摘 要
地震灾害是全球范围内最具破坏性的自然灾害之一，其引发的地表形变对人类社会和自然环境造成了深远影响。为提高地震灾害评估的科学性和准确性，本研究聚焦地表形变监测技术在地震灾害评估中的应用，旨在通过先进的遥感与测量手段揭示地震前后地表变化规律及其潜在风险。研究采用合成孔径雷达干涉测量（InSAR）、全球导航卫星系统（GNSS）以及无人机倾斜摄影等多种技术手段，结合地质构造分析和数值模拟方法，构建了一套多源数据融合的地表形变监测体系。通过对典型地震案例的分析，验证了该体系在地表位移监测、断层活动性识别以及震后灾害评估中的有效性。结果表明，InSAR技术能够高精度捕捉区域尺度的地表形变特征，而GNSS则在局部动态监测中表现出显著优势，二者结合可实现时空分辨率的互补。此外，无人机倾斜摄影为震后快速评估提供了直观的三维可视化支持。本研究的主要创新点在于提出了多技术协同的地表形变监测框架，并首次将机器学习算法引入形变数据分析，显著提升了异常信号的识别效率和精度。研究成果不仅为地震灾害评估提供了新的技术路径，也为防灾减灾决策支持系统的发展奠定了重要基础。
关键词：地表形变监测；InSAR技术；GNSS
ABSTRACT
Earthquake disasters are among the most destructive natural calamities globally, inducing surface deformations that have profound impacts on human society and the natural environment. To enhance the scientific rigor and accuracy of earthquake disaster assessment, this study focuses on the application of surface deformation monitoring technologies in earthquake evaluation, aiming to reveal the patterns of surface changes and their associated risks before and after seismic events through advanced remote sensing and measurement techniques. The research employs a combination of interferometric synthetic aperture radar (InSAR), global navigation satellite systems (GNSS), and unmanned aerial vehicle (UAV)-based oblique photogrammetry, integrated with geological structural analysis and numerical simulation methods, to establish a multi-source data fusion system for surface deformation monitoring. Through the analysis of typical earthquake cases, the effectiveness of this system in monitoring surface displacements, identifying fault activities, and assessing post-earthquake damages is validated. Results indicate that InSAR technology can capture regional-scale surface deformation characteristics with high precision, while GNSS demonstrates significant advantages in local dynamic monitoring, enabling complementary spatial and temporal resolutions when combined. Additionally, UAV oblique photogrammetry provides intuitive three-dimensional visualization support for rapid post-earthquake assessments. A key innovation of this study lies in proposing a multi-technology collaborative fr amework for surface deformation monitoring and introducing machine learning algorithms into deformation data analysis for the first time, which substantially improves the efficiency and accuracy of anomaly signal detection. The findings not only offer new technical approaches for earthquake disaster assessment but also lay an important foundation for the development of decision-support systems in disaster prevention and mitigation.
Keywords: Surface Deformation Monitoring; InSAR Technology; Gnss
目 录
摘 要 I
ABSTRACT II
第1章 绪论 1
1.1 地表形变监测技术的研究背景 1
1.2 地震灾害评估中的技术需求与意义 1
1.3 国内外研究现状分析 2
1.4 本文研究方法与技术路线 2
第2章 地表形变监测技术原理与方法 3
2.1 地表形变监测的基本概念 3
2.2 遥感技术在地表形变监测中的应用 3
2.3 GPS技术的地表形变监测功能 4
2.4 InSAR技术的原理与优势 4
2.5 各种技术的对比与选择 5
第3章 地表形变监测在地震灾害评估中的应用 6
3.1 地震前后地表形变特征分析 6
3.2 地表形变数据对震源机制的反演 6
3.3 地表形变监测在地震烈度评估中的作用 7
3.4 地震灾害风险区划中的地表形变信息 7
3.5 实例分析：某地区地震灾害评估 8
第4章 地表形变监测技术的优化与展望 9
4.1 监测技术精度提升的关键因素 9
4.2 数据处理与解释的技术改进 9
4.3 多源数据融合在地表形变监测中的应用 10
4.4 地表形变监测技术的未来发展方向 10
4.5 技术推广与实际应用的挑战 11
结论 12
参考文献 13
致 谢 14
