基于时序InSAR的珠江口大面积地面沉降监测

高辉; 罗孝文; 吴自银; 阳凡林

doi:10.3969/j.issn.1001-909X.2020.02.009

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海洋学研究 ›› 2020, Vol. 38 ›› Issue (2) : 81-87. DOI: 10.3969/j.issn.1001-909X.2020.02.009

研究报道

基于时序InSAR的珠江口大面积地面沉降监测

高辉^1,2,3, 罗孝文^*1,2,3, 吴自银^2,3, 阳凡林¹

作者信息 +

Large area land subsidence monitoring in thePearl River Estuary by InSAR time-series analysis

GAO Hui^1,2,3, LUO Xiaowen^*1,2,3, WU Ziyin^2,3, YANG Fanlin¹

Author information +

文章历史 +

摘要

珠江口是我国沿海地面沉降灾害较严重地区之一,长期地面沉降威胁着人类生产生活的质量和安全。针对传统InSAR在河口等沿海地区空间采样率不足的现状,采用基于KS检验和特征分解的DS-InSAR时序分析方法,获得了珠江口地区2015—2018年间地面沉降监测数据,并分析了几处沉降严重地区的沉降特征和原因。采用的DS-InSAR方法在沥青路面、裸土等非城市区域提取了较大密度的高相干点,提高了时序InSAR形变反演的精度。研究表明,研究区域总体呈地面沉降趋势且分布不均匀,珠江三角洲西北部和东南部为主要沉降区,最大沉降速率可达25 mm/a,珠江口西岸沉降相对东岸分布更广,沉降量更大。

Abstract

The Pearl River Estuary (PRE) is one of the coastal areas with serious land subsidence, which forms a serious threat to the quality and safety of human life and production. In response to the problems associated with the lack of man-made targets of traditional time-series Interferometric Synthetic Aperture Radar (InSAR) in estuaries and other coastal areas, a distributed scatterers InSAR (DS-InSAR) method based on a spatially adaptive filter and an eigendecomposition algorithm to estimating the optimal phase of statistically homogeneous DS was applied to obtain the deformation information in PRE between 2015 and 2018. High-density and high-coherence points were extracted in asphalt pavement, bare soil and other non-urban areas, to improve the inversion accuracy. The results suggest that land subsidence in the PRE was widespread and unevenly distributed. The northwest and southeast are the main subsidence areas, with a maximum subsidence rate greater than 25 mm/a.

导出引用

高辉, 罗孝文, 吴自银, 阳凡林. 基于时序InSAR的珠江口大面积地面沉降监测[J]. 海洋学研究. 2020, 38(2): 81-87 https://doi.org/10.3969/j.issn.1001-909X.2020.02.009

GAO Hui, LUO Xiaowen, WU Ziyin, YANG Fanlin. Large area land subsidence monitoring in thePearl River Estuary by InSAR time-series analysis[J]. Journal of Marine Sciences. 2020, 38(2): 81-87 https://doi.org/10.3969/j.issn.1001-909X.2020.02.009

中图分类号： P642.26

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