基于近景摄影测量的滑坡表面形变监测研究

地质灾害是自然界发生频率最高、破坏性最大、分布最广的灾害之一。其中，滑坡作为最主要的地质灾害，在我国造成了较多人员伤亡和重大经济损失。滑坡监测是预防滑坡灾害的重要手段。在诸多监测物理量中，表面形变作为判断坡体滑移的直接证据，在边坡稳定性分析评价中不可或缺。已有表面形变监测方法如基于 GPS 或北斗系统的高精度定位监测成本高，难以实现高密度布设，获取的滑坡表面位移空间分辨率不足。因此，本文拟发展近景摄影测量算法，开发高时空分辨率、高精度的滑坡表面形变监测技术。

近景摄影测量法相比于其他的表面形变监测方法，具有成本低廉，布设简易、信息量大、可自动化等优势。然而，由于软硬件的限制，该方法在滑坡监测上的应用研究相对较少。近年来随着相机分辨率的不断提高和图像处理算法的快速发展，基于计算机视觉技术的近景摄影测量法在滑坡表面形变监测任务上具有了前所未有的应用前景和巨大的应用价值。

本研究设计并实现了基于近景摄影测量的滑坡表面形变监测系统，该系统在地面固定点架设高分辨率光学相机，并在坡面上设置多个醒目标志物。相机周期性地自动拍摄坡面图片，通过图像处理与机器学习相结合的方法提取标志物的特征进行目标检测，随后根据摄影测量方法计算标志物的真实坐标，从而在一连串的时序图像中捕捉标志物的微小位移，得到边坡表面形变。

该系统成功应用于室内滑坡实验，实现了坡面位移场和面应变的监测，表面位移监测精度达到毫米级水平。实际测量测试验证了监测系统的稳定性和准确性。通过多次室内模拟降雨滑坡实验，本文探究了不同模型下滑坡变形破坏特征以及相应的表面形变差异。实验结果表明，在边坡最终破坏前会出现 5 毫米到 10 毫米的缓慢前兆性滑移。所开发的近景摄影测量系统能有效地捕捉到滑坡早期出现的微小形变，可为滑坡预防和预警提供可靠的表面形变证据。目前，该系统已部署于野外滑坡监测试验场，未来拟开展滑坡监测预警实际应用研究。

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