UDC

910.1+910.3

Authors

Seredkin Konstantin Anatolyevich
North-Western Branch of the P.P. Shirshov Institute of Oceanology (Arkhangelsk, Russia)
e-mail: log23@rambler.ru
Dolgoshchelova Maria Ivanovna
Northern Agency for Hydrometeorology and Environmental Monitoring (Arkhangelsk, Russia)
e-mail: asolie@mail.ru
Korobov Vladimir Borisovich
North-Western Branch of the P.P. Shirshov Institute of Oceanology (Arkhangelsk, Russia)
e-mail: szoioran@mail.ru

Abstract

This article reviews analytic hierarchy process and its advantages and disadvantages in applications. Alternatively, we consider method of direct impact, based on the concept of analytical networks and takes into account factors connection. The authors have proposed additions to the procedure of the method implementing a probabilistic approach to the assessment of factors, which supposes to abandon the uniform distribution of weighting coefficients of factors and enter the real distribution derived from the objectives of Geoecology. We obtained the weighting coefficients to size the evaluation of the anthropogenic impact on the environment of the Arkhangelsk region. We used a number of factors, divided into 5 groups: climatic, ecological, oceanographic, geological and socio-economic. The obtained factors are as follows: thermal regime, fog, hazards, precipitation, density of the river network, crossing the streams, the density of lakes, wetlands, the presence of ice, shores stability, topography, seismicity, exogenous geological processes, soils, permafrost, biological productivity, protected areas, the level of pollution, population, settlement system, transportation hubs, the density of the road network, pipeline routes, railways, ports, the navigation period, airfields. The results of the comparison for each gradation scale of considered anthropogenic load are described. Application of analytical network classification models, such as zoning, leads to change of the boundaries of allocated sites. The impact of a change of the weighting coefficient of influencing factor in a group (decreasing or increasing), when associated factors have high scores, is especially significant. Considering these results, the authors do not exclude the use of these methods for other tasks of multicriteria evaluation in the future.

Keywords

analytical network, analytic hierarchy process, expert assessments, transport infrastructure, influencing factors, Arkhangelsk region

References

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