MODELING AND SPATIAL ANALYSIS OF THE SOCIAL-ECONOMIC POTENTIAL FIELD (CASE STUDY – RUSSIAN ARCTIC)

• Main Authors: V. L. Baburin, S. V. Badina
• Format: Article
• Language: English
• Published: Laboratory of Complex Mapping, Faculty of Geography, MSU 2017-01-01
• Series: InterCarto. InterGIS
• Subjects: Russian Arctic; social-economic potential; field potential; natural hazards; natural risks
• Online Access: http://intercarto.msu.ru/jour/article/view/477

The article is devoted to a study of spatial distribution of socio-economic potential regularities and its cartographic mapping method. We offer a theoretical justification and a methodical approach to the territorial social-economic potential field construction. We show the possibilities of analyzing social-economic potential field using gradients (including ones for the purpose of risk assessment from natural hazards). Natural hazards risk is a function of the dangerous event probability and potential damage from its impact. The potential field method allows us to consider the natural and economic components of natural risk in a space with single (comparable) dimension. A database of significant socio-economic indicators for the density potential assessing at the municipalities level for the Russian Arctic has been compiled. It includes data on population, fixed assets, gross production and land use. Due to the limited municipal statistics, some indicators have only estimated values calculated by the proportional dependencies using Rosstat data. The density approach allows taking into account the real borders and the degree of concentration of socioeconomic potential in space. This is very important in natural risks assessing. Based on the database, we have calculated the index of territorial social-economic potential density, made spatial interpolation of index values from local maxima and constructed the field of its distribution for the Russian Arctic. This approach makes it possible to estimate the probable value of the density potential at any point in considered territory. This is possible due to the fact that the socio-economic space is represented as complete, not divided by artificial administrative borders. Finally we have analyzed the results and identified specific features of differences in potential distribution in the Russian Arctic.