OROGRAPHIC BARRIERITY OF POLITICAL BORDERS OF EURASIA
A.N. Fartyshev1,2, A.S. Silaev1
1V.B. Sochava Institute of Geography, Siberian Branch, Russian Academy of Sciences 2Irkutsk State University
Keywords: theory of natural boundaries, digital elevation models, political geography, geopolitics, SRTM, Mann-Whitney U-test
Abstract
The article analyzes the orographic barrierity of political borders of Eurasia using the geoinformation approach. The review of evolution of concepts of natural borders from ancient times to the present day is presented. A classification of the barrierity of political borders has been carried out, including natural, infrastructural, institutional, demographic, ethnocultural, and historical types. The research proposes a method for assessing orographic barrierity of borders using the geoinformation approach through elevation differences in the two-kilometer zone of remoteness from the border, which is calculated using STRM digital elevation models. The article shows significant differences in the conditions of political borders in Eurasia and reveals new patterns between the barrierity and conflict and integration types of borders, such as a high level of barrierity of borders in Southeast Asia, a fairly high level of barrierity of borders on the Korean and Arabian Peninsulas, a low level of barrierity in Eastern Europe and on the Indo-Pakistan border, etc. Using statistical analysis methods, it has been revealed that conflict borders in Eurasia paradoxically more often follow orographic barriers, in contrast to integration borders, exhibiting less naturalness; which, on the contrary, is a refutation of the original theory of natural boundaries. The results of the work can be useful for assessing the influence of geographical entities and for understanding the influence of geographical conditions on the formation and functioning of political borders. The developed neighborhood matrix can serve as an alternative method for calculating the neighborhood weight (wij) in the Moran’s spatial autocorrelation index (Moran’s I).
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