Study on the Regularity of Surface Collapse in Goaf using UAV Remote Sensing Technology

Abstract

UAV remote sensing technology is used to analyze the characteristics of surface collapse and evaluate the degree of damage in the mining area, and the regularity of surface collapse in the mining area is studied. The distribution and variation characteristics of surface collapse pits and surface cracks and surface deformation characteristics are obtained from UAV images. Taking the area of collapse pits, the depth of collapse pits, the width of cracks, the drop of cracks, the density of cracks, surface subsidence and surface inclination as the evaluation factors, the fuzzy opinion centralized decision-making of the classical fuzzy comprehensive evaluation method is introduced into the combined weighting method, and the fuzzy comprehensive evaluation model based on AHP-CRITIC method is established. The results show that: (1) From August 2020 to June 2021, 125 surface cracks have increased; Three new collapse pits are generated, with a maximum area of about 323m2 and a maximum depth of about 21m; The surface deformation in the south of the mining area is obvious, forming a settlement funnel. (2) The severe damage degree of surface collapse is mainly distributed near the surface collapse pits, the moderate damage degree is mainly distributed in the central and southern part of the study area, and the mild and slight damage degree is mainly distributed in the periphery of the ore body.