Информативность геоинформационной вычислительной визуализации процессов формирования природных объектов

Abstract

The paper discusses informative possibilities and prospects of application of digital nature-like methodology for computational visualization of natural processes of natural system formation based on the proposed order parameter—intensity of integral geophysical field created by host structure-forming outer space. Since the designated order parameter defines the structure and properties of natural systems and processes, the gradient of the parameter defining the structure of the natural object is a measure of its order parameter and, therefore, can serve as a predictor of forecasting the change in its properties and structure. The declared approach is tested using an example of forecasting the process of flood formation and processes of visualization of tectonic stress fields. The authors have developed a method of point prediction of the onset time and flood level based on a three-level neural network model and a method of vector space-time visualization of a hierarchy of tectonic stress fields on the territory of an unlimited area. The research shows that computational operations with the parameter of the regional temperature gradient along with intelligent forecasting methods illustrate the prospects of point medium-, long-term forecasting of hydrometeorological processes provided with long rows of instrumental observation data. Computational visualization of general, background and local fields of tectonic stresses in the territories of unlimited area serves as a source of parametric data for geoinformation-mathematical modeling of tectonic stress field restructuring in processes of tectonosphere self-organization, calculation of position of geodynamic instability loci—epicenters of possible earthquakes, visualization of tectonic currents in the Earth’s crust. Monitoring geophysical data at geodynamic instability loci opens up prospects for point prediction of earthquakes. Calculation of order parameters of natural objects and processes opens up prospects of their computational modeling, derivation of numerical laws of their conjugate development and a scale series of interaction, as well as prediction of the state of geo objects and geo processes at a given geo space point in conditions of increasing global natural variability.