Advanced Differential SAR Interferometry Research Articles

Impact assessment of unsustainable airport development in the Himalayas using remote sensing: A case study of Pakyong Airport, Sikkim, India

Ground deformation is a widespread phenomenon that accelerates due to anthropogenic land development. Thus reclaimed/created land is more vulnerable to deformation and subsidence, especially in mountain areas. Advanced Differential Synthetic Aperture Radar Interferometry (A-DInSAR) can be used to monitor such projects. The Pakyong Airport is an engineering feat, constructed by cutting a mountain and converting it into a tabletop in a landslide-prone zone and seismically active region of the Sikkim Himalayas. The cutting of hill slopes for airport construction and other anthropogenic activities has increased slope instability in the region. This paper studies the slow-moving landslides in the airport neighbourhood using A-DInSAR on Sentinel-1 time series data consisting of 64 images of ascending track and 82 images of the descending track. The time period of monitoring was from October 2014 to April 2018 (43 months). The images have been connected using the Minimum Spanning Tree graph for interferogram generation for estimating deformation. The atmospheric noise was removed, and the results enabled the identification of deformation (in line-of-sight) on the airstrip as well as in the neighbouring area, both the upslope and downslope of the airport. The deformation rates estimated were up to ±90 mm/year in Pakyong from both tracks. We could successfully capture such land movement associated with the Pakyong Airport construction and help assess the impacts of infrastructure construction on the slope stability of the area. The controlling factors such as precipitation, seismicity, geology and others were analysed with respect to the deformation obtained. This study helps in assessing the land deformation after construction (cutting and filling of the slope) in the area. The deformation detected in this study needs to be addressed for the safety of the residents as well as for the infrastructure present in the area.

A Low-Cost and Fast Operational Procedure to Identify Potential Slope Instabilities in Cultural Heritage Sites

Italy is famous for its one-of-a-kind landscapes and the many cultural heritage sites characterizing the story of its regions. In central Italy, during the medieval age, some of them were built on the top of high and steep cliffs, often on the top of ancient ruins, to protect urban agglomerations, goods and people. The geographical locations of these centers allowed them to maintain their original conformation over time, but, at the same time, exposed them to a high risk of landslides. In this context, this research aimed to present an integrated and low-cost approach to study the potential landslide phenomena affecting two medieval towns. Field surveys and mapping were carried out through the use of innovative digital mapping tools to create a digital database directly on the field. Data gathered during field surveys were integrated with GIS analyses for an improved interpretation of the geological and geomorphological features. Due to the inaccessibility of the cliffs surrounding the two villages, a more detailed analysis of these areas was performed through the use of unmanned aerial vehicle-based photogrammetry, while advanced differential synthetic aperture radar interferometry (A-DInSAR) interpretation was undertaken to verify the stability of the buildings in proximity to the cliffs and other potential active failures. The results of the study highlighted the similar geometry and structural settings of the two areas. Kinematically, the intersection of three main joint sets tends to detach blocks (sometimes in high volumes) from the cliffs. The A-DInSAR analysis demonstrated the presence of a landslide failure along the northwest side of the Monte San Martino town. The buildings in proximity to the cliffs did not show evidence of movements. More generally, this research gives insights into the pro and cons of different survey and analysis approaches and into the benefits of their procedural integration in space and in time. Overall, the procedure developed here may be applied in similar contexts in order to understand the structural features driving slopes’ instabilities and create digital databases of geological/monitoring data.

Slope-Scale Evolution Categorization of Deep-Seated Slope Deformation Phenomena with Sentinel-1 Data

Deep-seated gravitational slope deformations (DsGSDs) are slope-scale phenomena which are widespread in mountainous regions. Despite interacting with human infrastructures and settlements, only a few cases are monitored with ground-based systems. Remote sensing technologies have recently become a consolidated instrument for monitoring and studying such widespread and slow processes. This paper proposes a three-step novel methodology to analyze the morpho-structural domain of DsGSDs by exploiting the advanced Differential Synthetic Aperture Radar Interferometry (A-DInSAR) technique through (i) the analysis of A-DInSAR measurement point density and distribution defining a coverage threshold; (ii) the assessment of the actual ground deformation with respect to the orientation of phenomena based on slope, aspect, and C-index; and (iii) ground deformation mapping with previously ranked velocity interpolation. The methodology was tested on two differently oriented phenomena: the mainly north–south-oriented Croix de Fana and the mainly east–west-oriented Valtournenche DsGSD, located in the Aosta Valley Region, northern Italy. The results show a variation in the kinematic behavior between the morpho-structural domains, while also considering any other superimposed surficial deformations. This work provides the lines for the implementation of a rapid and low-cost tool based on the use of A-DInSAR measurements which are suitable for assessing the impact of any type of DsGSD on the anthropic facilities and infrastructures in mountainous areas.

Ground subsidence associated with mining activity in the Ningdong coal base area, northwestern China revealed by InSAR time series analysis

Ningdong coal base area located in northwestern China is one of the largest coal-producing bases in China. The aim of this work is to investigate a regional-scale mining subsidence over the Ningdong coal base area, by using both conventional and advanced Differential Synthetic Aperture Radar Interferometry (DInSAR) methods. Fifteen L-band SAR images from ALOS-2 satellite and 102 C-band images from Sentinel-1A satellite spanning between November 2014 and July 2019 were used for the analysis. To increase the spatial extent of the displacement signal because of decorrelated effects, we modified the traditional Small Baseline Subset (SBAS) method to incorporate the coherence into the inverse problem, hereafter we call it coherence-based SBAS method. Instead of excluding decorrelated pixels present in the interferograms, we keep all the pixels in the time series analysis and down-weighted the decorrelated pixels with coherence. We performed the coherence-based SBAS method to both the two SAR datasets to obtain the subsidence rate maps and displacement time-series over the mining areas, and compared the results with that from the traditional stacking InSAR method. We evaluated the effectiveness of L-band and C-band DInSAR for monitoring mining subsidence by comparing differential interferograms and displacements derived from SBAS method between ALOS-2 and Sentinel-1A data. Compared to C-band, L-band SAR are less affected by phase aliasing due to large displacement gradients. The most significant subsidence was found at Maliantai mine with −264 mm/year detected by SBAS method from Sentinel-1 data. We validated the InSAR displacement accuracy by comparing both ALOS-2 and Sentinel-1 results with 18 GPS stations above five active mining regions. The average RMSE between InSAR and GPS measurements is 28.4 mm for Sentinel-1 data and 21 mm for ALOS-2 data. Our results demonstrate that the combined exploitation of L-band and C-band SAR data through both conventional and advanced DInSAR methods could be crucial to monitor ground subsidence in mining areas, which provides insights into subsidence dynamics and determine the characteristic surface response to longwall advance.

Geomorphological characterization, remote sensing monitoring, and modeling of a slow-moving landslide in Alcoy (Southern Spain)

In the present paper, an active landslide located to the southeast of the urban area of Alcoy (Alicante, Spain) is analysed. This landslide affects the N-340 road, as well as an area in which some industrial buildings dated from the fifteenth century and catalogued as Places of Cultural Interest are placed. This region is characterised by the existence of a steep relief composed of materials from the Miocene to the present, on which many gravitational movements are developed. The displacements have been analysed using high-resolution spotlight mode SAR images captured by the Spanish SAR satellite PAZ (which operates at X-band), which were processed by advanced differential SAR Interferometry (A-DInSAR). The behaviour of the instability has been determined using InSAR-derived time series displacement maps. Additionally, the study has been completed with a detailed geomorphological mapping at 1:2000 scale and an analysis of structural damage carried out in situ. The landslide was modelled in 3D, from a deterministic and probabilistic point of view, confirming the global instability of the area and the relationship of the landslide with rainfall and the construction of a new road. The integration of all this information obtained and its subsequent analysis has made possible to precisely define the extension of the instability, its kinematics, and to identify the main triggering factors. This information will be crucial for the proper management of this landslide by the local authorities.

Comments on “Study of Systematic Bias in Measuring Surface Deformation With SAR Interferometry”

In a recent publication, Ansari <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> (2021) claimed (see, in particular, the Discussion and Recommendation Section in their article) that the advanced differential SAR interferometry (InSAR) algorithms for surface deformation retrieval, based on the small baseline approach, are affected by systematic biases in the generated InSAR products. Therefore, to avoid such biases, they recommended a strategy primarily focused on excluding “the short temporal baseline interferograms and using long baselines to decrease the overall phase errors.” In particular, among various techniques, Ansari <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> (2021) identified the solution presented by Manunta <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> (2019) as a small baseline advanced InSAR processing approach where the presence of the above-mentioned biases (referred to as a fading signal) compromises the accuracy of the retrieved InSAR deformation products. We show that the claim of Ansari <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> (2021) is not correct (at least) for what concerns the mentioned approach discussed by Manunta <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> (2019). In particular, by processing the Sentinel-1 dataset relevant to the same area in Sicily (southern Italy) investigated by Ansari <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> (2021), we demonstrate that the generated InSAR products do not show any significant bias.

The Role of Satellite InSAR for Landslide Forecasting: Limitations and Openings

The paper explores the potential of the satellite advanced differential synthetic aperture radar interferometry (A-DInSAR) technique for the identification of impending slope failure. The advantages and limitations of satellite InSAR in monitoring pre-failure landslide behaviour are addressed in five different case histories back-analysed using data acquired by different satellite missions: Montescaglioso landslide (2013, Italy), Scillato landslide (2015, Italy), Bingham Canyon Mine landslide (2013, UT, USA), Big Sur landslide (2017, CA, USA) and Xinmo landslide (2017, China). This paper aimed at providing a contribution to improve the knowledge within the subject area of landslide forecasting using monitoring data, in particular exploring the suitability of satellite InSAR for spatial and temporal prediction of large landslides. The study confirmed that satellite InSAR can be successful in the early detection of slopes prone to collapse; its limitations due to phase aliasing and low sampling frequency are also underlined. According to the results, we propose a novel landslide predictability classification discerning five different levels of predictability by satellite InSAR. Finally, the big step forward made for landslide forecasting applications since the beginning of the first SAR systems (ERS and Envisat) is shown, highlighting that future perspectives are encouraging thanks to the expected improvement of upcoming satellite missions that could highly increase the capability to monitor landslides’ pre-failure behaviour.

Ground displacements revealed by A-DInSAR analysis in the Germano iron mining complex before and after the Fundão Dam collapse using Sentinel-1 data

Advanced differential SAR interferometry (A-DInSAR) has been used as an effective monitoring tool in mining environments. This work presents an investigation of surface displacement in the Germano iron mining complex (Mariana, Minas Gerais, Brazil), where on November 5, 2015, the Fundão tailings dam collapsed. Initially, the analysis was performed with 14 Sentinel-1 images, acquired from May 8, 2015, to November 4, 2015, and focused on the Fundão dam before its rupture to detect prior signs of surface deformations. The analysis after the Fundão dam collapse was conducted in the Germano area using 43 Sentinel-1 images, acquired from November 16, 2015 to May 15, 2017, and aimed at detecting surface displacement on the remaining infrastructure, the Sela&Tulipa and Selinha dikes and the main Germano tailings dam, which were directly or indirectly affected by the accident. The results reveal precursor signals of surface displacement at the Fundão dam prior to rupture, particularly on the left abutment setback sector where the collapse started according to a witness, reaching accumulated values of up to −60 mm. The results provided by the A-DInSAR analysis after the dam collapse indicate a stability in the Sela&Tulipa and Selinha dikes as well as in the main Germano dam, which is corroborated by in situ topographic measurements. On the auxiliary dikes within the Germano reservoir, accumulated displacement of up to −90 mm caused by settlements and continuous traffic of vehicles was detected. In addition, the detected accumulate displacement within the reservoir showed values of up to −120 mm, in general caused by settlements of the waste dry material due to the inactivity of the mining process. The investigation emphasized the important role that satellite-based A-DInSAR can play in mitigating possible accidents and for operational planning and risk assessment in mining operations.

Tracking Deformation Processes at the Legnica Glogow Copper District (Poland) by Satellite InSAR—I: Room and Pillar Mine District

Mining exploitation leads to slow or rapid ground subsidence resulting from deformation until the collapse of underground post-mining voids following excavation activities. Satellite SAR interferometry capabilities for the evaluation of ground movements allows the monitoring of intensive surface mine subsidence and can provide new knowledge about the risks in the mining industry. This work integrates both conventional and advanced Differential SAR Interferometry (DInSAR) to study the ground subsidence in the Legnica Glogow Copper District (LGCD, Poland) by processing about 400 Sentinel-1 images from October 2014 to April 2019. Even without field data and information on past and ongoing excavation activities, the DInSAR approach allowed us to identify 30 troughs of subsidence, ranging from 500 m to 2.5 km in diameter, which in some cases, took place several times during the analyzed time span. The cumulative subsidence in 4 years and 7 months exceeds 70 cm in several zones of the LGCD. The sub-centimetric precision achieved by advanced analysis (A-DInSAR), allowed us to monitor the real extent of the mining influence area on the surface, with deformation velocities of up to 50 mm/year. The ground deformation detected at LGCD can be due to both mining-induced tremors and roof subsidence above the underground excavation rooms. As deformations do not occur concurrently with tremors, this can be related to excavation activities or to degradation of abandoned mines.

Tracking Deformation Processes at the Legnica Glogow Copper District (Poland) by Satellite InSAR—II: Żelazny Most Tailings Dam

The failures of tailings dams have a major negative impact on the economy, surrounding properties, and people’s lives, and therefore the monitoring of these facilities is crucial to mitigate the risk of failure, but this can be challenging due to their size and inaccessibility. In this work, the deformation processes at Żelazny Most tailings dam (Poland) were analyzed using satellite Ad-vanced Differential SAR Interferometry (A-DInSAR) from October 2014 to April 2019, showing that the dam is affected by both settlements (with a maximum rate of 30 mm/yr), and horizontal sliding in radial direction with respect to the ponds. The load of the tailings is pushing the dam forward along the glacio-tectonic shear planes located at depth, in the Pliocene clays, causing horizontal displacements at a rate up to 30 mm/yr, which could lead to a passive failure of the dam. The measured displacements have been compared with the ones observed by in situ data from the 90s to 2013, available in the literature. The outcomes indicate that intense localized deformations occur in the eastern and northern sectors of the dam, while the western sector is deforming evenly. Moreover, although the horizontal deformation had a slowdown from 2010 until 2013, it continued in 2014 to 2019 with recovered intensity. The upper and the recent embankments are affected by major settlements, possibly due to a lower consolidation degree of the most recent tailings and a larger thickness of compressible materials.

Geodetic Study of the 2006–2010 Ground Deformation in La Palma (Canary Islands): Observational Results

La Palma is one of the youngest of the Canary Islands, and historically the most active. The recent activity and unrest in the archipelago, the moderate seismicity observed in 2017 and 2018 and the possibility of catastrophic landslides related to the Cumbre Vieja volcano have made it strongly advisable to ensure a realistic knowledge of the background surface deformation on the island. This will then allow any anomalous deformation related to potential volcanic unrest on the island to be detected by monitoring the surface deformation. We describe here the observation results obtained during the 2006–2010 period using geodetic techniques such as Global Navigation Satellite System (GNSS), Advanced Differential Synthetic Aperture Radar Interferometry (A-DInSAR) and microgravimetry. These results show that, although there are no significant associated variations in gravity, there is a clear surface deformation that is spatially and temporally variable. Our results are discussed from the point of view of the unrest and its implications for the definition of an operational geodetic monitoring system for the island.

Inferring the Creep Settlement Behavior of Rockfill in Reclaimed Lands by Advanced SAR Interferometry and Numerical Modeling: An Example from Arabian Gulf

Satellite Advanced Differential Synthetic Aperture Radar Interferometry (A-DInSAR) is becaming a key-technique for monitoring ground deformations. The potential of A-DInSAR for settlement monitoring is exploited in this paper through the investigation of a reclaimed land in Dubai (UAE). Time histories of displacements were obtained from COSMO-SkyMed satellite images over the period between 2011 to 2016, allowing to derive the long-term deformation of the entire artificial island. Special attention was paid on long-term settlement of the hydraulically-placed rockfill of the peripheral rubble-mound revetments. The A-DInSAR results have been compared with results derived from numerical analyses and with field surveys, proving the relation between observed and modeled displacements. The study has also revealed that rockfill long-term settlement (creep) rate is significantly dependent on the aging (time since placement). In the analyzed time-frame (2011–2016) it has been observed that recently placed rockfill experienced creep rate up to ten times higher than the creep rate measured for similar rockfill structures placed 30 years earlier. Furthermore, it has been demonstrated that static compression by preloading and dynamic or impact densification induced by wave forces proved to have also a significant impact on reducing the creep rate of the rockfill.

Advanced DINSAR analysis on dam stability monitoring: A case study in the Germano mining complex (Mariana, Brazil) with SBAS and PSI techniques

This work presents an investigation of detection and monitoring of surface motions using Advanced Differential SAR Interferometry (A-DInSAR) with SBAS (Small Baseline Subset) and PSI (Persistent Scatterer Interferometry) techniques in the Germano iron mining complex region (Mariana, Brazil), after the collapse of the Fundão tailing dam occurred on November 5th, 2015. The research was carried out aiming to provide useful information about ground movement monitoring, planning and risk assessment in the area after the tragic event. The analysis was performed using 46 TerraSAR-X images and a Digital Elevation Model (DEM) obtained by Pleiades data. A-DInSAR processing provided the removal of the atmospheric phase artifacts, baseline related errors, DEM height error estimation and finally the ground displacement determination. The results pointed out that with both techniques it was possible to assess the stability conditions of the Germano mining assets, particularly the main structures of the Germano dam and the detection of small settlements in the mining tailings storage, pointing out that these may be an important components for risk management of open pit mining operations, including tailings dams.

Mapping and Characterizing Thermal Dilation of Civil Infrastructures with Multi-Temporal X-Band Synthetic Aperture Radar Interferometry

Temperature variation plays a significant role in the long-term structural behaviour of civil infrastructures, but very few quantitative studies have measured and analysed the infrastructures&rsquo; global thermal dilation because of their large sizes and geometric complexities. The modern Differential Synthetic Aperture Radar Interferometry (DInSAR) technique has great potential in applications of their thermal dilation mapping and characterization due to the techniques&rsquo; unique capabilities for use in large areas, with high-resolution, and at low-costs for deformation measurements. However, the practical application of DInSAR in thermal dilation estimation is limited by difficulty in the precise separation from the residual topographic phase and the trend deformation phase. Moreover, due to a lack of thermal dilation characteristics analyses in previous studies, the thermal dilation mechanisms are still unclear to users, which restricts the accurate understanding of the thermal dilation evolution process. Given the above challenges, an advanced multi-temporal DInSAR approach is proposed in this study, and the effectiveness of this approach was presented using three cases studies concerning different infrastructure types. In this method, the coherent, incoherent, and semantic information of structures were combined in order to refine the detection of point-like targets (PTs). Interferometric subsets with small temporal baselines and temperature differences were used for high-resolution topography estimation. A pre-analysis was adopted to determine the transmission direction, spatial pattern, and temporal variation of the thermal dilation. Then, both the traditional least squares estimation and our robust coherence-weighted least squares regression analysis were performed between the time series displacements and the corresponding temperatures to quantitatively estimate the thermal dilation model. The results were verified in terms of the estimated linear thermal dilation coefficient, which indicates the greater reliability of our method. Furthermore, the thermal dilation characteristics of different civil infrastructure types were analysed, which facilitates a greater understanding of the thermal dilation evolution process of civil infrastructures.

Suitability Assessment of X-Band Satellite SAR Data for Geotechnical Monitoring of Site Scale Slow Moving Landslides

This work addresses the suitability of using X-band Synthetic Aperture Radar (SAR) data for operational geotechnical monitoring of site scale slow moving landslides, affecting urban areas and infrastructures. The scale of these studies requires high resolution data. We propose a procedure for the practical use of SAR data in geotechnical landslides campaigns, that includes an appropriate dataset selection taking into account the scenario characteristics, a visibility analysis, and considerations when comparing advanced differential SAR interferometry (A-DInSAR) results with other monitoring techniques. We have determined that Sentinel-2 satellite optical images are suited for performing high resolution land cover classifications, which results in the achievement of qualitative visibility maps. We also concluded that A-DInSAR is a very powerful and versatile tool for detailed scale landslide monitoring, although in combination with other instrumentation techniques.

Monitoring Land Subsidence in a Rural Area Using a Combination of ADInSAR and Polarimetric Coherence Optimization

This paper investigates a combination of advanced differential synthetic aperture radar interferometry (ADInSAR) with different coherence optimization methods. After the launch of satellites with polarimetry capabilities, differential synthetic aperture radar interferometry (DInSAR) is feasible to generate polarimetric DInSAR to enhance pixel phase quality and increase coherent pixel (CP) density. The first method proposed in this paper, modified coherence set-based polarimetry optimization (MCPO), is a modification of a known single-baseline coherence optimization method to optimize coherence of all interferograms simultaneously. The second method, coherence-set based polarimetry optimization (CPO), was presented by Neumann et al., and is an existing revision of the single-baseline coherence optimization technique. The final method, exhaustive search polarimetry optimization, is a search-based approach to find the optimized scattering mechanism introduced by Navarro-Sanchez et al. The case study is the Tehran basin located in the North of Iran, which suffers from a high-rate of land subsidence and is covered by agricultural fields. Usually such an area would significantly decorrelate but applying polarimetric ADInSAR allows us to obtain a more CP coverage. A set of dual polarization TerraSAR-X images with 9 × 9 and 15 × 15 as multilook factors were used within the polarimetric ADInSAR procedure. All three coherence optimization methods with two different multilook factors are shown to have increased the density and phase quality of CPs. Moreover, the estimated deformation rates were evaluated using available levelling measurements. MCPO, which is presented in this paper, works more successful than CPO in terms of CPs density, phase quality and deformation accuracy.

Combination of Conventional and Advanced DInSAR to Monitor Very Fast Mining Subsidence with TerraSAR-X Data: Bytom City (Poland)

In this work, the analysis of TerraSAR-X satellite images combining both conventional and advanced Differential Synthetic Aperture Radar Interferometry (DInSAR) approaches has proven to be effective to detect and monitor fast evolving mining subsidence on urban areas in the Upper Silesian Coal Basin (Poland). This region accounts for almost three million inhabitants where mining subsidence has produced severe damage to urban structures and infrastructures in recent years. Conventional DInSAR approach was used to generate 28 differential interferograms between 5 July 2011 and 21 June 2012 identifying 31 subsidence troughs that account up to 245 mm of displacement in 54 days (equivalent to 1660 mm/year). SqueeSARTM processing yielded a very dense measurement point distribution, failing to detect faster displacements than 330 mm/year, which occur within the subsidence troughs detected with conventional DInSAR. Despite this limitation, this approach was useful to delimit stable areas where mining activities are not conducted and areas affected by residual subsidence surrounding the detected subsidence troughs. These residual subsidence mining areas are located approximately 1 km away from the 31 detected subsidence troughs and account for a subsidence rate greater than 17 mm/year on average. The validation of this methodology has been performed over Bytom City were underground mining activity produced severe damages in August 2011. Conventional DInSAR permitted to successfully map subsidence troughs between July and August 2011 that coincide spatially and temporally with the evolution of underground mining excavations, as well as with the demolition of 28 buildings of Karb district. Additionally, SqueeSARTM displacement estimates were useful to delimit an area of 8.3 km2 of Bytom city that is affected by a residual mining subsidence greater than 5 mm/year and could potentially suffer damages in the midterm. The comparison between geodetic data and SqueeSARTM for the common monitoring period yields and average absolute difference of 7 mm/year, which represents 14% of the average displacement rate measured by the geodetic benchmarks. These results demonstrate that the combined exploitation of high-resolution satellite SAR data through both conventional and advanced DInSAR techniques could be crucial to monitor fast evolving mining subsidence, which may severely impact highly populated mining areas such as the Upper Silesia Coal Basin (USCB).

Analysis of deformation patterns through advanced DINSAR techniques in Istanbul megacity

Abstract. As result of the Turkey’s economic growth and heavy migration processes from rural areas, Istanbul has experienced a high urbanization rate, with severe impacts on the environment in terms of natural resources pressure, land-cover changes and uncontrolled sprawl. As a consequence, the city became extremely vulnerable to natural and man-made hazards, inducing ground deformation phenomena that threaten buildings and infrastructures and often cause significant socio-economic losses. Therefore, the detection and monitoring of such deformation patterns is of primary importance for hazard and risk assessment as well as for the design and implementation of effective mitigation strategies. Aim of this work is to analyze the spatial distribution and temporal evolution of deformations affecting the Istanbul metropolitan area, by exploiting advanced Differential SAR Interferometry (DInSAR) techniques. In particular, we apply the Small BAseline Subset (SBAS) approach to a dataset of 43 TerraSAR-X images acquired, between November 2010 and June 2012, along descending orbits with an 11-day revisit time and a 3 m × 3 m spatial resolution. The SBAS processing allowed us to remotely detect and monitor subsidence patterns over all the urban area as well as to provide detailed information at the scale of the single building. Such SBAS measurements, effectively integrated with ground-based monitoring data and thematic maps, allows to explore the relationship between the detected deformation phenomena and urbanization, contributing to improve the urban planning and management.

Enhanced landslide investigations through advanced DInSAR techniques: The Ivancich case study, Assisi, Italy

We extensively exploit advanced Differential SAR Interferometry (DInSAR) techniques for enhanced landslide investigations. We focus on the Ivancich area, Assisi, Central Italy, which is affected by a deep-seated landslide investigated through in-situ surveys. For this area, large data sets of SAR acquisitions were collected by the C-band ERS-1/2 and ENVISAT sensors (from April 1992 to November 2010), and by the X-band radars of the COSMO-SkyMed (CSK) constellation (from December 2009 to February 2012). We concentrate on the advanced DInSAR technique referred to as Small BAseline Subset (SBAS) approach, benefiting of its capability to generate deformation time series at full spatial resolution and from multi-sensor SAR data. This allows us to present one of the first examples for a landslide area of ERS-1/2 — ENVISAT deformation time series exceeding 18 years. The results allowed characterizing the long-term behaviour of the landslide, and identifying sectors of the unstable slope affected by different deformation dynamics. Analysis of the CSK data set, characterized by a reduced revisit time and improved spatial resolution, resulted in a 15-time larger point density with respect to the ERS-ENVISAT measurements, allowing to investigate nearly all the buildings (and, in many cases, portions of buildings) in the landslide area. Lastly, we present an innovative modelling approach based on the effective integration of the DInSAR measurements with traditional geological and geotechnical information, providing deeper insights on the kinematical evolution of the landslide. We consider our analysis a prototype example that can be extended to different geological and geotechnical conditions, providing significant advances in the understanding of ground deformations induced by active landslides.

MONITORING AND ANALYSIS OF LANDSLIDE HAZARD USING DINSAR TECHNIQUE APPLIED TO ALOS PALSAR IMAGERY: A CASE STUDY IN KAYANGAN CATCHMENT AREA, YOGYAKARTA, INDONESIA

The differential synthetic aperture radar interferometry (DInSAR) technique is applied to the ALOS PALSAR data to observe surface displacement in Kayangan Catchment area, Yogyakarta, Indonesia. Change detection is implemented to extract information on several landslides that occurred in the region in a time span between 2007 and 2009. The advanced DInSAR processing of images (2007–2009) has shown slight surface movements before the landslide events. These results are compared and validated with available GPS measurements. Our analysis reveals that Kayangan catchment area exhibits clear indication of surface displacements varying from 5.2 to 57.9 cm/year. The occurence of landslides has been analyzed in relation to the following terrain parameters; elevation, slope, distance to stream network, geology, landuse, and distance from road. Among these factors, it is found that 18% of landslides occur in elevation &gt;100 m, 56% in slope 300-400, 34% in