基于时序SAR影像的地下资源开采导致的地表形变监测方法与应用
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摘要
随着经济发展、城市规模和人口数量膨胀以及工业化程度提高,各种资源消耗量急剧上升,地下水、煤炭、石油、天然气等多种地下资源被大量开采,并引发了严重的地面沉降。研究如何快速、高效的对地面形变进行监测,分析其规律及机理具有重要的现实意义。本论文根据InSAR技术特点,将地表线性沉降和非线性沉降区别对待,针对性的对PSInSAR技术和传统DInSAR技术进行改进,提出了基于时序SAR影像的地表形变监测分析方法;分别用改进的PSInSAR技术对北京地下水开采导致的地表形变、用基于时序差分干涉图的方法对澳大利亚某矿区开采导致的地表形变进行了监测分析,讨论、验证了各自结果的准确性与精度。论文主要成果如下:
1)系统阐述了InSAR、DInSAR和PSInSAR的基本原理、技术特点、数据处理流程及其各自的优缺点;总结了国内外相关领域的研究现状及不足。
2)提出了一种基于干涉相位的高精度基线估算方法。该方法从基线误差导致的相位误差分布规律出发,以低精度轨道或星历数据为初始数据,在干涉图中剔除因基线误差导致的相位差。该方法不需要进行相位解缠,也不需要地面控制点的参与,而且还可以用来对别的基线估算方法得到的结果进行“平差”。
3)提出了基于PS点自适应估计的PSInSAR改进处理方法。针对用PSInSAR监测城市及周边地区地表形变存在的SAR图像覆盖区域内存在多个由植被分割开的建筑物群现状,围绕提高PS点密度目的,通过向高可靠性PS参考网引入相对低可靠性离散PS点,提高了PSInSAR处理时PS点的密度,增强了PSInSAR结果的可靠性与精度。实验研究结果显示,用此方法进行PSInSAR处理,无论是高可靠性PS点还是相对低可靠性PS点的数量,比Kampes所用算法都有所提高,相对低可靠性PS点的使用数量提高了近50%。
4)提出了时序差分干涉相位图的误差剔除方法。将PS思想引入时序差分干涉图的数据处理中,剔除时间序列差分干涉图中的DEM误差、大气效应误差和噪声误差,提高了传统DInSAR结果的精度,能明显消除DEM误差和大气效应误差。
5)应用改进的PSInSAR技术对北京地下水开采导致的地表形变进行了监测分析。针对缺乏地面监测数据的情况,应用不同的SAR影像(ENVISAT ASAR和ALOS PALSAR)进行实验,将两者的结果进行交叉验证。结合北京市浅层地下水水位的历史变化数据,对PSInSAR结果进行分析,探讨了浅层地下水水位与地表形变的关系,比较了ENVISAT ASAR和ALOS PALSAR数据用于PSInSAR分析的优缺点。
6)用时序差分干涉数据对澳大利亚某矿区开采导致的地表形变进行了监测分析。为了保证差分干涉图的相干性,选用了长波段的ALOS PALSAR影像进行实验研究。将实验结果与开采工作面位置、推进进度信息相叠加,验证了结果的准确性以及开采沉陷与工作面推进速度之间的关系。将GPS实际监测数据与DInSAR实验结果进行了比较分析,得出GPS监测结果与DInSAR结果大致吻合,两者误差最大值为45mm,平均误差为12mm,标准差为8mm。
7)探讨了DInSAR监测结果用于分析煤矿地表三维形变的方法及可行性。根据煤矿开采工作面的相关信息,采用基于Knothe时间函数的地表动态沉陷预计方法对开采沉陷进行预计,将其与DInSAR结果进行比较,说明一维的DInSAR结果无法满足开采沉陷监测对地表三维形变信息的需求。实验研究了利用DInSAR结果解算地表三维形变的方法,将之与GPS观测的地表三维形变信息对比,得出由DInSAR解算的地表三维形变信息在垂直、正东和正北方向的误差分别为1.4cm、0.7cm和3.5cm,标准差分别为3.0cm、0.7cm和5.9cm。结果表明,在一定的条件下,用DInSAR监测结果分析开采沉陷的动态规律和机理是可行的。
该论文有图63幅,表18个,参考文献119篇。
In recent years, with the rapid growth of economy, industrialization, urbanization and population, the whole world is consuming a huge number of resources. Many kinds of underground resources, underground water, coal, oil and gas, are mined to meet the social requirement. These mine activities has caused devastating ground surface deformation. It is very important to research on how to monitor, analyze and mitigate the ground surface deformation rapidly and efficiently. InSAR is a remote sensing technique for topographic mapping and ground surface deformation monitoring which was developed in recent decades. In order to monitor the ground surface deformation caused by continuous underground resources mine activities, various time-series SAR data processing methodologies and algorithms are developed in this thesis according to two types of ground surface deformation: linear and non-linear.
A high-accuracy baseline estimation algorithm based on the Interferometric phases is developed to enhance the accuracy of InSAR technique. One ALOS PASAR pair is used to evaluate this algorithm, and the result is quite convincing.
The advanced PSInSAR method based on the adaptive estimation of PS points is developed and applied to monitor the linear ground surface deformation caused by underground water extraction around Beijing. Two SAR images dataset, ENVISAT ASAR and ALOS PALSAR, are used for experimental research. The PSInSAR results fit quite well with the underground water level data.
The multiple time-series differential interferograms processing strategy is discussed and applied to monitor the non-linear mine subsidence in Australia. The DInSAR results match quite well with the mine schedule. The accuracy of the DInSAR results is evaluated by the GPS surveying data; it is found that the accuracy of DInSAR results is up to cm level, which is lower than the mm level GPS data.
There are 63 figures, 18 tables and 119 references.
1)系统阐述了InSAR、DInSAR和PSInSAR的基本原理、技术特点、数据处理流程及其各自的优缺点;总结了国内外相关领域的研究现状及不足。
2)提出了一种基于干涉相位的高精度基线估算方法。该方法从基线误差导致的相位误差分布规律出发,以低精度轨道或星历数据为初始数据,在干涉图中剔除因基线误差导致的相位差。该方法不需要进行相位解缠,也不需要地面控制点的参与,而且还可以用来对别的基线估算方法得到的结果进行“平差”。
3)提出了基于PS点自适应估计的PSInSAR改进处理方法。针对用PSInSAR监测城市及周边地区地表形变存在的SAR图像覆盖区域内存在多个由植被分割开的建筑物群现状,围绕提高PS点密度目的,通过向高可靠性PS参考网引入相对低可靠性离散PS点,提高了PSInSAR处理时PS点的密度,增强了PSInSAR结果的可靠性与精度。实验研究结果显示,用此方法进行PSInSAR处理,无论是高可靠性PS点还是相对低可靠性PS点的数量,比Kampes所用算法都有所提高,相对低可靠性PS点的使用数量提高了近50%。
4)提出了时序差分干涉相位图的误差剔除方法。将PS思想引入时序差分干涉图的数据处理中,剔除时间序列差分干涉图中的DEM误差、大气效应误差和噪声误差,提高了传统DInSAR结果的精度,能明显消除DEM误差和大气效应误差。
5)应用改进的PSInSAR技术对北京地下水开采导致的地表形变进行了监测分析。针对缺乏地面监测数据的情况,应用不同的SAR影像(ENVISAT ASAR和ALOS PALSAR)进行实验,将两者的结果进行交叉验证。结合北京市浅层地下水水位的历史变化数据,对PSInSAR结果进行分析,探讨了浅层地下水水位与地表形变的关系,比较了ENVISAT ASAR和ALOS PALSAR数据用于PSInSAR分析的优缺点。
6)用时序差分干涉数据对澳大利亚某矿区开采导致的地表形变进行了监测分析。为了保证差分干涉图的相干性,选用了长波段的ALOS PALSAR影像进行实验研究。将实验结果与开采工作面位置、推进进度信息相叠加,验证了结果的准确性以及开采沉陷与工作面推进速度之间的关系。将GPS实际监测数据与DInSAR实验结果进行了比较分析,得出GPS监测结果与DInSAR结果大致吻合,两者误差最大值为45mm,平均误差为12mm,标准差为8mm。
7)探讨了DInSAR监测结果用于分析煤矿地表三维形变的方法及可行性。根据煤矿开采工作面的相关信息,采用基于Knothe时间函数的地表动态沉陷预计方法对开采沉陷进行预计,将其与DInSAR结果进行比较,说明一维的DInSAR结果无法满足开采沉陷监测对地表三维形变信息的需求。实验研究了利用DInSAR结果解算地表三维形变的方法,将之与GPS观测的地表三维形变信息对比,得出由DInSAR解算的地表三维形变信息在垂直、正东和正北方向的误差分别为1.4cm、0.7cm和3.5cm,标准差分别为3.0cm、0.7cm和5.9cm。结果表明,在一定的条件下,用DInSAR监测结果分析开采沉陷的动态规律和机理是可行的。
该论文有图63幅,表18个,参考文献119篇。
In recent years, with the rapid growth of economy, industrialization, urbanization and population, the whole world is consuming a huge number of resources. Many kinds of underground resources, underground water, coal, oil and gas, are mined to meet the social requirement. These mine activities has caused devastating ground surface deformation. It is very important to research on how to monitor, analyze and mitigate the ground surface deformation rapidly and efficiently. InSAR is a remote sensing technique for topographic mapping and ground surface deformation monitoring which was developed in recent decades. In order to monitor the ground surface deformation caused by continuous underground resources mine activities, various time-series SAR data processing methodologies and algorithms are developed in this thesis according to two types of ground surface deformation: linear and non-linear.
A high-accuracy baseline estimation algorithm based on the Interferometric phases is developed to enhance the accuracy of InSAR technique. One ALOS PASAR pair is used to evaluate this algorithm, and the result is quite convincing.
The advanced PSInSAR method based on the adaptive estimation of PS points is developed and applied to monitor the linear ground surface deformation caused by underground water extraction around Beijing. Two SAR images dataset, ENVISAT ASAR and ALOS PALSAR, are used for experimental research. The PSInSAR results fit quite well with the underground water level data.
The multiple time-series differential interferograms processing strategy is discussed and applied to monitor the non-linear mine subsidence in Australia. The DInSAR results match quite well with the mine schedule. The accuracy of the DInSAR results is evaluated by the GPS surveying data; it is found that the accuracy of DInSAR results is up to cm level, which is lower than the mm level GPS data.
There are 63 figures, 18 tables and 119 references.
引文
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