Suppr超能文献

基于SBAS-PS-DS-InSAR的通辽市区地表形变时间序列监测研究

Research on Time Series Monitoring of Surface Deformation in Tongliao Urban Area Based on SBAS-PS-DS-InSAR.

作者信息

Chen Yuejuan, Ding Cong, Huang Pingping, Yin Bo, Tan Weixian, Qi Yaolong, Xu Wei, Du Siai

机构信息

College of Information Engineering, Inner Mongolia University of Technology, Hohhot 010080, China.

Inner Mongolia Key Laboratory of Radar Technology and Application, Hohhot 010051, China.

出版信息

Sensors (Basel). 2024 Feb 10;24(4):1169. doi: 10.3390/s24041169.

Abstract

As urban economies flourish and populations become increasingly concentrated, urban surface deformation has emerged as a critical factor in city planning that cannot be overlooked. Surface deformation in urban areas can lead to deformations in structural supports of infrastructure such as road bases and bridges, thereby posing a serious threat to public safety and creating significant safety hazards. Consequently, research focusing on the monitoring of urban surface deformation holds paramount importance. Interferometric synthetic aperture radar (InSAR), as an important means of earth observation, has all-day, wide-range, high-precision, etc., characteristics and is widely used in the field of surface deformation monitoring. However, traditional solitary InSAR techniques are limited in their application scenarios and computational characteristics. Additionally, the manual selection of ground control points (GCPs) is fraught with errors and uncertainties. Permanent scatterers (PS) can maintain high interferometric coherence in man-made building areas, and distributed scatterers (DS) usually show moderate coherence in areas with short vegetation; the combination of DS and PS solves the problem of manually selecting GCPs during track re-flattening and regrading, which affects the monitoring results. In this paper, 45 Sentinel-1B data from 16 February 2019 to 14 December 2021 are used as the data source in the urban area of Horqin District, Tongliao City, Inner Mongolia Autonomous Region, for example. A four-threshold (coherence coefficient threshold, FaSHPS adaptive threshold, amplitude divergence index threshold, and deformation velocity interval) GCPs point screening method for PS-DS, as well as a Small Baseline Subset-Permanent Scatterers-Distributed Scatterers-Interferometric Synthetic Aperture Radar (SBAS-PS-DS-InSAR) method for selecting PS and DS points as ground control points for orbit refinement and re-flattening, are proposed. The surface deformation results obtained using the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) and the SBAS-PS-DS-InSAR proposed in this paper were comparatively analysed and verified. The maximum cumulative line-of-sight settlements were -90.78 mm and -83.68 mm, and the maximum cumulative uplifts are 74.94 mm and 97.56 mm, respectively; the maximum annual average line-of-sight settlements are -35.38 mm/y and -30.38 mm/y, and the maximum annual average uplifts are 25.27 mm/y and 27.92 mm/y. The results were evaluated and analysed in terms of correlation, mean absolute error (MAE), and root mean square error (RMSE). The deformation results of the two InSAR methods were evaluated and analysed in terms of correlation, MAE, and RMSE. The errors show that the Pearson correlation coefficients between the vertical settlement results obtained using the SBAS-PS-DS-InSAR method and the GPS monitoring results were closer to 1. The maximum MAE and RMSE were 13.7625 mm and 14.8004 mm, respectively, which are within the acceptable range; this confirms that the monitoring results of the SBAS-PS-DS-InSAR method were better than those of the original SBAS-InSAR method. SBAS-InSAR method, which is valid and reliable. The results show that the surface deformation results obtained using the SBAS-InSAR, SBAS-PS-DS-InSAR, and GPS methods have basically the same settlement locations, extents, distributions, and temporal and spatial settlement patterns. The deformation results obtained using these two InSAR methods correlate well with the GPS monitoring results, and the MAE and RMSE are within acceptable limits. By comparing the deformation information obtained using multiple methods, the surface deformation in urban areas can be better monitored and analysed, and it can also provide scientific references for urban municipal planning and disaster warning.

摘要

随着城市经济的繁荣和人口日益集中,城市地表变形已成为城市规划中不容忽视的关键因素。城市地区的地表变形会导致道路基层和桥梁等基础设施结构支撑的变形,从而对公共安全构成严重威胁并造成重大安全隐患。因此,专注于城市地表变形监测的研究至关重要。干涉合成孔径雷达(InSAR)作为一种重要的对地观测手段,具有全天时、大范围、高精度等特点,在地表变形监测领域得到广泛应用。然而,传统的单台InSAR技术在应用场景和计算特性方面存在局限性。此外,地面控制点(GCP)的人工选择充满误差和不确定性。永久散射体(PS)在人造建筑区域能保持较高的干涉相干性,分布式散射体(DS)在植被较短的区域通常表现出中等相干性;DS和PS的结合解决了轨道重新整平和平整过程中人工选择GCP的问题,这会影响监测结果。本文以内蒙古自治区通辽市科尔沁区市区为例,将2019年2月16日至2021年12月14日的45景哨兵 - 1B数据作为数据源。提出了一种针对PS - DS的四阈值(相干系数阈值、FaSHPS自适应阈值、幅度发散指数阈值和变形速度区间)GCP点筛选方法,以及一种将PS和DS点作为轨道精化和平整的地面控制点的小基线子集 - 永久散射体 - 分布式散射体 - 干涉合成孔径雷达(SBAS - PS - DS - InSAR)方法。对使用小基线子集干涉合成孔径雷达(SBAS - InSAR)和本文提出的SBAS - PS - DS - InSAR得到的地表变形结果进行了对比分析和验证。最大累积视线沉降分别为 - 90.78毫米和 - 83.68毫米,最大累积隆起分别为74.94毫米和97.56毫米;最大年平均视线沉降分别为 - 35.38毫米/年和 - 30.38毫米/年,最大年平均隆起分别为25.27毫米/年和27.92毫米/年。从相关性、平均绝对误差(MAE)和均方根误差(RMSE)方面对结果进行了评估和分析。对两种InSAR方法的变形结果从相关性、MAE和RMSE方面进行了评估和分析。误差表明,使用SBAS - PS - DS - InSAR方法获得的垂直沉降结果与GPS监测结果之间的皮尔逊相关系数更接近1。最大MAE和RMSE分别为13.7625毫米和14.8004毫米,均在可接受范围内;这证实了SBAS - PS - DS - InSAR方法的监测结果优于原始的SBAS - InSAR方法。SBAS - InSAR方法有效且可靠。结果表明,使用SBAS - InSAR、SBAS - PS - DS - InSAR和GPS方法获得的地表变形结果在沉降位置、范围、分布以及时空沉降模式上基本相同。使用这两种InSAR方法获得的变形结果与GPS监测结果相关性良好,MAE和RMSE在可接受范围内。通过比较多种方法获得的变形信息,可以更好地监测和分析城市地区的地表变形,也可为城市市政规划和灾害预警提供科学参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78dc/10893464/68cd403959b7/sensors-24-01169-g001a.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验