Particle identification and statistical methods of a rock avalanche accumulation body based on the particle analysis system

Particle identification and statistics of rock avalanche deposits are the focus of researches on rock avalanche disasters. Based on the image processing PCAS particle recognition system, taking the collapse-rock avalanche of the Pusa Village in Nayong of Guizhou Province as an example, combined with the measured results of the particle size of the Nayong collapse, the parameter values of threshold (T), pore throat closing radius (r) and minimum pore area (S₀) during the identification process are explained. The application of PCAS software to the identification and statistics of rock avalanche particles is studied, and the selection methods of these parameters are proposed. The analysis results show that (1) PCAS can automatically and accurately identify debris flow accumulation particles and pores, which are more precise than manual counting. Small particles in each area of the recognized accumulation have a large proportion, and the proportion of 0～2 m particles in each area is more than 50%. (2) When the threshold value is 170 (pixels), a fine binary image can be obtained, and the particles and the pores are accurately distinguished. (3) The particle size distribution results of the deposits obtained under different parameter values are different, and the particle identification of the rock avalanche deposits should adopt larger r and S₀. When r/S₀=3/30 (pixels), the particle size distribution can be better reflected. (4) PCAS is of the high feasibility and the statistical results show that the variation trend of each particle size content is similar to that of artificial statistics. The proportion and distribution of particle sizes in the two statistical methods are basically consistent with each other, which is of great significance for the efficient and convenient analysis of particle size distribution of collapse-rock avalanche.