【摘要】 隧道洞口仰坡的稳定性直接影响隧道工程的安全运行。传统的隧道洞口仰坡检测方法存在覆盖范围有限、操作复杂等局限性。为此，研究提出了一种基于无人机遥感监测技术的隧道洞口仰坡地表位移检测方法，通过运动恢复结构法实现仰坡的三维重建，并采用GM(1,1)模型处理遥感数据，实现地表位移检测。研究结果表明，三维模型重建具有极高的精度，误差控制在1.25 mm以内。研究提出的检测方案在水平和垂直位移检测上的最大误差分别为1.29 mm和1.00 mm，平均误差低至0.64 mm和0.02 mm，远低于对比方案。在检测方案的数据支持下，施工团队能够有效减少沉降量，控制水平位移，扩大施工过程中的稳定区域。研究提高了隧道洞口仰坡地表位移检测精度，为隧道工程的安全运营提供了有力的技术支持，具有较高的实际应用价值。更多还原

【Abstract】 The stability of tunnel entrance slope directly affects the safe operation of tunnel engineering.Traditional detection methods of tunnel entrance slopes are limited in coverage and complicated in operation. Therefore,a surface displacement detection method based on UAV remote sensing monitoring technology is proposed for tunnel entrances. The three-dimensional reconstruction of the slope is realized through the motion recovery structure method,and the remote sensing data is processed by GM(1,1)model to realize surface displacement detection. The results show that the 3D model reconstruction has a very high precision,and the error is controlled within 1.25 mm. The maximum error of horizontal and vertical displacement detection schemes proposed in this study is 1.29 mm and 1.00 mm respectively,and the average error is as low as 0.64 mm and 0.02 mm,which is much lower than the comparison schemes.And with the support of the data of the detection scheme,the construction team can effectively reduce the settlement amount,control the horizontal displacement,and expand the stable area in the construction process. The research improves the detection accuracy of the surface displacement of the tunnel entrance heading slope,provides powerful technical support for the safe operation of tunnel engineering,and has high practical application value.更多还原