测绘通报 ›› 2024, Vol. 0 ›› Issue (12): 24-32.doi: 10.13474/j.cnki.11-2246.2024.1205

• 学术研究 • 上一篇    下一篇

基于升降轨SAR数据的六库街道地表形变监测及地理探测机制

俞文轩1, 李益敏2, 计培琨2, 马恩华2, 吕圣彬2   

  1. 1. 云南大学国际河流与生态安全研究院, 云南 昆明 650500;
    2. 云南大学地球科学学院, 云南 昆明 650500
  • 收稿日期:2024-02-26 发布日期:2024-12-27
  • 作者简介:俞文轩(1999-),男,硕士生,研究方向为InSAR地表形变监测、机器学习。E-mail:yuwenxuan202305@163.com
  • 基金资助:
    云南省科技厅—云南大学联合基金重点项目(2019FY003017);云南省中老孟缅自然资源遥感监测国际联合实验室;遥感技术服务“一带一路”倡议融入研究生教育教学研究(JG-Y202425)

Surface deformation and monitoring geodetic detection mechanism in Liuku street based on ascending and descending SAR data

YU Wenxuan1, LI Yimin2, JI Peikun2, MA Enhua2, Lü Shengbin2   

  1. 1. Institute of International Rivers and Eco-security, Yunnan University, Kunming 650500, China;
    2. College of Earth Science, Yunnan University, Kunming 650500, China
  • Received:2024-02-26 Published:2024-12-27

摘要: 地表形变作为一种普遍存在的地质灾害,易在地形复杂的山区引发滑坡、泥石流等灾害,长期威胁着人民的人身财产安全。然而,由于缺乏全面的地表形变监测和对形变驱动因子的定量分析,难以针对性地对地表形变进行有效防范。为了准确识别山区地表形变的主导因素,本文基于升降轨SAR数据集的星载合成孔径雷达干涉测量技术(InSAR),获取了云南省六库街道2016年1月—2022年2月的地表形变时空分布;在验证监测结果的可靠性后,利用地理探测器量化驱动因子的贡献并揭示其相互作用的机制。结果表明:①六库街道地表形变以沉降为主,主要集中在主城区,形变速率为-44~30 mm/a;②降水量、高程、土壤类型与研究区地表形变表现出较强的空间相关性,驱动因子之间的交互作用增强了地表形变的空间相关性;③主城区形变以垂直向沉降为主,李家田、大密扣村存在水平形变。

关键词: SBAS, PS, 时序InSAR, 地理探测器, 形变监测

Abstract: Surface deformation, a common geological hazard, frequently triggers landslides and debris flow disasters in complex mountainous terrain, posing a long-term threat to personal and property safety. However, the effective prevention of surface deformation remains challenging due to the lack of comprehensive monitoring and quantitative analysis of its driving factors. To accurately identify the dominant factors of surface deformation in mountainous areas, this study uses InSAR technology with ascending and descending orbit SAR datasets to determine the spatiotemporal distribution of surface deformation in Liuku county, Yunnan province, from January 2016 to February 2022. After verifying the reliability of the monitoring results, a geographic detector quantifies the contributions of driving factors and reveals their interactive mechanisms. The research results show that:①Surface deformation in Liuku county is primarily subsidence, mainly concentrated in the main urban area, with deformation rates ranging from -44 to 30 mm/a. ②Rainfall, elevation, and soil type have a strong spatial correlation with surface deformation in the study area, and interactions among driving factors enhance this spatial correlation. ③Deformation in the main urban area is primarily characterized by vertical subsidence, while horizontal deformation occurs in Lijiatian and Damikou village.

Key words: SBAS, PS, time series InSAR, geographical detector, deformation monitoring

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