Information and Logic Model Development Natural Engineering System Environmental Monitoring

Abstract

Environmental monitoring is the main source of information on the current environment state and its changes associated with man-made and anthropogenic impact. The system of environmental monitoring of increased danger technogenic objects includes state observations of air and water environments, soil snow cover, as well as monitoring of flora and fauna, including biotesting and bioindication. An example of an integrated approach to organizing the environment conditionobserving system is environmental monitoring in the zone of chemical weapons destruction facilities. The results of monitoring activities are numerical arrays of quantitative indicators of the environment state related to specific monitoring objects: concentrations of pollutants in natural environments (air, water, and soil); indicators of the state of flora and fauna; bioindication results. The complexity of the monitoring result integrated analysis is primarily associated with the diversity of the structure and number of indicators for individual natural environments, different dimensions of indicators, as well as the sparseness of the matrices of data arrays. Taking into account the above-mentioned information, it is relevant to develop methods for storing and updating environmental monitoring data arrays, as well as algorithms for operational analysis of the results of monitoring studies. The paper presents an information and logical model that allows to form databases for storing and replenishing data on the state of the natural engineering system. The developed information and logic model is focused on building OLAP cubes for subsequent analysis of environmental monitoring data. The presented information and logical model is the main stage of developing a system for storing, updating and analyzing the results of environmental monitoring of the TCP. Systematization and structuring of indicators of natural environments and ecosystems makes it possible to formulate a number of practical tasks for assessing and predicting the state of the environment in the presence of technogenic impact.