Intelligent characterization of discontinuities and heterogeneity evaluation of potential hazard sources in high-steep rock slope by TLS-UAV technology
Changqing Liu, Han Bao, Tianyi Wang, Jingfeng Zhang, Hengxing Lan, Shengwen Qi, Wei Yuan, Shunichi Koshimura
Abstract
The identification of rock mass hazard sources is fundamental for preventing rockfall and landslide disasters in mountainous regions, with rock mass structural characteristics playing a vital role in hazard assessment. In this study, terrestrial laser scanning (TLS) and unmanned aerial vehicle (UAV) technologies were integrated to enhance the evaluation methodology for rock mass hazard sources, focusing on the Sichuan Yanjiang Expressway project in China. The findings demonstrate that TLS-UAV technology enhanced both spatial coverage and data density in slope modeling. Through integrated algorithmic analysis, rock discontinuities within heterogeneous datasets were systematically identified, enabling quantitative extraction and statistical analysis of key geometric parameters, including orientation, trace length, spacing, and roughness. Furthermore, quantitative models were developed for cohesion, friction angle and the morphology parameter M of in situ discontinuities, respectively, facilitating efficient mechanical parameter acquisition. A novel rock mass hazard index ( RHI ) was developed incorporating discontinuity geometric rating ( DGR ), discontinuity mechanical rating ( DMR ), and slope mass rating ( SMR ). Field validation confirmed the methodology's effectiveness in evaluating risk levels and spatial heterogeneity of rock mass hazard sources, revealing the contribution of different discontinuity sets to the rock mass hazard and identifying the primary discontinuity sets controlling instability mechanisms. This study is of great significance for evaluating discontinuity-controlled rock mass hazard sources and preventing rockfall disasters.