Substantiation of the appropriateness of applying geographic information systems in landscape-ecological monitoring
Journal: Visnyk of Taras Shevchenko National University of Kyiv. Geology (Vol.88, No. 1)Publication Date: 2020-03-04
Authors : V. Zatserkovnyi; L. Plichko; О. Prylipko; O. Nikolaienko; T. Muzhanova;
Page : 98-105
Keywords : geographic information system; landscape-ecological monitoring; information content; geoinformation modeling;
Abstract
Modern cities are characterized by such negative effects of civilization as urban densification, the pollution of air, water, soil, increasing noise and vibration pollution level, heat islands, the impact of magnetic, electric, ionization fields, etc. There is an unprecedented speed and scale of using various natural resources and contaminating the environment with production and consumption wastes. One of the efficient mechanisms of counteracting these negative effects is landscape-ecological monitoring (LEM) of the present urban ecological infrastructure (constructions and objects designed for protection, restoration and improvement of the natural environment) which is meant to provide the compensating resistance to the consequences of anthropogenic impact. LEM is significant when developing the evidence-based urban environmental policy and optimizing the environmental management system. Taking effective managerial decisions on the improvement of urban environmental situation requires complete and accurate information about basic natural conditions. The research focused on systematic gathering of data on an area mostly belongs to the field of landscape-ecological mapping. The authors have substantiated the necessity of using geographic information systems (GIS) in LEM and presented a model of assessing information gain which can be obtained when applying GIS in LEM. This model enables to assess the reduction of entropy (enhance information content) of LEM system by applying GIS. According to the authors' estimation, the introduction of GIS to LEM will enable to reduce entropy (uncertainty) of a system almost by half, that indicates the need of applying GIS in LEM.
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