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Fristad K.E.,University of Oslo | Pedentchouk N.,University of East Anglia | Roscher M.,University of Oslo | Roscher M.,Beak Consultants GmbH | And 3 more authors.
Palaeogeography, Palaeoclimatology, Palaeoecology | Year: 2015

The largest mass extinction in Earth history occurred at the end-Permian (~252millionyears ago) and is marked by a global negative carbon isotope excursion and the onset of Siberian Trap volcanism, prompting diverse hypotheses on the link between flood basalt volcanism, carbon cycle perturbations, and mass extinction. Phreatomagmatic pipes associated with Siberian Trap volcanism have been proposed as conduits for the release of 12C-enriched carbon gases from thermogenic and/or magmatic sources to the end-Permian atmosphere. Some of the pipes have preserved crater-lake sediments of volcaniclastic origin. This study examined the preserved evidence for 12C-enriched carbon release into the Western Oktyabrsk crater in east Siberia from the underlying volcanic basin. We find that the 13C/12C ratio of the carbonate cement, organic matter, and long-chain n-alkanes in the lacustrine crater sediments support the hypothesis that 12C-enriched carbon infiltrated the basal crater sediments and lake water immediately after crater formation. The values and trends of δ13CCarb, δ13CTOC, and δ13Cn-alkanes in the crater sediments are consistent with 12C-enriched carbon with isotopic values similar to that of carbon sourced from thermogenic and/or 12C-enriched magmatic sources. This implies that carbon release through the pipes in the Tunguska Basin may explain the source of the global negative carbon isotope perturbations, and their coincidence with Siberian Trap volcanism, at the end-Permian. © 2015 Elsevier B.V.


Grant
Agency: European Commission | Branch: FP7 | Program: CSA-SA | Phase: ENV.2007.4.1.4.1. | Award Amount: 2.42M | Year: 2008

Africa, the largest single component of the African Caribbean Pacific (ACP) Group of States, despite its huge potential for development through both human and georesources, suffers in many places from poverty and underdevelopment. The sustainable use of its resources is a key issue, not only for development of the African countries, but also for the worlds future. Over the coming decades, these issues are likely to play an ever-increasing role due to the worlds growing population, rapid urban development and the rising demand for better infrastructure and services. The sustainable use of georesources requires a knowledge based on data, information and expertise. Thus, the availability, traceability, accessibility and processing using GIS technologies of heterogeneous data from multiple sources is essential. Such processing requires a qualified and experienced personnel and the definition of strategies for capacity building and training. In view of this situation, a recognised need has emerged for a shared, distributed, Internet-linked georesources observation system, based on open standards and interoperability developments, as a contribution to the sustainable development of African countries. The Support Action is the preparatory phase needed to design the African-European Georesource Observation System (AEGOS) capable of hosting and providing access to Africas geological resources, including groundwater, energy, raw materials and mineral resources. Its objectives are to define: i) operational procedures for data management (Spatial Data Infrastructure, metadata and data specification), ii) user-oriented products and services including the preparation of innovative spin off projects based on AEGOS and an evaluation of the input of Interoperability and interdisciplinary in support of GEOSS iii) the African- European partner network, iv) a geoscience contribution to GEOSS, in the context of INSPIRE


Noack S.,Beak Consultants GmbH | Barth A.,Beak Consultants GmbH | Irkhin A.,Beak Consultants GmbH | Bennewitz E.,Beak Consultants GmbH | Schmidt F.,Beak Consultants GmbH
International Journal of Applied Geospatial Research | Year: 2012

Artificial neural networks (ANN) are used for statistical modeling of spatial events in geosciences. The advantage of this method is the ability of neural networks to represent complex interrelations and to be "able to learn" from known (spatial) events. The software advangeo ® was developed to enable GIS users to apply neural network methods on raster geodata. This statistic modeling can be displayed in a user-friendly way within the ESRI ArcGIS environment. The complete workflow is documented by the software. This paper presents three pilot studies conducted to illustrate the possibilities of spatial predictions with the use of existing raster datasets, which described influencing factors and the selection of known events of the phenomenon to be modeled. These applications included (1) the prognosis of soil erosion patterns, (2) the prediction of mineral resources, and (3) vulnerability analysis for forest pests. Copyright © 2012, IGI Global.


Noack S.,Beak Consultants GmbH | Knobloch A.,Beak Consultants GmbH | Etzold S.H.,Beak Consultants GmbH | Barth A.,Beak Consultants GmbH | Kallmeier E.,Beak Consultants GmbH
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives | Year: 2014

The modelling or prediction of complex geospatial phenomena (like formation of geo-hazards) is one of the most important tasks for geoscientists. But in practice it faces various difficulties, caused mainly by the complexity of relationships between the phenomena itself and the controlling parameters, as well by limitations of our knowledge about the nature of physical/mathematical relationships and by restrictions regarding accuracy and availability of data. In this situation methods of artificial intelligence, like artificial neural networks (ANN) offer a meaningful alternative modelling approach compared to the exact mathematical modelling. In the past, the application of ANN technologies in geosciences was primarily limited due to difficulties to integrate it into geo-data processing algorithms. In consideration of this background, the software advangeo® was developed to provide a normal GIS user with a powerful tool to use ANNs for prediction mapping and data preparation within his standard ESRI ArcGIS environment. In many case studies, such as land use planning, geo-hazards analysis and prevention, mineral potential mapping, agriculture & forestry advangeo® has shown its capabilities and strengths. The approach is able to add considerable value to existing data.

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