GIS-Oriented Database on Seismic Hazard Assessment for Caucasian and Crimean Regions
- Authors: Soloviev A.A.1,2, Soloviev A.A.1,3, Gvishiani A.D.1,2, Nikolov B.P.1, Nikolova Y.I.1
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Affiliations:
- Geophysical Center of the Russian Academy of Sciences
- Schmidt Institute of Physics of the Earth, Russian Academy of Sciences
- Institute of Earthquake Prediction Theory and Mathematical Geophysics, Russian Academy of Sciences
- Issue: Vol 54, No 9 (2018)
- Pages: 1363-1373
- Section: Methods and Means of Satellite Data Processing and Interpretation
- URL: https://journals.rcsi.science/0001-4338/article/view/148668
- DOI: https://doi.org/10.1134/S0001433818090505
- ID: 148668
Cite item
Abstract
Zones of higher seismic hazard occupy about 20% of Russia’s territory, and 5% are characterized by extremely high hazard. These latter are, in particular, regions of Caucasus and Crimea with an aggregate population of about 15 M people. In order to assess seismic hazard and to minimize the consequences of possible earthquakes in these regions, a special-purpose database has been created for these regions; this database and a multifunctional user interface for its operation are currently being developed. For the first time, one software environment has integrated the most complete results on recognizing zones of higher seismicity by independent methods and the initial data on which the recognition was based. Thus, the system allows integrated multi-criteria seismic hazard assessment in a given region. The use of a modern geographic informational system (GIS) has made the preparation, organization, and analysis of these data considerably easier. The GIS makes it possible on the basis of a comprehensive approach to seismic hazard assessment to group and visualize the respective data in an interactive map. The analytical and interactive query tools integrated in the GIS allow a user to assess the degree of risk in regions under consideration based on different criteria and methods. The seismic hazard assessment database and its user interface were achieved using ESRI ArcGIS software, which completely satisfies the scaling requirement in terms of both functionality and data volume.
About the authors
An. A. Soloviev
Geophysical Center of the Russian Academy of Sciences; Schmidt Institute of Physics of the Earth, Russian Academy of Sciences
Email: j.zharkikh@gcras.ru
Russian Federation, Moscow; Moscow
Al. A. Soloviev
Geophysical Center of the Russian Academy of Sciences; Institute of Earthquake Prediction Theory and Mathematical Geophysics, Russian Academy of Sciences
Email: j.zharkikh@gcras.ru
Russian Federation, Moscow; Moscow
A. D. Gvishiani
Geophysical Center of the Russian Academy of Sciences; Schmidt Institute of Physics of the Earth, Russian Academy of Sciences
Email: j.zharkikh@gcras.ru
Russian Federation, Moscow; Moscow
B. P. Nikolov
Geophysical Center of the Russian Academy of Sciences
Email: j.zharkikh@gcras.ru
Russian Federation, Moscow
Yu. I. Nikolova
Geophysical Center of the Russian Academy of Sciences
Author for correspondence.
Email: j.zharkikh@gcras.ru
Russian Federation, Moscow
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