首页|京沪高速公路北京—天津段地面沉降时序InSAR监测与影响因素

京沪高速公路北京—天津段地面沉降时序InSAR监测与影响因素

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地面沉降作为平原区主要的地质灾害之一,对高速公路安全运行产生了潜在的影响.为了探究京沪高速公路北京—天津段的地面沉降情况,选取 2017 年 1 月至 2020 年 3 月 70 景Sentinel-1B卫星影像,利用SBAS-InSAR技术对该路段沿线地面沉降展开监测,并采用外部水准观测方法对InSAR监测结果进行精度评定;在此基础上,结合 3 类 9 个影响因子数据对沿线地面沉降进行空间模拟,通过对比普通最小二乘(OLS)模型、地理加权回归(GWR)模型和多尺度地理加权回归(MGWR)模型的模拟效果,最后选取相对最优模型对各种影响因子进行量化研究.结果表明:京沪高速公路北京—天津段表现出不均匀沉降特征,最大年均沉降速率超过-90 mm·年-1;研究区主要分布有 6 个明显的沉降中心,京沪高速公路北京—天津段经过其中 3 个;采用模拟效果相对最优的多尺度地理加权回归模型进行定量分析可知,第四系沉积厚度和地下水位变化对沉降的影响较大,而地形环境因子的影响较小.
Time Series InSAR Monitoring and Influencing Factors of Land Subsidence Along the Beijing-Tianjin Section of Beijing-Shanghai Expressway,China
Land subsidence,as one of the main geological hazards in the plain area,has a potential impact on the safe operation of the expressway.In order to explore the land subsidence of the Beijing-Tianjin section of Beijing-Shanghai expressway,70 Sentinel-1 B satellite images from January 2017 to March 2020 were selected,and SBAS-InSAR technology was used to monitor the land subsidence along the section.The accuracy of InSAR monitoring result was evaluated by external level observation.On this basis,nine factors were divided into three categories to conduct spatial simulation of the settlement amount.By comparing the simulation effects of OLS,GWR and MGWR models,the relative optimal model was selected to conduct quantitative research on various influencing factors.The results show that the Beijing-Tianjin section of Beijing-Shanghai expressway exhibits uneven settlement characteristics,with a maximum annual sedimentation rate exceeding-90 mm·a-1.There are mainly six obvious severe settlement centers distributed in the study area,with three of them passing through by Beijing-Shanghai expressway.The quantitative analysis of MGWR model,which has the best simulation effect,shows that the deposition thickness of Quaternary system and groundwater level changes have greater influence on the settlement,while the topographical environmental factors have less influence.

land subsidenceSBAS-InSAR technologytime series analysisGWR modelimpact factorBeijing-Shanghai expressway

王楚、丁瑞力、陈蜜、张丹丹、葛鹏飞、成曦、范凯伦

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首都师范大学 资源环境与旅游学院,北京 100048

首都师范大学城市环境过程与数字模拟国家重点实验室培育基地,北京 100048

首都师范大学水资源安全北京实验室,北京 100048

自然资源部矿业城市自然资源调查监测与保护重点实验室,山西 晋中 030600

山西省煤炭地质物探测绘院有限公司 资源环境与灾害监测山西省重点实验室,山西 晋中 030600

自然资源部国土卫星遥感应用中心,北京 100048

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地面沉降 SBAS-InSAR技术 时序分析 地理加权回归模型 影响因素 京沪高速公路

国家重点研发计划国家自然科学基金国家自然科学基金

2017YFB050380341201419U2344225

2024

地球科学与环境学报
长安大学

地球科学与环境学报

CSTPCD北大核心
影响因子:1.422
ISSN:1672-6561
年,卷(期):2024.46(2)
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