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Earthquakes cause a huge number of landslides and alter the regional landslide risk distribution. As a result, after a significant earthquake, the landslide susceptibility maps (LSMs) must be updated. The study goal was to create seismic landslide susceptibility maps containing landslide causative variables which are adaptable to great changes in susceptibility after the Jiuzhaigou earthquake (MS 7.0) and to perform a rapid update of the LSM after the earthquake by means of the distributed scatterer interferometric synthetic aperture radar (DS-InSAR) technique. We selected the territory of Jiuzhaigou County (southwestern China) as the study region. Jiuzhaigou is a world-renowned natural heritage and tourist area of great human and ecological value. For landslide susceptibility mapping, we examined the applicability of three models (logistic regression, support vector machine, and random forest) for landslide susceptibility mapping and offered a strategy for updating seismic landslide susceptibility maps using DS-InSAR. First, using logistic regression, support vector machine, and random forest techniques, susceptibility models of seismic landslides were built for Jiuzhaigou based on twelve contributing variables. Second, we obtained the best model parameters by means of a Bayesian network and network search, while using five-fold cross-validation to validate the optimized model. According to the receiver operating characteristic curve (ROC), the SVM model and RF model had excellent prediction capability and strong robustness over large areas compared with the LR models. Third, the surface deformation in Jiuzhaigou was calculated using DS-InSAR technology, and the deformation data were adopted to update the landslide susceptibility model using the correction matrix. The correction of deformation data resulted in a susceptibility class transition in 4.87 percent of the research region. According to practical examples, this method of correcting LSMs for the continuous monitoring of surface deformation (DS-InSAR) was effective. Finally, we analyze the reasons for the change in the revised LSM and point out the help of ecological restoration in reducing landslide susceptibility. The results show that the integration of InSAR continuous monitoring not only improved the performance of the LSM model but also adapted it to track the evolution of future landslide susceptibility, including seismic and human activities. [ABSTRACT FROM AUTHOR]

Multi-temporal interferometric Persistent Scatterers Interferometry (PSI) techniques derive from the elaboration of satellite Synthetic Aperture Radar (SAR) images and represent a useful tool to detect ground millimetric movements over wide areas; thanks to non-invasiveness and high accuracy. However, PSI data are relative measurements estimated along the sensor Line Of Sight and referred to a chosen stable motionless reference point, so they lack absolute reference both in time and space. In this work, we propose a methodological procedure that exploits Global Navigation Satellite System (GNSS) data acquired from permanent stations to calibrate and fix relative InSAR results into conventional geodetic reference systems. Mean yearly velocities of PSI radar targets are corrected with GNSS values throughout operative procedures used in geodesy for crustal and local deformation data. The methodology is tested in Ravenna and Ferrara cities on the north-western Adriatic coast within the eastern alluvial plain of Po river (Italy), extensively affected by subsidence with strong spatial and temporal variations. The results reveal high rates of long-term subsidence of the study area and the effectiveness of the presented methodology for producing unique ground deformation maps over wide areas. .

Earthquakes cause a huge number of landslides and alter the regional landslide risk distribution. As a result, after a significant earthquake, the landslide susceptibility maps (LSMs) must be updated. The study goal was to create seismic landslide susceptibility maps containing landslide causative variables which are adaptable to great changes in susceptibility after the Jiuzhaigou earthquake (MS 7.0) and to perform a rapid update of the LSM after the earthquake by means of the distributed scatterer interferometric synthetic aperture radar (DS-InSAR) technique. We selected the territory of Jiuzhaigou County (southwestern China) as the study region. Jiuzhaigou is a world-renowned natural heritage and tourist area of great human and ecological value. For landslide susceptibility mapping, we examined the applicability of three models (logistic regression, support vector machine, and random forest) for landslide susceptibility mapping and offered a strategy for updating seismic landslide susceptibility maps using DS-InSAR. First, using logistic regression, support vector machine, and random forest techniques, susceptibility models of seismic landslides were built for Jiuzhaigou based on twelve contributing variables. Second, we obtained the best model parameters by means of a Bayesian network and network search, while using five-fold cross-validation to validate the optimized model. According to the receiver operating characteristic curve (ROC), the SVM model and RF model had excellent prediction capability and strong robustness over large areas compared with the LR models. Third, the surface deformation in Jiuzhaigou was calculated using DS-InSAR technology, and the deformation data were adopted to update the landslide susceptibility model using the correction matrix. The correction of deformation data resulted in a susceptibility class transition in 4.87 percent of the research region. According to practical examples, this method of correcting LSMs for the continuous monitoring of surface deformation (DS-InSAR) was effective. Finally, we analyze the reasons for the change in the revised LSM and point out the help of ecological restoration in reducing landslide susceptibility. The results show that the integration of InSAR continuous monitoring not only improved the performance of the LSM model but also adapted it to track the evolution of future landslide susceptibility, including seismic and human activities.

Multitemporal interferometric synthetic aperture radar (MTI) displacement time series are usually characterized by the model-dependent temporal phase coherence as a quality measure. Additional tests have to be performed to recognize other “interesting” but nonmodeled trends, and several automated approaches to this task have been proposed to date. We introduce here the fuzzy entropy ($F_{E}$), a measure introduced in medical data analysis, as a viable parameter to characterize MTI time series. Being a measure of disorder in a time series, $F_{E}$ exhibits homogeneously low values for a large class of displacement models, such as seasonal, parabolic, or piecewise linear signals, while increasing for more chaotic trends, dominated by noise. It appears therefore suited as a discriminative parameter to isolate meaningful MTI time series within large data sets, without specifying a predefined model. The calculation of $F_{E}$ has low computational cost and can thus be easily performed as a prescreening filter. In this letter, results over simulated data and some examples on a real data set are shown with interesting performances which hint to possible large-scale implementations. [ABSTRACT FROM AUTHOR]

Persistent Scatterer Interferometry (PSI) is a time series remote sensing technique to estimate displacements of geo-objects from the interferometric phases of selected Persistent Scatterers (PS). The relative position of a scatterer within a resolution cell causes an additional phase contribution in the observed phase, which needs to be accounted for in PSI processing. Here we analyze the influence of this sub-pixel position correction on point localization and displacement quality. Apart from a theoretical evaluation, we perform experiments with TerraSAR-X, Radarsat-2, and Sentinel-1, demonstrating various levels of improvement. We show that the influence of the sub-pixel correction is significant for the geolocation of the scatterer (meter-level improvement), modest for the elevation estimation (centimeter-level improvement), and limited for the displacement estimation (submillimeter-level). For displacement velocities, we find variations of a few tenths of a millimeter per year. The effect of sub-pixel correction is most dominant for large orbital baselines and short time series. [ABSTRACT FROM AUTHOR]

Multi-temporal interferometric Persistent Scatterers Interferometry (PSI) techniques derive from the elaboration of satellite Synthetic Aperture Radar (SAR) images and represent a useful tool to detect ground millimetric movements over wide areas; thanks to non-invasiveness and high accuracy. However, PSI data are relative measurements estimated along the sensor Line Of Sight and referred to a chosen stable motionless reference point, so they lack absolute reference both in time and space. In this work, we propose a methodological procedure that exploits Global Navigation Satellite System (GNSS) data acquired from permanent stations to calibrate and fix relative InSAR results into conventional geodetic reference systems. Mean yearly velocities of PSI radar targets are corrected with GNSS values throughout operative procedures used in geodesy for crustal and local deformation data. The methodology is tested in Ravenna and Ferrara cities on the north-western Adriatic coast within the eastern alluvial plain of Po river (Italy), extensively affected by subsidence with strong spatial and temporal variations. The results reveal high rates of long-term subsidence of the study area and the effectiveness of the presented methodology for producing unique ground deformation maps over wide areas.. [ABSTRACT FROM AUTHOR]

Synthetic Aperture Radar Interferometry (InSAR) techniques have been long exploited for detecting and mapping slow-moving ground surface displacements due to their millimeter accuracy, non-invasiveness and wide area coverage. A review on different applications of Persistent Scatterers InSAR approaches, proposed and applied over Tuscany region (Italy) across time, is here presented. The study area is characterized by both subsidence of alluvial plains and landslides on hilly and mountainous reliefs. Tuscany has a leading role in Italy in the field of interferometric applications: the first InSAR analyses, which date back to 2003, were performed at local basin scale, by exploiting various PSI-based approaches for risk mapping. The first InSAR applications at regional scale date back to 2009, relying on historical SAR archives of ERS and ENVISAT satellites for updating subsidence and landslide inventory maps at a certain temporal date. Nowadays, the availability of Sentinel-1 SAR data with a regular and systematic 6-days acquisitions plan, allows near-real time monitoring of deformative scenario at regional scale rather than solely mapping of geo-hydrological phenomena. Most recent innovative InSAR applications over Tuscany region scan the territory, exploiting the regular repeat pass of Sentinel-1, and promptly highlight the sites affected by the highest ground movements with high temporal frequency. Such approaches permit us to pass from a static ‘picture’ of regional slope instability to a weekly updated ‘movie’ with improved detail, useful for civil protection practices. These last ongoing works significantly enhance the value of multi-temporal InSAR approaches for investigating and managing geo-hazards over the Region.

The combination of ascending and descending persistent scatterers interferometric (PSI) data by means of resampling and/or spatial interpolation, separately for each synthetic aperture radar geometry, is a commonly followed procedure, limited though by the reduced spatial coverage and the introduced uncertainties from multiple rasterization steps. Herein, an alternative approach is proposed for combining different PSI line-of-sight observables in the vector domain, based on the geographic proximity of PS point targets. In the proposed nearest neighbour vector approach all necessary analysis steps are performed by means of attributes transfer and calculations between features geodatabases, prior to any rasterization. By increasing the number of input point vectors during subsequent interpolation, the overall error budget coming from spatial interpolation is being reduced. The advantages of the proposed vector-based approach compared to the commonly used grid-based procedure are being demonstrated using real data. [ABSTRACT FROM AUTHOR]

Since the 1970s, land subsidence has been rapidly developing on the Beijing Plain, and the systematic study of the evolutionary mechanism of this subsidence is of great significance in the sustainable development of the regional economy. On the basis of Interferometric Synthetic Aperture Radar (InSAR) results, this study employed the Mann–Kendall method for the first time to determine the mutation information of land subsidence on the Beijing Plain from 2004 to 2015. By combining the hydrogeological conditions, “southern water” project, and other data, we attempted to analyse the reasons for land subsidence mutations. First, on the basis of ENVISAT ASAR and RADARSAT-2 data, the land subsidence of the Beijing Plain was determined while using small baseline interferometry (SBAS-InSAR) and Persistent Scatterers Interferometry (PSI). Second, on the basis of the Geographic Information System (GIS) platform, vector data of displacement under different scales were obtained. Through a series of tests, a scale of 960 metres was selected as the research unit and the displacement rate from 2004 to 2015 was obtained. Finally, a trend analysis of land subsidence was carried out on the basis of the Mann–Kendall mutation test. The results showed that single-year mutations were mainly distributed in the middle and lower parts of the Yongding River alluvial fan and the Chaobai River alluvial fan. Among these mutations, the greatest numbers occurred in 2015 and 2005, being 1344 and 915, respectively. The upper and middle alluvial fan of the Chaobai River, the vicinity of the emergency water sources, and the edge of the groundwater funnel have undergone several mutations. Combining hydrogeological data of the study area and the impact of the south-to-north water transfer project, we analysed the causes of these mutations. The experimental results can quantitatively verify the mutation information of land subsidence in conjunction with time series to further elucidate the spatial-temporal variation characteristics of land subsidence in the study area.

The evaluation of landslide specific risk, defined as the expected degree of loss due to landslides, requires the parameterization and the combination of a number of socio-economic and geological factors, which often needs the interaction of different skills and expertise (geologists, engineers, planners, administrators, etc.). The specific risk sub-components, i.e., hazard and vulnerability of elements at risk, can be determined with different levels of detail depending on the available auxiliary data and knowledge of the territory. These risk factors are subject to short-term variations and nowadays turn out to be easily mappable and evaluable through remotely sensed data and GIS (Geographic Information System) tools. In this work, we propose a qualitative approach at municipal scale for producing a "specific risk" map, supported by recent satellite PSI (Persistent Scatterer Interferometry) data derived from SENTINEL-1 C-band images in the spanning time 2014-2017, implemented in a GIS environment. In particular, PSI measurements are useful for the updating of a landslide inventory map of the area of interest and are exploited for the zonation map of the intensity of ground movements, needed for evaluating the vulnerability over the study area. Our procedure is presented throughout the application to the Volterra basin and the output map could be useful to support the local authorities with updated basic information required for environmental knowledge and planning at municipal level. Moreover, the proposed procedure is easily managed and repeatable in other case studies, as well as exploiting different SAR sensors in L- or X-band. [ABSTRACT FROM AUTHOR]

Road and rail networks provide critical support for society, yet they can be degraded by seasonal soil movements. Currently, few transport network operators monitor small-scale soil movement, but understanding the conditions contributing to infrastructure failure can improve network resilience. Persistent Scatterers Interferometry (PSI) is a remote sensing technique offering the potential for near real-time ground movement monitoring over wide areas. This study tests the use of PSI for monitoring the response of major roads, minor roads, and railways to ground movement across six study sites in England, using Sentinel 1 data in VV polarisation in ascending orbit. Some soils are more stable than others--a national soil map was used to quantify the relationships between infrastructure movement and major soil groups. Vertical movement of transport infrastructure is a function of engineering design, soil properties, and traffic loading. Roads and railways built on soil groups prone to seasonal water-logging (Ground-water Gley soils, Surface-water Gley soils, Pelosols, and Brown soils) demonstrated seasonal subsidence and heave, associated with an increased risk of infrastructure degradation. Roads and railways over Podzolic soils demonstrated relative stability. Railways on Peat soils exhibited the most extreme continual subsidence of up to 7.5 mm year-1. Limitations of this study include the short observation period (~13 months, due to satellite data availability) and the regional scale of the soil map--mapping units contain multiple soil types with different ground movement potentials. Future use of a higher resolution soil map over a longer period will advance this research. Nevertheless, this study demonstrates the viability of PSI as a technique for measuring both seasonal soil-related ground movement and the associated impacts on road and rail infrastructure. [ABSTRACT FROM AUTHOR]

Persistent Scatterers Interferometry (PSI) represents one of the most powerful techniques for Earth's surface deformation processes' monitoring, especially for long-term evolution phenomena. In this work, a dataset of 34 TerraSAR-X StripMap images (October 2013–October 2014) has been processed by two PSI techniques - Coherent Pixel Technique-Temporal Sublook Coherence (CPT-TSC) and Small Baseline Subset (SBAS) - in order to study the evolution of a slow-moving landslide which occurred on February 23, 2012 in the Papanice hamlet (Crotone municipality, southern Italy) and induced by a significant rainfall event (185 mm in three days). The mass movement caused structural damage (buildings' collapse), and destruction of utility lines (gas, water and electricity) and roads. The results showed analogous displacement rates (30–40 mm/yr along the Line of Sight – LOS-of the satellite) with respect to the pre-failure phase (2008–2010) analyzed in previous works. Both approaches allowed detect the landslide-affected area, however the higher density of targets identified by means of CPT-TSC enabled to analyze in detail the slope behavior in order to design possible mitigation interventions. For this aim, a slope stability analysis has been carried out, considering the comparison between groundwater oscillations and time-series of displacement. Hence, the crucial role of the interaction between rainfall and groundwater level has been inferred for the landslide triggering. In conclusion, we showed that the integration of geotechnical and remote sensing approaches can be seen as the best practice to support stakeholders to design remedial works. [ABSTRACT FROM AUTHOR]

The evaluation of landslide specific risk, defined as the expected degree of loss due to landslides, requires the parameterization and the combination of a number of socio-economic and geological factors, which often needs the interaction of different skills and expertise (geologists, engineers, planners, administrators, etc.). The specific risk sub-components, i.e., hazard and vulnerability of elements at risk, can be determined with different levels of detail depending on the available auxiliary data and knowledge of the territory. These risk factors are subject to short-term variations and nowadays turn out to be easily mappable and evaluable through remotely sensed data and GIS (Geographic Information System) tools. In this work, we propose a qualitative approach at municipal scale for producing a “specific risk” map, supported by recent satellite PSI (Persistent Scatterer Interferometry) data derived from SENTINEL-1 C-band images in the spanning time 2014–2017, implemented in a GIS environment. In particular, PSI measurements are useful for the updating of a landslide inventory map of the area of interest and are exploited for the zonation map of the intensity of ground movements, needed for evaluating the vulnerability over the study area. Our procedure is presented throughout the application to the Volterra basin and the output map could be useful to support the local authorities with updated basic information required for environmental knowledge and planning at municipal level. Moreover, the proposed procedure is easily managed and repeatable in other case studies, as well as exploiting different SAR sensors in L- or X-band.

Road and rail networks provide critical support for society, yet they can be degraded by seasonal soil movements. Currently, few transport network operators monitor small-scale soil movement, but understanding the conditions contributing to infrastructure failure can improve network resilience. Persistent Scatterers Interferometry (PSI) is a remote sensing technique offering the potential for near real-time ground movement monitoring over wide areas. This study tests the use of PSI for monitoring the response of major roads, minor roads, and railways to ground movement across six study sites in England, using Sentinel 1 data in VV polarisation in ascending orbit. Some soils are more stable than others—a national soil map was used to quantify the relationships between infrastructure movement and major soil groups. Vertical movement of transport infrastructure is a function of engineering design, soil properties, and traffic loading. Roads and railways built on soil groups prone to seasonal water-logging (Ground-water Gley soils, Surface-water Gley soils, Pelosols, and Brown soils) demonstrated seasonal subsidence and heave, associated with an increased risk of infrastructure degradation. Roads and railways over Podzolic soils demonstrated relative stability. Railways on Peat soils exhibited the most extreme continual subsidence of up to 7.5 mm year−1. Limitations of this study include the short observation period (~13 months, due to satellite data availability) and the regional scale of the soil map—mapping units contain multiple soil types with different ground movement potentials. Future use of a higher resolution soil map over a longer period will advance this research. Nevertheless, this study demonstrates the viability of PSI as a technique for measuring both seasonal soil-related ground movement and the associated impacts on road and rail infrastructure.

This study deals with the estimation of subtle ground deformation at millimetric accuracy over the broader area of the Mornos River delta in Central Greece and its spatio-temporal distribution for the period between 1992 and 2009 through Persistent Scatterers Interferometry (PSI). The results showed that the majority of the scatterers, which show subsidence, are located within the delta plain with mean subsidence rates throughout the delta varying between -7.2 and +0.7 mm/y. An attempt is made to highlight the geographic distribution, the amplitude, and the causes of the observed delta plain subsidence. The positive correlation between the thickness of the fine-grained Holocene deltaic deposits and the subsidence rates reveals that the main cause is the natural compaction of sediments. The highest subsidence is observed at Bouka Karahassani village, which corresponds to the area of the most recently abandoned river mouth, which is intensely eroded by marine processes. Apart from the dominance of fine sediments in the study area, subsidence may also be attributed to submarine gravitational mass movements along the steep slopes of the prodelta as well as to the reduction of sediment load after the dam construction in 1979. The NW part of the delta seems to have been affected by aseismic slip along a NE-SW trending normal fault buried beneath the alluvial deposits of the Skala torrent fan. [ABSTRACT FROM AUTHOR]

Abstract: The investigation area is located in the most southern part of Sinai Peninsula boarded from the west by the Gulf of Suez and from the east by the Gulf of Aqaba. The present study concerns the application of stacking and persistent scattering of SAR interferometry in order to monitor ground deformation in the southern part of Sharm El-Shiekh area. The specific techniques were applied in order to reduce the influence of atmospheric effects on the ground deformation estimates. For this purpose a total number of 26 ENVISAT ASAR scenes covering the period between 2003 and 2009 were processed and analyzed. Interferometric processing results show both patterns of uplift and downlift in the study area. Specifically an area along the coastline with a N–S direction, corresponding to the build up zone of Sharm El-Sheikh, shows annual average subsidence rates between 5 and 7mm/yr along the line of sight (LOS). On the contrary, Sharm El-Maya, an inner zone, parallel to the above subsided area; shows maximum slant range uplift of 5mm/yr. The obtained results of both stacking and persistent scattering indicate that the ground deformation in Sharm El-Sheikh–Ras Nasrani coastal zone is attributed to several effecting factors compromising water pumping, lithology, seismicity, and possible active fracture. The contribution of all these factors is discussed in the context. [Copyright &y& Elsevier]

Abstract: The aim of this paper is to detect ground deformation detection in the Rio-Antirio area (Western Greece), between 1992 and 2000. The construction of Rio-Antirio bridge, commenced in year 2000 and completed in 2004 when its operation was launched, demands the study of the historic deformation of the broader area. The Interferometric Point Target Analysis (IPTA) was applied using a dataset of 42 ERS-1 and 2 scenes. Two separate IPTA processing were performed using different reference points for Rio and Antirio respectively. It would not be possible to unwrap the entire scenes using a single reference point because of the presence of the sea water mass between Rio and Antirio. The majority of the point targets show subsidence for the area of Rio ranging between −1.8 mm/year and −6.2 mm/year and for the Antirio area stability or subsidence rates of less than 2 mm/year. Additionally, the deformation history for a number of point targets for both areas was investigated. The detected subsidence of the coastal plains and specially this of Rio could be attributed to the presence of active faults as the area is located over the hanging wall of the fault zone. [Copyright &y& Elsevier]

Abstract: This article presents the main results of the Persistent Scatterer Interferometry Codes Cross Comparison and Certification for long term differential interferometry (PSIC4) project. The project was based on the validation of the PSI (Persistent Scatterer Interferometry) data with respect to levelling data on a subsiding mining area near Gardanne, in the South of France. Eight PSI participant teams processed the SAR data without any a priori information, as a blind test. Intercomparison of the different teams'' results was then carried out in order to assess any similarities and discrepancies. The subsidence velocity intercomparison results obtained from the PSI data showed a standard deviation between 0.6 and 1.9 mm/year between the teams. The velocity validation against rates measured on the ground showed a standard deviation between 5 and 7 mm/year. A comparison of the PSI time series and levelling time series shows that if the displacement is larger than about 2 cm in between two consecutive SAR-images, PS-InSAR starts to seriously deviate from the levelling time series. Non-linear deformation rates up to several cm/year appear to be the main reason for these reduced performances, as no prior information was used to adjust the processing parameters. Under such testing conditions and without good ground-truth information, the phase-unwrapping errors for this type of work are a major issue. This point illustrates the importance of having ground truth information and a strong interaction with the end-user of the data, in order to properly understand the type and speed of the deformation that is to be measured, and thus determine the applicability of the technique. [Copyright &y& Elsevier]

Abstract: We present two case studies regarding the application of Synthetic Aperture Radar (SAR) Persistent Scatterers Interferometry (PSI) techniques to landslide-prone slopes situated in the municipal territories of Caramanico Terme and Volturino (Italy). The analysis of satellite SAR data with PSI techniques poses often problems on sites where, due to the scarcity of human artefacts and the presence of vegetation cover, density of coherent points (PS) is low (<10 per km2). Moreover, the steep and rough topography typical of landslide-prone areas hamper the interferometric pre-processing, making more difficult the joint estimation of displacements and of DEM errors. Under these conditions the significance of temporal interferometric phase trends can be uncertain and conservative assumptions, necessary to ensure low false detection probabilities, need to be coupled with innovative processing strategies to increase the detection efficiency of PS objects. Here, the SPINUA (Stable Point Interferometry over Un-urbanised Areas) processing technique is applied together with an alternative PS Candidate (PSC) selection procedure based on the use of pixels classified as urban. The cases of Caramanico and Volturino are representative, respectively, of harsh and favourable conditions for PSI applications. The results from Caramanico show clusters of PS exhibiting similar line-of-sight (LOS) deformation behaviour in the period 1995–2000. The locations of moving PS often coincide with distressed buildings and appear consistent with the areal distribution of recent and past landslide activity. The temporal displacement trends, however, are characterised by very low annual average velocities (from 3 to 7 mm/y) and it is uncertain to what extent the PS data reflect true slope movements, local deformations (e.g. settlement of engineering structures) or both. Thanks to the more favourable conditions, the application of the standard SPINUA approach in the Volturino area was sufficient to obtain suitable densities of PS, as well as spatially and temporally consistent displacement results for a period 1992–2000. In particular, a group of moving PS was identified in a peri-urban area, known for the past and recent slope stability problems. The slowly moving PS (from 3 to 5 mm/y) fall in a location that, unlike the remaining part of the town, is characterised by the presence of many distressed buildings and structures. Although the site information confirms the reliability of PS data, in the absence of ground monitoring and detailed records of landslide movements, it is difficult to identify the main mechanism of the detected deformations. In general, in geologically and topographically complex urban/peri-urban settings, the significance of very low-velocity PSI surface displacements should always be considered together with in situ geotechnical controls and ground monitoring data. [Copyright &y& Elsevier]

Since the 1970s, land subsidence has been rapidly developing on the Beijing Plain, and the systematic study of the evolutionary mechanism of this subsidence is of great significance in the sustainable development of the regional economy. On the basis of Interferometric Synthetic Aperture Radar (InSAR) results, this study employed the Mann–Kendall method for the first time to determine the mutation information of land subsidence on the Beijing Plain from 2004 to 2015. By combining the hydrogeological conditions, "southern water" project, and other data, we attempted to analyse the reasons for land subsidence mutations. First, on the basis of ENVISAT ASAR and RADARSAT-2 data, the land subsidence of the Beijing Plain was determined while using small baseline interferometry (SBAS-InSAR) and Persistent Scatterers Interferometry (PSI). Second, on the basis of the Geographic Information System (GIS) platform, vector data of displacement under different scales were obtained. Through a series of tests, a scale of 960 metres was selected as the research unit and the displacement rate from 2004 to 2015 was obtained. Finally, a trend analysis of land subsidence was carried out on the basis of the Mann–Kendall mutation test. The results showed that single-year mutations were mainly distributed in the middle and lower parts of the Yongding River alluvial fan and the Chaobai River alluvial fan. Among these mutations, the greatest numbers occurred in 2015 and 2005, being 1344 and 915, respectively. The upper and middle alluvial fan of the Chaobai River, the vicinity of the emergency water sources, and the edge of the groundwater funnel have undergone several mutations. Combining hydrogeological data of the study area and the impact of the south-to-north water transfer project, we analysed the causes of these mutations. The experimental results can quantitatively verify the mutation information of land subsidence in conjunction with time series to further elucidate the spatial-temporal variation characteristics of land subsidence in the study area. [ABSTRACT FROM AUTHOR]