The monitoring and analysis of the coastal lowland subsidence in the southern Hangzhou Bay with an advanced time-series InSAR method
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摘要: 针对PSInSAR方法在沿海地区(尤其是围垦填海等区域)地面沉降监测中存在监测点稀疏和可靠性不高的突出问题,本文提出一种改进的DSInSAR方法。该方法通过特征分解算法估算DS候选点的最优相位,增加了非城市区域监测点密度,并大幅提高了计算效率。分别利用PSInSAR和改进的DSInSAR方法对24景COSMO-SkyMed影像进行时序InSAR分析,获取了2013-2015年杭州湾南岸上虞区地面沉降场的时空演变过程。两种方法获取的地面沉降结果空间分布基本一致,但DSInSAR方法监测点密度明显高于PSInSAR方法,其目标点密度约为后者的3.5倍。利用同期精密水准数据对InSAR结果进行了精度评估,结果表明DSInSAR和PSInSAR方法的平均误差分别为±5.0 mm/yr和±5.5mm/yr,前者略优于后者。上虞区地面沉降主要分布于城区、工业较发达的乡镇及围垦区,最大沉降速度达-30.2mm/yr,结合地质资料、实地踏勘及历史围垦资料分析表明人类活动和填海材料的自然压实是地面沉降的主要原因。研究结果表明,DSInSAR方法在沿海地区地面沉降监测方面具有巨大潜力,可用于进一步研究沿海地区沉降相关的环境问题。Abstract: Time-series InSAR analysis (e.g., permanent scatterers (PSInSAR)) has been proven as an effective technology in monitoring ground deformation over urban areas. However, it is a big challenge to apply this technology in coastal regions due to the lack of man-made targets. An distributed scatterers interferometric synthetic aperture radar (DSInSAR) is developed to solve the problem of insufficient samples and low reliability in monitoring coastal lowland subsidence, by applying a spatially adaptive filter and an eigendecomposition algorithm to estimating the optimal phase of statistically homogeneous distributed scatterers (DSs). Twenty-four scenes of COSMO-SkyMed images acquired between 2013 and 2015 are used to retrieve the land subsidence over the Shangyu District on south coast of the Hangzhou Bay, Zhejiang Province, China. The spatial pattern of the land subsidence obtained by the PS-InSAR and the DSInSAR coincides with each other, but the density of the DSs is three point five times higher than the permanent scatterers (PSs). Validated by precise levelling data over the same period, the DSInSAR method achieves an accuracy of ±5.0 mm/a which is superior to the PS-InSAR with ±5.5 mm/a. The land subsidence in the Shangyu District is mainly distributed in the urban areas, industrial towns and land reclamation zones, with a maximum subsidence rate –30.2 mm/a. The analysis of geological data, field investigation and historical reclamation data indicates that human activities and natural compaction of reclamation material are major causes of the detected land subsidence. The results demonstrate that the DSInSAR method has a great potential in monitoring the coastal lowland subsidence and can be used to further investigate subsidence-related environmental issues in coastal regions.
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Key words:
- coastal areas /
- land subsidence /
- DSInSAR /
- PSInSAR /
- leveling observation
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