地球信息科学学报 ›› 2018, Vol. 20 ›› Issue (4): 440-451.doi: 10.12082/dqxxkx.2018.170579

所属专题: 气候变化与地表过程

• 全国激光雷达大会特约稿件 • 上一篇    下一篇

适用于自然地表形变反演的小基线集方法

黄俊松1(), 曾琪明1,*(), 高胜1,2, 焦健1, 胡乐银3   

  1. 1. 北京大学遥感与地理信息系统研究所,北京 100871
    2. 中国科学院电子学研究所,北京 100190
    3. 北京市地震局,北京 100080
  • 收稿日期:2017-12-04 修回日期:2018-02-05 出版日期:2018-04-20 发布日期:2018-04-20
  • 通讯作者: 曾琪明 E-mail:junsongh@pku.edu.cn;qmzeng@pku.edu.cn
  • 作者简介:

    作者简介:黄俊松(1990-),男,博士生,研究方向为InSAR时序分析。E-mail: junsongh@pku.edu.cn

  • 基金资助:
    国家重点研发计划(2017YFB0502703);内蒙古自治区科技厅“数字化矿区资源管理与矿区生态环境监测技术与应用”项目(2015-2019)

An Improved Small Baseline Subset Method for Deformation Retrieval of Natural Terrains

HUANG Junsong1(), ZENG Qiming1,*(), GAO Sheng1,2, JIAO Jian1, HU Leyin3   

  1. 1. Institute of Remote Sensing and GIS, Peking University, Beijing 100871, China
    2. Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China
    3. Beijing Earthquake Agency, Beijing 100080, China
  • Received:2017-12-04 Revised:2018-02-05 Online:2018-04-20 Published:2018-04-20
  • Contact: ZENG Qiming E-mail:junsongh@pku.edu.cn;qmzeng@pku.edu.cn
  • Supported by:
    National Key R&D Program of China, No.2017YFB0502703;Digital Mining Resource Management and Mining Ecological Environment Monitoring Technology and Application Project of the Science and Technology Department of Inner Mongolia Autonomous Region (2015-2019).

摘要:

由于自然地表像元在长期观测中容易发生时空失相干,利用时序InSAR(Synthetic Aperture Radar Interferometry)技术对其开展形变监测会面临可用形变测量点不足的挑战。针对这一问题,提出一种改进的小基线(Small Baseline Subset,SBAS)方法。该方法改进了传统SBAS中初始高相干像元筛选及相位滤波过程:首先利用拟合优度检验,并结合相干性阈值条件来识别同质像元;然后根据同质像元数量将所有像元分成2部分,即PS(Persistent Scatterers)候选点和DS(Distributed Scatterers)候选点;其次分别在这两部分像元中开展初始高相干PS点及DS点筛选;最后对选出的高相干PS点及DS点进行加权相位滤波。利用覆盖北京平原区西北部(含城区及山区)的27景ENVISAT ASAR影像开展的形变监测实验表明:与2个参考方法相比,该方法能够有效扩展形变结果上的测量点数量和覆盖范围,测量点数量分别提高了22.6%及27.6%,且自然地表的形变测量点密度得到了明显提升。同时,研究区形变结果与4个连续GPS站的位移数据有很好的一致性,证明了该方法在地表形变反演中的有效性及优越性。

关键词: SBAS, 形变, 时序InSAR, PS-InSAR, PS, DS

Abstract:

Owning to that the pixels in natural terrains are prone to spatial-temporal decorrelation during the long-term observation, using time-series InSAR (Synthetic Aperture Interferometry) technique to carry out deformation monitoring of natural terrains will face the challenge of lacking of available deformation measurement points. To solve this problem, an improved Small Baseline Subset (SBAS) method is proposed. It improves the selection process of initial high coherent pixels and phase filtering in conventional SBAS. Firstly, it uses the goodness of fit and the coherence threshold condition to identify statistically homogeneous pixels (SHP). After this, all pixels are divided into two parts base on the number of SHP, i.e. Persistent Scatterers (PS) candidates and Distributed Scatterers (DS) candidates. Then, initial high coherent PS and DS are selected from these two parts respectively. Finally those selected high coherent PS and DS are filtered by a weighted phase filter. The deformation monitoring experiment with 27 ENVISAT ASAR images, acquired over the northwest part of Beijing plain shows that: compared with StaMPS-PS (refers to the PS-InSAR in StaMPS) method and StaMPS-SBAS (refers to the SBAS in StaMPS) method, the improved method can effectively extend the quantity and coverage of deformation measurement points. The quantity of measurement points is increased by 22.6% and 27.6% respectively, and the deformation result of natural terrains is improved effectively. The deformation result of this study area is in good agreement with the displacement of 4 continuous GPS stations. Experimental results prove the effectiveness and superiority of this method in the inversion of ground deformation.

Key words: SBAS, deformation, time-series InSAR, PS-InSAR, PS, DS