基于PS-InSAR的天津地区沉降监测及分析

城市地面沉降监测是保障城市安全建设和健康发展的重要手段之一，而传统的沉降监测方法无法大尺度反映地面形变信息。针对近几年天津地区出现大面积沉降现象，利用Sentinel-1A数据基于永久散射体干涉测量技术开展城区大范围沉降监测研究并分析了地面沉降原因。结果表明：近年来天津地区多处出现地面沉降，严重沉降区集中天津的武清区、北辰区以及郊区乡镇结合区域的王庆坨镇、胜芳镇、左各庄镇、静海镇以及大寺镇,其最大沉降漏斗位于王庆坨镇，沉降速率为-63.2 mm/a。经分析发现天津地面沉降与地下水过度开采、大型工业区的迁移和建设以及活动断裂带地质活动有关。     

基于Sentinel-1A数据的天津地区PS-InSAR地面沉降监测与分析

为有效预防地面沉降带来的灾害,利用2015年4月~2018年2月天津地区的24景Sentinel-1A数据,进行了永久散射体干涉测量处理,并使用高精度轨道数据和TanDEM-X DEM修正残差相位,提取了3 a的地面沉降结果,结合土地利用类型、水文、地质和交通等数据,分析了多处沉降地区的特征和形成原因,最后和小基线集方法的监测结果进行对比分析。结果表明:近3 a来天津城区沉降治理效果显著,平均沉降速率在8 mm/a以内,郊区沉降仍然严重,沉降速率在50~70 mm/a,沉降最为严重的区域为武清区王庆坨镇,3 a累计沉降量超过200 mm,并且有和其他沉降漏斗连成片的趋势。地面沉降发生的区域与地下水漏斗形成的区域基本一致,且两种方法得到的累积形变量差值95%在5 mm以内,说明本研究结果可以为天津市地质灾害防治提供数据支撑和决策依据。     

基于PSI技术的芜湖市地面沉降时空特征分析

城市的沉降监测有利于了解区域实时高程,可为地质灾害与防护部门提供数据依据,避免因高程损失而带来的地质灾害。基于2016年1月至2017年12月共22景Sentinel-1A干涉宽幅模式影像数据,利用永久散射体合成孔径雷达干涉测量技术以及合成孔径雷达差分干涉测量技术进行芜湖市地表形变监测,并分析研究区地面沉降的时空分布特征。空间上,阐述芜湖市地面沉降的整体格局,再以道路为专题,分析了道路的沉降分布格局。时间上,以时间为基线,逐月分析地面沉降部分在年内的具体变化。结果表明：空间上,芜湖市地面沉降主要集中在长江以东的范围,呈现出由西向东逐渐增加的趋势,长江以西呈现零星漏斗式沉降分布,其中,沉降累积量也与道路的密度与建设相关,道路汇集区与修建区域的沉降累积量较大;时间上,研究区整体沉降量各月变化较均匀,其中,沉降量变化范围在6月最大,10月与11月最小。     

基于PSI技术的芜湖市地面沉降时空特征分析

城市的沉降监测有利于了解区域实时高程,可为地质灾害与防护部门提供数据依据,避免因高程损失而带来的地质灾害。基于2016年1月至2017年12月共22景Sentinel-1A干涉宽幅模式影像数据,利用永久散射体合成孔径雷达干涉测量技术以及合成孔径雷达差分干涉测量技术进行芜湖市地表形变监测,并分析研究区地面沉降的时空分布特征。空间上,阐述芜湖市地面沉降的整体格局,再以道路为专题,分析了道路的沉降分布格局。时间上,以时间为基线,逐月分析地面沉降部分在年内的具体变化。结果表明:空间上,芜湖市地面沉降主要集中在长江以东的范围,呈现出由西向东逐渐增加的趋势,长江以西呈现零星漏斗式沉降分布,其中,沉降累积量也与道路的密度与建设相关,道路汇集区与修建区域的沉降累积量较大;时间上,研究区整体沉降量各月变化较均匀,其中,沉降量变化范围在6月最大,10月与11月最小。     

基于PSI技术的芜湖市地面沉降时空特征分析

城市的沉降监测有利于了解区域实时高程，可为地质灾害与防护部门提供数据依据，避免因高程损失而带来的地质灾害。基于2016年1月至2017年12月共22景Sentinel-1A干涉宽幅模式影像数据，利用永久散射体合成孔径雷达干涉测量技术以及合成孔径雷达差分干涉测量技术进行芜湖市地表形变监测，并分析研究区地面沉降的时空分布特征。空间上，阐述芜湖市地面沉降的整体格局，再以道路为专题，分析了道路的沉降分布格局。时间上，以时间为基线，逐月分析地面沉降部分在年内的具体变化。结果表明：空间上，芜湖市地面沉降主要集中在长江以东的范围，呈现出由西向东逐渐增加的趋势，长江以西呈现零星漏斗式沉降分布，其中，沉降累积量也与道路的密度与建设相关，道路汇集区与修建区域的沉降累积量较大；时间上，研究区整体沉降量各月变化较均匀，其中，沉降量变化范围在6月最大，10月与11月最小。     

基于SBAS-InSAR技术的围填海区域地面沉降监测

以围填海活动为代表的沿海快速城市化过程,是引起地面沉降的重要影响因素之一。研究聚焦沿海围填海活动热点区域广州市南沙区,使用2015年6月~2018年4月共34景Sentinel-1数据,应用SBAS-InSAR技术,揭示了南沙区在研究时段内地面沉降的时空变化格局及演变特征。结果表明：①南沙区整体呈现持续沉降的趋势,沉降速率分化严重,平均沉降速率达到3.2 mm/a,圈层分析法显示中心圈层平均沉降速率为2.6 mm/a,最外层平均沉降速率为26.8 mm/a;②该区地面沉降在空间上呈现出异质性,主要分布在东部和南部,其中南部万顷沙、龙穴岛地面沉降最为严重,最大年沉降速率达到72.2 mm/a,在2015年6月~9月还出现地面沉降回弹现象,可能是台风天气带来季节性强降水变化影响。③基于不同极化方式的Sentinel-1数据进行交叉验证,VV极化、VH极化监测结果平均值分别为2.09 mm和1.01 mm,均方根误差分别为1.12 mm和2.65 mm。结果表明：SBAS-InSAR技术在提取围填海区域的地面沉降信息方面是有效可靠的,能更好地为监测沿海地区的地面沉降情况提供科学依据。     

基于D-InSAR技术的唐山万达广场地区沉降监测及其安全性评价

唐山市万达广场南边为煤矿区,由于开采引起的地面沉降,直接影响到城市建筑物的安全,因此,采用D-InSAR形变监测手段获取煤矿区及周边地区的沉降时空分布特征显得尤为重要。收集了2004年～2008年唐山市万达广场及周边地区的3景ENVISAT ASAR数据,使用合成孔径雷达差分干涉测量(D-InSAR)技术来研究地面沉降对万达广场建设及周边地区的影响,获得了两期地面沉降结果,并将结果结合GIS技术对广场的建设进行安全性分析。实验结果表明:唐山煤矿地下开采引起的地面沉降从2004年开始没有再向万达广场的方向扩展,所以不会影响万达广场的建设,从而保证了广场的顺利建设和周边地区安全、有序的发展,也进一步验证了D-InSAR技术在煤矿区地面沉降监测中应用的可行性。     

北京平原区地面沉降PS-InSAR监测

地面沉降是北京平原区的主要地质灾害之一。针对地下水长期超量开采引发的大范围地面沉降,采用雷达遥感的技术方法对其进行监测分析:以2003~2010年间覆盖北京的31景ENVISAT ASAR数据为基础,采用永久散射体干涉测量技术对北京市平原区进行长时间序列的地面沉降监测,并对比地下水水位变化数据,通过GIS空间分析的方法讨论地面沉降的时空演化特征。结果表明:2003~2010年,北京市平原区地表形变速率范围为-52.1~8.2mm/yr,已经形成五大沉降漏斗(朝阳—通州沉降漏斗、天竺—金盏沉降漏斗、来广营沉降漏斗、高丽营沉降漏斗和昌平沉降漏斗),地面沉降发生区域与地下水漏斗形成区域基本一致。     

基于PSI技术监测上海市2009年～2010年区域地表沉降

采用振幅和相位联合分析的PS探测方法,以上海市作为实验研究区,进行PSI城市地表沉降监测并对成因进行了详细分析。实验结果表明:①由于大规模的城市建设、地下水开采、工业化生产和交通运输等活动,研究区内最大沉降速率达-47mm/年,平均沉降速率达-16.96mm/年,地表沉降比较明显。②2008年以前的沉降中心得到有效控制,现阶段有3个沉降中心较为明显,即罗泾镇宝山工业园区,平均沉降速率为-29.8mm/年;虹口足球场,平均沉降速率为-24.58mm/年;闵行经济技术开发区,平均沉降速率为-32.2mm/年。③地表沉降随着城市建设的发展向北、南、西南、东南逐步扩展。④水准数据验证了监测结果,精度可达±6mm,表明PSI技术在城市地表沉降监测中具有很大的优势。     

基于PS-InSAR技术的廊坊市地面沉降监测研究

随着城市化进程的加速发展,地面沉降危害不断加剧。以廊坊市城区为示范研究区,选取近5 a的ENVISat卫星ASAR数据,采用永久散射体干涉测量(PS-InSAR)技术,提取廊坊市城区2003~2007年时间序列地面沉降形变信息,并对廊坊市地面沉降空间分布特征进行初步分析。研究结果表明:廊坊市城区年平均沉降速率在-19.2~18.7mm/a之间变化,沉降中心主要分布在城区北部地区,对城市基础设施及施工建设产生严重影响。     

Land Subsidence Monitoring in Tianjin with PS-InSAR Technique based on Sentinel -1 Data

Land Subsidence is one of the most important geological hazards in many areas. In order to prevent disasters caused by land subsidence efficiently, 24 Sentinel-1A images covering area of Tianjin are choosed from 2015 to 2018. Based on Persistent Scatterers InSAR technique, the results of land subsidence for three years are extracted using the precise orbit data and TanDEM-X DEM and compared with the monitoring results of SBAS (Small Baseline Subset) method. Combined with land use types, hydrogeological and traffic data, the characteristics and formation reasons of several subsidence areas are analyzed. The experimental results show that: (1) In recent three years, the land subsidence in Tianjin urban area is relatively slow, with an average speed of less than 8 mm/a. However, suburban land subsidence is still serious with an average speed between 50 mm/a~70 mm/a. The most serious land subsidence area was Wangqingtuo Town in Wuqing district, the total land subsidence was over 200 mm. And there is a trend of connectivity in these subsidence areas. (2) Land subsidence and the falling of groundwater levels have a very high spatial correlation and the difference between the cumulative shape variables obtained by the two methods of SBAS and PSInSAR is less than 5 mm. The results of this study can provide data support for the government of Tianjin.     

时序InSAR技术地表沉降监测结果可靠性及沉降梯度分析

为系统评价时序InSAR技术监测结果的精度和可靠性,进一步挖掘监测结果中隐藏的空间地理信息,利用两种时序InSAR技术对天津市及周边区域地表沉降情况进行监测,并基于水准数据测量结果、不同时序InSAR技术监测结果以及夜间灯光数据二次分析结果,研究了系统评价监测结果可靠性的方法,对监测结果进行了精度和可靠性的评价。在此基础上,基于ArcGIS空间插值与梯度分析方法,对研究区两个重点沉降区域进行了沉降梯度分析。研究结果表明:1研究区时序InSAR技术监测结果精度较高、可靠性较好;2重点沉降区域分布于天津市市区周边辖区,而市区相对比较稳定;3沉降梯度较大区域多分布于"沉降漏斗"的边缘,沉降梯度大小与沉降速率之间没有直接联系。     

基于NPSI方法的西安市地裂缝灾害链地表形变监测与演化态势分析

受构造背景、地下水采掘、活断层等因素的综合作用,西安市地裂缝于近年间不断加剧,引发多处不均匀地表沉降,并演化为对地表及地下建筑物均有强烈破坏作用的城市地质灾害链。为探明西安市地裂缝灾害链区域近年间的地表沉降态势、辨析不均匀沉降与地裂缝发育的联系,引入在城市地表形变监测精度和可靠性方面具有显著优势的网络化永久散射体时序雷达干涉测量（NPSI）方法,以2017年3月至2018年3月间成像的15期Sentinel-1A卫星SAR影像为数据源针对西安地区开展了时序监测分析,结合水准测量数据验证发现NPSI监测结果的精度达到 ±4.75 mm。实验结果表明：西安市地裂缝正向西南郊发育,地下水采掘及地上地下工程的建设在地裂缝发育趋势下加剧了不均匀沉降灾害,在形成地裂缝灾害链的鱼化寨、电子城、曲江新区以及地铁3号线等危害严重区域需要实时监测地裂缝发育趋势,并合理规划地下水开采及工程建设活动。相关研究结果可为路政、城建等部门的业务工作及相关研究提供参考信息。     

Characterization and causes of land subsidence in Beijing,China

Long-term overexploitation of groundwater is the primary factor causing regional land subsidence in the Beijing plain area, China. Currently, large subsidence funnels exist, one each in southern and northern Beijing. We adopted the multi-temporal interferometric synthetic aperture radar (MT-InSAR) method, incorporating both persistent scatterer (PS) and small baseline (SB) approaches on 47 Envisat Advanced Synthetic Aperture Radar (ASAR) single look complex (SLC) images to map land subsidence in the Beijing plain area. The temporal and spatial variations of land subsidence and its seasonal variation were explained by the MT-InSAR results. Then, the InSAR results were combined with the dynamic monitoring of groundwater level, extensometer measurements, and hydrogeological data; the characterization and causes of land subsidence were analysed with Geographic Information System (GIS) spatial analysis methods. The results show the following. 1) Land subsidence developed rapidly in the Beijing plain area from 2003 to 2010, with obviously uneven settlement; settlement rates exceeded 100 mm year^?1 in some areas. Seasonal variation in settlement rates may be affected by changes in the precipitation rates and the exploitation of groundwater. 2) The contribution of different aquifer systems to land subsidence varies. The variation in the groundwater level in the second confined aquifer, at a depth of 100–180 m, has the greatest impact on land subsidence. 3) The settlement is centred in the lower part of the Wenyu–Chaobai and Yongding alluvial fan areas, where the compressible layer is more than 100 m thick. Meanwhile, land subsidence forms a structural feature with larger differences in the deformation gradient on both sides of faults.     

Recent subsidence in Tianjin,China: observations from multi-looking TerraSAR-X InSAR from 2009 to 2013

Tianjin, China, has been suggested to have serious ground subsidence due to excessive extraction of groundwater. It is essential to monitor this subsidence, which has potential hazards and risks. Time series InSAR (TS-InSAR), such as small baselines subset (SBAS), is a powerful tool that can monitor ground deformation with high accuracy and at high spatial resolution over a long time interval. However, the high computational complexity may exceed computer memory limit when high-spatial resolution SAR (such as TerraSAR-X, TSX) images are used. In this article, the multi-look approach is introduced to the SBAS tool from StaMPS/MTI (Stanford method for persistent scatter/multi-temporal InSAR) in order to balance the spatial resolution and subsidence information in detection. The looks used for multi-looking are first fixed in terms of the accuracy of deformation and the density of coherent points. Then, the recent subsidence in Tianjin is extracted using multi-looking SBAS based on 48 TSX images acquired from 2009 to 2013. The results are validated by levelling measurements with a root mean square error (RMSE) of 4.7 mm year^–1, which demonstrates that SBAS analysis can effectively monitor deformation based on multi-looking TSX acquisitions in the area under investigation. Besides, the results also show that Tianjin has been suffering from subsidence during this period, and there were two separate large subsidence basins located in this study area with more than 500 mm cumulative subsidence. Moreover, the subsidence rate increased after December 2010 in Tianjin.     

Monitoring of large-scale deformation in mining areas using sub-band InSAR and the probability integral fusion method

The large-scale and rapid land subsidence that occurs in mining areas often leads to problems, such as densely spaced interference fringes and the temporal decorrelation of interferometric synthetic aperture radar (InSAR) interferograms. To solve these problems, sub-band InSAR is applied to monitor the large-scale deformation that occurs in mining areas. First of all, four different bandwidth images with three sub-band bandwidth parameters are used to extract simulated mining-induced subsidence with seven different deformation magnitudes. The results of the simulation experiment suggest the following conclusions. In monitoring subsidence with different deformation magnitudes using images with different bandwidths, an optimal monitoring value exists; wider image bandwidths lead to smaller optimal monitoring values and higher monitoring accuracies. Therefore, an appropriate sub-band bandwidth should be selected that depends upon the image bandwidth and the subsidence level to achieve optimal monitoring. The optimal sub-band bandwidth for monitoring subsidence of different magnitudes in mining areas is determined through simulation experiments, and these conclusions can provide a technical basis for selecting the appropriate sub-band bandwidth for the monitoring of subsidence in mining areas. Although sub-band InSAR can reduce the number of interference fringes and the difficulty of unwrapping, the simultaneous introduction of large amounts of noise leads to reduced monitoring precision, and the application of the probability integral method in the prediction of mine subsidence is more mature. Therefore, the combined use of sub-band InSAR and the probability integral fusion method to monitor mining-induced deformation is proposed in this paper. The probability integral method is used to perform noise peeling on the interferometric phases of the sub-bands to improve the monitoring accuracy of sub-band interferometry. Then, according to the results of the simulation experiment, the fusion method with the appropriate sub-band bandwidth parameters is applied to monitor the surface deformation associated with working face 52,304 from 2 December 2012 to 13 December 2012. Finally, the monitoring results are compared with the results of monitoring using conventional differential interferometric synthetic aperture radar (D-InSAR) and global positioning system (GPS) field survey data. The results show that the reliability and accuracy of the fusion method are much better than those of conventional D-InSAR in monitoring the large-scale deformation that occurs at the edges of subsidence basins.