environmental perspective in Greece. Through Plurigaussian modeling, the hydrofacies are first transformed into Gaussian Random Fields. …
The occurrence of geohazards entails sudden, unpredictable, and cascading effects, with numerous conceptual frameworks and intricate spatiotemporal relationships existing between hazard events. Presently, the absence of a unified mechanism for describing and expressing geohazard knowledge poses substantial challenges in terms of sharing and reusing domain-specific knowledge pertaining to geohaz…