Problems of geoinformation modeling of natural-zonal differentiation in geography

he natural zone is a basic concept of physical geography, reflecting the horizontal differentiation of the geographic sphere from the equator to the poles. Diversification of global geospatial data and the improvement of automatic computer classification methods offer new opportunities for the application of geoinformation analysis algorithms for delimitation of land units by zonal climatic features. The aim of the article is to apply geoinformation modeling to identify natural zonal boundaries, as well as to reveal limitations and problems associated with the uncontrolled classification. We use normalized indicators from the University of Edinburgh database (compiled on the basis of WorldClim data). At the first step, a set of significant climatic parameters necessary to model zonal-climatic groupings of natural complexes: annual temperature range, seasonality of monthly average temperatures, annual sum of average daily temperatures above 0°C, annual seasonality of precipitation, Thornthwaite aridity index and seasonality of potential evapotranspiration, was substantiated by the analysis of the main components. Further, uncontrolled classification of these parameters was carried out according to a different number of classes (15, 22, 72). To obtain a picture similar to the global naturalzonal differentiation, 22 classes are allocated in the model. New zonal-climatic boundaries obtained as a result of modeling were compared with the boundaries of natural zones on maps compiled on the basis of other methodological approaches using the case of Europe. In general new boundaries reflect major regularities of the belt-zonal differentiation of the land and could provide background for further typology of landscapes by means of geoinformation modeling. The study made it possible to identify principal methodological limitations of the geoinformation modeling of natural zones at the global and continental levels. Limitations of the cluster analysis for small-scale mapping of natural complexes are also associated with the complexity of choosing the optimal number of classes to obtain adequate visualization of the spatial structure of natural zonal systems, as well as with the “equal contribution” factor of all climatic variables used for modeling. It is shown that realization of automated modeling algorithms requires other geospatial data, in addition to climatic parameters (even in various combinations). The undoubted advantage of the described approach is the reproducibility of classification algorithms and the possibility to obtain the required degree of detail at the output, depending on specific tasks of particular geo-ecological studies.

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