多基线差分雷达干涉测量的大型人工线状地物形变监测

大型人工线状地物是人类改造自然的产物,同人类生活息息相关。本文从大型人工线状地物定义出发,阐述了其形变现象、成因及衍生灾害;并利用多基线差分雷达干涉测量技术(DifferentialSyntheticApertureRadarInterferometry,DInSAR)实施大型人工线状地物形变监测。通过多数据源实验(ENVISATASAR,广州;PALSAR,香港大屿山;TerraSAR-X,深圳),分析了当前高级DInSAR方法,包括永久散射体和相干目标法在监测大型人工线状地物形变上的能力。实验结果表明,采用了不同的影像干涉对组合策略,永久散射体法适合大数据量SAR影像处理,而相干目标法适合小数据量SAR影像分析。微波穿透性和垂直临界基线随波长增加而增加。因此,在波段选择上,低相干区宜选用长波SAR数据(比如ALOSPALSAR)以获取稳健反演结果;而高相干区宜选用短波TerraSAR-X或者ENVISATASAR数据,以获取高精度地表形变场。结合线状地物几何和物理特性,分别从先验基础GIS/GPS数据、SAR数据源选择、PS点提取和模型改进四方面进行分析和探讨,认为面向线状地物形变监测多基线DInSAR模型的研发是亟待解决的问题。     

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DInSAR技术监测玉树地震同震形变场的研究

近二十年来,合成孔径雷达干涉测量技术（DInSAR）作为一种监测地表形变的有效技术得到广泛应用,其视线向精度可达厘米级甚至毫米级。该技术尤其是对监测快速、激烈的地表形变更为有效,如地震、火山等。利用DInSAR技术,选用日本ALOS卫星PALSAR数据,获取了2010—04—14玉树Mw6．9地震的同震形变场。结果表明：地表至少发生过3次地表破裂,沿断层走向的形变分布范围远远大于垂直断层分布范围,形变分布特征以左旋走滑为主。     

基于小基线DInSAR技术监测太原市2003～2009年地表形变场

基于高相干点目标反演缓慢地表形变已成为当前DInSAR技术的研究热点.本文通过融合PS方法和相干目标法优点,采用小基线DInSAR技术提取城市地表形变场,并重点分析了地表线性形变的反演.在此基础上,以太原市为研究区,利用23景ENVISAT ASAR影像,提取了该市2003～2009年的地表形变场.研究结果表明:(1)...     

基于DInSAR的徐州张双楼煤矿地表形变监测研究

徐州煤矿资源开采已造成了大规模的地面沉陷,为了为矿区安全开采和塌陷区环境综合治理提供科学依据,利用雷达差分干涉测量（DInSAR）技术对ALOS PALSAR数据进行处理,获得徐州张双楼煤矿区2011-01-16至2011-03-03期间的地表形变分布图.结果表明,张双楼煤矿在46 d间隔里出现了3处沉降漏斗区域,漏斗中心最大沉降量达到420mm,并且沉降漏斗区域与矿区分布一致,说明DInSAR能够有效地监测矿区地表形变.     

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基于DInSAR与概率积分法的铁路变形监测与预测

为掌握采空区上方铁路实时动态变形及变形趋势,本文提出了合成孔径雷达差分干涉技术（DInSAR）与概率积分法相结合的方法。首先利用DInSAR技术对采空区进行了监测,并利用水准数据对DInSAR结果进行了验证;然后基于DInSAR结果结合概率积分法反算参数,并对参数进行了修正,得到工作面充分采动时的下沉参数;最后利用修正的参数对铁路的变形进行了预测。结果表明两者的结合可以有效地对铁路等线性构筑物进行监测与预测。     

Towards Operational Repeat-Pass SAR Interferometry at Active Volcanoes

Measurement of volcanic surface movement is an operational technique at many volcano observatories to help understand internal processes and to aid in eruption forecasting. The potential of differential radar interferometry (DInSAR) to map patterns of surface deformation on volcanoes is well-proven. However, the technique has not yet become operational, partly because current spaceborne radars were not designed for the task. We discuss the limitations of the European Space Agency's ERS SARs for this purpose in terms of: radar system constraints, volcano surface characteristics, interpretational uncertainties and the operational context. We illustrate the drawbacks at typical stratovolcanoes in South America, chosen to represent a range of conditions. For non expert users of DInSAR, knowing how well DInSAR will work on a particular volcano is important. Freely-available global datasets of vegetation cover and atmospheric water vapour content can be used as proxy measures of coherence and path delay effects, which are the two main determinants of data quality. Operational volcano DInSAR is still years away, but many of the characteristics of such a system can be specified based on the experience learned from earlier radars.