Technology and method research on the early detection of high-level collapse based on the nap-of-the-object photography
LIANG Jingtao1, TIE Yongbo2, ZHAO Cong1, ZHANG Su1
1. Sichuan Geological Survey Evaluation and Utilization of Strategic Rare Metals and Rare Earth Resource Key Laboratory of Sichuan Province, Chengdu 610081, China; 2. Chengdu Center of China Geological Survey, Chengdu 610081, China
Abstract：The high-level collapse has the characteristics of high altitude difference and strong sudden occurrence, so it is difficult to forecast accurately. It is of great significance to carry out the early detection of high-level collapse for disaster prevention and mitigation. It is difficult and inefficient to carry out field investigation by manual work and it is easy to form investigation blind areas. It is difficult to effectively obtain the key parameters such as the occurrence of rock structural plane, joint combination characteristics and fracture geometry characteristics by common investigation techniques. Therefore, the authors applied the nap-of-the-object photography technology with the advantage of high resolution and mutilangle to the early detection of high-level collapse. Taking Guoda-shan high-level collapse in Kangding County as an example, the authors summarized the detailed application process of this technology, which can provide some reference for the geological disaster investigation and early recognition of high-level collapse. The research results show that the nap-of-the-object photography can be used to identify sub-centimeter scale fractures in the rock mass, especially suitable for the high-level collapse investigation and early identification. And on the basis of high-precision 3D model and space analytic geometry theory, the occurrence of rock structural plane can be calculated by three-point method.
梁京涛, 铁永波, 赵聪, 张肃. 基于贴近摄影测量技术的高位崩塌早期识别技术方法研究[J]. 中国地质调查, 2020, 7(5): 107-113.
LIANG Jingtao, TIE Yongbo, ZHAO Cong, ZHANG Su. Technology and method research on the early detection of high-level collapse based on the nap-of-the-object photography. , 2020, 7(5): 107-113.
2020, Vol. 7 
