Interferometric SAR Time Series Analysis for Ground Subsidence of the Abandoned Mining Area in North Peixian Using Sentinel-1A TOPS Data

The North Peixian mining area of China has rich coal resources, with total proven reserves of 2.37 billion tons. However, the underground coal mining activities have resulted in ground collapse, which has caused serious harm to the environment and threatened the lives and properties of local residents. In this study, 12 Sentinel-1A terrain observation by progressive scans (TOPS) mode acquisitions between 30 July 2015 and 13 May 2016 over the abandoned mining area in North Peixian were analyzed using the interferometric synthetic aperture radar (InSAR) time series method to detect the ground subsidence, with the maximum ground subsidence reaching 83 mm/a and an average value of about 12.7 mm/a. The subsidence results derived from the Sentinel-1A TOPS mode dataset were proven to be effective in investigating and monitoring the ground subsidence in the North Peixian mining area. Compared to the rapid deformation during the ongoing period of mining excavation, the ground subsides slowly in abandoned mining areas and shows a linear relationship with time over a relatively long period of time. Spatial correlation between the subsidence distribution and land cover was found, in that the magnitude of the subsidence in urban areas was smaller than that in rural areas, which is associated with the controlled coal mining activities under buildings, railways, and water bodies. The results demonstrate that Sentinel-1A TOPS SAR images can be used to effectively and accurately detect and monitor ground subsidence in a mining area, which is critically important when investigating land subsidence in a large-scale mining area.     

Subsidence in the Kathmandu Basin,before and after the 2015 Mw 7.8 Gorkha Earthquake,Nepal Revealed from Small Baseline Subset-DInSAR Analysis

Land subsidence in densely urbanized areas is a global problem that is primarily caused by excessive groundwater withdrawal. The Kathmandu Basin is one such area where subsidence due to groundwater depletion has been a major problem in recent years. Moreover, on 25 April 2015, this basin experienced large crustal movements caused by the Gorkha earthquake (Mw 7.8). Consequently, the effects of earthquake-induced deformation could affect the temporal and spatial nature of anthropogenic subsidence in the basin. However, this effect has not yet been fully studied. In this paper, we applied the SBAS-DInSAR technique to estimate the spatiotemporal displacement of land subsidence in the Kathmandu Basin before and after the Gorkha earthquake, using 16 ALOS-1 Phased Array L-band Synthetic Aperture Radar (PALSAR) images during the pre-seismic period and 26 Sentinel-1 A/B SAR images during the pre- and post-seismic periods. The results showed that the mean subsidence rate in the central part of the basin was about ?8.2 cm/year before the earthquake. The spatial extents of the subsiding areas were well-correlated with the spatial distributions of the compressible clay layers in the basin. We infer from time-series InSAR analysis that subsidence in the Kathmandu basin could be associated with fluvio-lacustrine (clay) deposits and local hydrogeological conditions. However, after the mainshock, the subsidence rate significantly increased to ?15 and ?12 cm/year during early post-seismic (108 days) and post-seismic (2015–2016) period, respectively. Based on a spatial analysis of the subsidence rate map, the entire basin uplifted during the co-seismic period has started to subside and become stable during the early-post-seismic period. This is because of the elastic rebound of co-seismic deformation. However, interestingly, the localized areas show increased subsidence rates during both the early-post- and post-seismic periods. Therefore, we believe that the large co-seismic deformation experienced in this basin might induce the local subsidence to increase in rate, caused by oscillations of the water table level in the clay layer.     

InSAR视角下准噶尔盆地农业灌溉区地表形变特征和演化规律

抽取地下水进行农业灌溉是导致地下水位快速下降的重要因素,而长期过度开采地下水往往会引发地面沉降灾害,这种现象在干旱和半干旱地区非常普遍。为了研究农业灌溉超采引发的地表形变特征和演化规律,本文以准噶尔盆地南缘、天山北麓地带为研究区域,利用SBAS-InSAR技术对2003年—2009年覆盖呼图壁县的ENVISAT/ASAR升、降轨数据进行处理,获取了该地区的地表形变场,并结合研究区的农业灌溉方式、水资源补给和季节变化等资料对地面沉降的时空变化特征进行分析,为水资源和农业可持续发展提供参考意义。实验表明,研究区内主要有两个沉降幅度较大的漏斗,且都位于农田区域。2007年以前,研究区地表没有显著形变,之后发生了较大量级的沉降。采用传统灌溉方式和时针式灌溉系统的农业区平均沉降速率最高分别可达50 mm/a和30 mm/a,前者在时间上呈线性变化,而后者具有显著的周期性变化特征。在冬季时,采用时针式灌溉系统的地区地面抬升量可达40 mm,远大于传统灌溉方式的农田区域,而夏季地面沉降速率可达200 mm/a。对研究区农业灌溉活动进行分析后发现,农业灌溉造成的地下水超采是该地区地面沉降的主要影响因素,其形变机制与季节变化具有较高的相关性,在灌溉活动休止期内地表形变取决于地下水的补给量。研究区内的形变特征和影响因素分析将为地下水资源的充分利用和农业的可持续发展提供有效的信息。     

智能全站仪水平位移监测技术在110 kV机场变电站形变监测中的应用

建设施工对周围建筑物有着较大的影响,可以诱导邻近建筑物地基产生较大的形变,进而引起邻近建筑物受力结构改变,导致建筑物破裂、倒塌。因此,在大型建设项目施工过程中实施动态形变监测有助于施工项目的顺利进行。基于此,本文以智能全站仪为基础手段,针对110 kV机场变电站接入线路施工进行了实时动态监测,为该工程的顺利施工奠定了基础。本文从深层土体位移、桥墩水平位移及沉降和路基地面沉降3个方面进行了形变监测,监测结果显示,监测精度能够满足基本需求,获得实时动态数据稳定、可靠,能够反映施工过程中的动态形变状况,并认为该建设工程项目对邻近建筑物影响不大,可以安全施工。     

利用时序InSAR技术分析北京及河北廊坊地面沉降

利用带大气估计模型的时序InSAR方法对24幅覆盖北京及河北廊坊的Envisat-ASAR影像数据进行了时序分析,获取了该地区2007年4月—2010年9月的地面沉降速率及均方差。发现了以北京朝阳区和通州区交界处为中心和以河北廊坊城区为中心的两个沉降区域,中心区平均沉降速率分别为35mm/a与22mm/a。研究区域形变速率均方差1.5mm/a。研究结果表明:利用时序InSAR技术进行城市地表沉降监测具有较好的精度及稳定性;产生该沉降的可能原因为地下水的开采、城市基础建设的发展及工业用地量、人为活动的增加。     

Spatiotemporal evolution of land subsidence around a subway using InSAR time-series and the entropy method

The underground railway network of Beijing City, China, which is an important urban infrastructure, has burgeoned with the expansion of the city. However, the influence of subway construction and operation on local subsidence has received minimal attention. By analyzing the Radarsat-2 synthetic aperture radar satellite data, and using persistent scatterer interferometry, we revealed the land subsidence characteristics along the Beijing Subway Line 6. In the context of land subsidence, the expectation (Ex) reflects the overall level of local land subsidence while the entropy (En) reflects the degree of nonuniformity of local land subsidence in time and space. By comparing the changes in Ex and En, we estimated the spatial range of the influence of the subway on local land subsidence. The influenced area was mainly located between 60 m north of the subway line and 80 m south of the subway line. Land subsidence was most strongly altered during subway construction. During operation of the subway, the deformation rates along the subway increased slightly in the first two years and were then stabilized.     

水准测量技术在宁波市轨道交通3号线工程中的应用分析

交通轨道施工环境复杂,周围高层建筑物林立,威胁着建设工程安全施工。因此,加强大型建设项目施工过程中的形变监测有助于施工项目安全开展。本文以水准测量技术为监测手段,对宁波市轨道交通3号线工程进行了形变监测,文章从3个方面进行形变分析。监测结果表明,深层土体位移最大为131.37 mm,支护桩顶部水平位移最大为2 mm,支护桩顶部沉降位移最大为2.1 mm,地表沉降最大为201.4 mm,项目施工开始至结束,未出现报警值情况,说明建设工程整体设计合理,认为该建设工程项目对临近建筑物影响不大,可以安全施工。     

南京地铁沿线地面沉降监测与危险性评价

采用MCTSB-InSAR技术监测南京市主城区地面沉降状况,揭示研究区内地面沉降空间分布特征;通过对地铁线路进行条带空间缓冲区分析和沿线路剖面线分析,进一步研究地铁沿线的地面及周边建筑物不均匀沉降信息;针对主要影响路段进行地质灾害危险性评价,评价结果及特征点时间序列沉降结果与同时期实际情况基本吻合。研究表明,长期进行城市主城区及地铁线路地面沉降监测具有重要意义,同时地质灾害危险性评价工作能为灾害防治及评估提供可靠的支持,具有较大的应用潜力。     

Land subsidence characteristics of Jakarta between 1997 and 2005, as estimated using GPS surveys

Jakarta is the capital city of Indonesia with a population of about 12 million people, inhabiting an area of about 625 km². It is well known that several areas in Jakarta are subsiding rapidly. There are four different types of land subsidence that can be expected to occur in the Jakarta basin, namely: subsidence due to groundwater extraction, subsidence induced by the load of constructions (i.e., settlement of high compressibility soil), subsidence caused by natural consolidation of alluvial soil and tectonic subsidence. In addition to the leveling method, Global Positioning System (GPS) survey methods have been used to study land subsidence in Jakarta. In this paper, we characterize subsidence in the Jakarta basin using eight episodic/campaign GPS surveys between 1997 and 2005. The estimated subsidence rates are 1–10 cm/year. The observed subsidence rates in several locations show a positive correlation with known abstraction volumes of groundwater extraction. These basin-wide series of GPS measurements show how this type of measurement can play an important role in multiple public policy decision making in this rapidly growing area.     

时序InSAR技术在地球环境监测及其资源管理中的应用:以交城-清徐地区为例

利用ALOS-1（2007-2010）、Sentinel-1A（2017-2018）存档数据对山西交城-清徐地区的地面沉降进行监测。结合小基线和永久散射体技术优点,在增加时间采样密度的基础上利用二维线性回归分析得到研究区域的形变速率和时间序列。经同期GPS观测结果校核表明:交城-清徐地区持续发生地面沉降,但山区和平原区域形变的空间分布、量级不同,引起形变原因也不同。平原地带沉降空间分布受构造断裂控制,断裂带两侧呈现明显的差异性形变,且最大沉降速率为－200 mm/a,沉降的主要原因是地下水超采,但经治理后地面沉降灾害有所缓解,表现为沉降速率小于－30 mm/a。山区主要由于矿产资源的长期开采,沉降中心不断向南移动,最大形变速率为－462 mm/a。     

利用时序InSAR监测兰州市中心城区地面沉降

针对兰州市中心城区的地面沉降问题,该文采用PS-SBAS和PS-InSAR技术,利用2016-01-20—2019-02-21时间段内的39景Sentinel-1A/B降轨数据,使用缓冲区分析技术对兰州市中心城区轨道交通线和铁路线周边100m区域做了沉降影响分析,监测结果表明:基于Sentinel-1A/B数据和时序InSAR技术,可以准确监测城市地表的沉降和轨道交通线的沉降时空规律;沉降区域主要集中在研究区东南部的方家泉村、和平镇和猪咀岭村;软土地基下地铁的施工会导致沉降现象的发生,兰州轨道交通线和铁路线的沉降主要发生在城区东南方向;在监测时段内,使用两种时序InSAR技术监测的同名点在沉降趋势和累计沉降量上保持了良好的一致性和吻合性,但PS-InSAR的时序变化曲线较PS-SBAS更为平缓。     

宁波地面沉降的短基线集监测与分析

针对传统地面沉降监测手段精度高,但监测周期长、空间分辨率低、人力物力耗费大等问题,该文基于短基线集时序分析技术提取了宁波地区的地表形变信息。首先根据短基线集技术监测结果分析了宁波地区地面沉降分布特征,然后对宁波东部新城的沉降进行了精细化分析,并给出了其沉降原因。结果表明:宁波地区地面沉降整体呈现弱发育特征,部分地区存在轻微地面隆起现象,东部新城地面沉降呈现中度发育特征,并存在不均匀沉降现象,快速的城市化建设是东部新城地面沉降的主要原因。     

Assessment of Land Surface Subsidence Due to Underground Metal Mining Using Integrated Spaceborne Repeat-Pass Differential Interferometric Synthetic Aperture Radar (DInSAR) Technique and Ground Based Observations

Differential interferometric synthetic aperture radar (DInSAR) is a novel remote sensing technique to measure earth surface deformation. It is capable of obtaining dense information related to the deformation of a large area efficiently, economically and effectively. Therefore, DInSAR is a promising technology for monitoring the earth surface deformation related to some natural hazardous events, such as earthquake, volcano eruption, land subsidence, landslide. In present study, Conventional DInSAR technique have been applied to a mineral rich zone, coming under the Khetri copper belt, a part of Northern Aravali range of hillocks in India, predominant with mining activities since late 1960’s to address the possibility of deformation phenomena due to hard rock underground metal mining. Four interferometric SAR data sets of Radarsat-2 was used for the study area to address the subsidence/uplift phenomena. Further, results obtained from conventional DInSAR technique using Radarsat-2 data sets compared with results obtained from ground based observation technique for its validity. In both the techniques, deformation results obtained in terms of average subsidence rate in mm (quarterly basis) of points under study within mining zone of Mine-A has well agreed to each other. Further, it has been observed that average subsidence rate in mm (quarterly basis) obtained from space based observation and ground based observation are 5.6 and 6.67, respectively over the points under study in mining zone of Mine-A.     

Monitoring surface changes in discontinuous permafrost terrain using small baseline SAR interferometry,object-based classification,and geological features: a case study from Mayo,Yukon Territory,Canada

Permafrost-induced deformation of ground features is threating infrastructure in northern communities. An understanding of permafrost distribution is therefore critical for sustainable adaptation planning and infrastructure maintenance. Considering the large area underlain by permafrost in the Yukon Territory, there is a need for baseline information to characterize the permafrost in this region. In this study, the Differential Interferometric Synthetic Aperture Radar (DInSAR) technique was used to identify areas of ground movement likely caused by changes in permafrost. The DInSAR technique was applied to a series of repeat-pass C-band RADARSAT-2 observations collected in 2015 over the Village of Mayo, in central Yukon Territory, Canada. The conventional DInSAR technique demonstrated that ground deformation could be detected in this area, but the resulting deformation maps contained errors due to a loss of coherence from changes in vegetation and atmospheric phase delay. To address these limitations, the Small BAseline Subset (SBAS) InSAR technique was applied to reduce phase error, thus improving the deformation maps. To understand the relationship between the deformation maps and land cover types, an object-based Random Forest classification was developed to classify the study area into different land cover types. Integration of the InSAR results and the classification map revealed that the built-up class (e.g., airport) was affected by subsidence on the order of ?2 to ?4 cm. The spatial extent of the surface displacement map obtained using the SBAS InSAR technique was then correlated with the surficial geology map. This revealed that much of the main infrastructure in the Village of Mayo is underlain by interbedded glaciofluvial and glaciolacustrine sediments, the latter of which caused the most damage to human made structures. This study provides a method for permafrost monitoring that builds upon the synergistic use of the SBAS InSAR technique, object-based image analysis, and surficial geology data.     

From ERS-1/2 to Sentinel-1: two decades of subsidence monitored through A-DInSAR techniques in the Ravenna area (Italy)

Land subsidence due to underground resources exploitation is a well-known problem that affects many cities in the world, especially the ones located along the coastal areas where the combined effect of subsidence and sea level rise increases the flooding risk. In this study, 25 years of land subsidence affecting the Municipality of Ravenna (Italy) are monitored using Advanced Differential Interferometric Synthetic Aperture Radar (A-DInSAR) techniques. In particular, the exploitation of the new Sentinel-1A SAR data allowed us to extend the monitoring period till 2016, giving a better understanding of the temporal evolution of the phenomenon in the area. Two statistical approaches are applied to fully exploit the informative potential of the A-DInSAR results in a fast and systematic way. Thanks to the applied analyses, we described the behavior of the subsidence during the monitored period along with the relationship between the occurrence of the displacement and its main driving factors.     

郑徐高铁开封段地面沉降分层监测方法

高铁沿线施工期间引起地面沉降的因素错综复杂、相互影响,本文提出通过对沉降区域地下水位、孔隙水压力等进行分层观测,根据分层观测得到地下水位变化、孔隙水压力变化等数据,并采用回归分析法构建了沉降区域地面沉降与诸影响因子的关联模型,通过对郑徐客运专线开封段进行的地面沉降监测量与同时采用二等精密水准测量得到的监测点沉降量进行对比分析,结果表明本方法的有效性和可靠性。     

郑州市地裂缝遥感识别与监测

根据坡度分析在灾害防治与水土保持工作上的应用,提出了以IPTA技术获取的地面沉降速率图为数据源,利用地面沉降坡度分析开展地裂缝遥感识别;以郑州市为研究区,根据地面沉降坡度分析识别出的目标区,在郑州市区首次发现因差异性地面沉降造成的地裂缝,实地调查发现该地裂缝东西长约2 000 m,已经造成附近10余处建筑物受损,监测结果表明该地裂缝存在明显的三维形变;实地调查和监测结果证明,地面沉降坡度分析不仅可以用于地裂缝的识别,也能用于地面沉降危险性分区,对地质灾害防治减灾有一定的指导意义。     

武汉市地面沉降时空分异特征及地理探测机制

城市地区地面沉降造成地面高程损失,威胁各类设施的安全运行,影响地表径流和水文循环,监测地面沉降现状并揭示其形成机制,对于城市可持续发展具有重要意义。以2007—2011年的ALOS-PALSAR影像和2015—2019年的Radarsat-2影像为数据源,基于小基线集技术（small baseline subset interferometric synthetic aperture radar, SBAS-InSAR）获取武汉市两个监测阶段的地面沉降速率、沉降时间序列,并利用地理探测器揭示规划单元尺度地面沉降的主导驱动因子及驱动因子之间的交互作用机制。结果表明:(1)2007—2011?年和2015—2019年地面沉降平均速率分别为-3.53 mm/a和-1.48 mm/a。地面沉降较为显著的区域:2007—2011年,是汉口、沙湖沿岸及以北、南湖以西和白沙洲地区;2015—2019年,是汉口、沙湖北和白沙洲地区。(2)?局部性、阶段性、与自然条件及人类活动相关是两个时期武汉市地面沉降演变的3个特点。(3)水文地质条件作为必要条件,通过与地面荷载、地下空间开发、工程施工因素交互作用形成武汉市地面沉降时空格局,2007?—2011年的工程施工因素、2015—2019年的地面荷载因素与水文地质条件交互作用明显较强。     

利用压密方程计算分析西安市地面沉降特征

利用西安市地下水位监测资料,基于水文地质三维结构模型,在不考虑粘土层滞后压缩变形的理想情况下,采用压密方程计算获得西安市抽取地下水可引起的理论地面沉降量及沉降分布特征,结果表明:计算所得沉降显著区位于西安市西南部的高新区及东南部的曲江新区,沉降量呈由北向南递增的特征,与InSAR监测结果整体趋势具有较好的一致性;地面沉降分布特征受到活动地裂缝影响,沉降曲线呈近NE向偏转展布。研究结果可为沉降灾害预防研究提供宏观的参考信息。     

Land subsidence under different land use in the eastern Beijing plain,China 2005-2013 revealed by InSAR timeseries analysis

Land subsidence has been occurring in Beijing since the 1970s. Five major land subsidence areas have been formed: Dongbalizhuang–Dajiaoting, Laiguangying, Changping Shahe–Ba Xianzhuang, Daxing Yufa–Lixian, and Shunyi–Ping Gezhuang. In this paper, we studied on land subsidence in Dongbalizhuang–Dajiaoting and Laiguangying using small baseline subset interferometry and interferometric point target methods of 47 ENVISAT ASAR and 29 RADARSAT-2 data. The results showed that the degree of land subsidence in these areas varied significantly. The mean land subsidence rate ranged from 143.43 to 8.2 mm/a and from 132.11 to 7.3 mm/a during 2005–2010 and 2011–2013, respectively. We correlated the observed settlement with the land use (agricultural, residential, and industrial). Displacement in the agricultural areas was greater than that in the other areas from 2005 to 2013. Moreover, we compared the observed deformation and the groundwater level in phreatic and confined aquifers. There was a strong correlation between ground subsidence and the groundwater level and the ground settlement increased with a decrease in the groundwater level and the maximum correlation coefficient can reach 0.525. Furthermore, subsidence appeared to be associated with compressible deposits, suggesting that for 90–210-m thick compressible deposits, ground settlement is more likely to occur as the thickness of the compressible layer increases.