Modeling and Visualizing Snow Cover Variability by Almost-Periodic Analysis

The paper proposes an algorithm for spatial visualization of snow cover variability based on a nearly periodic analysis of linearized data obtained from preliminary polygonal transformation of satellite images of snow mass, and a mathematical model of an avalanche based on the smoothed particle hydrodynamics method. Data transformation involves forming a matrix of brightness values of discretization nodes obtained by applying an approximating grid to the spatial structure of the snow mass on a satellite image. A system of uniform longitudinal and transverse intervals of homogeneous behavior of linearized data obtained from the results of transformation of snow mass images is revealed. A set of uniform intervals of uniform behavior of linearized data determining the degree of snow cover variability is compiled. Based on the established intervals of uniform behavior of data obtained from preliminary polygonal transformation of satellite images, spatial qualitative and quantitative criteria for snow cover variability are proposed. Based on the proposed criteria, a condition for a snow avalanche descent is formulated. The proposed approach is applicable for the rapid assessment of avalanche danger based on the analysis of satellite images.