Monitoring subway construction using Sentinel-1 data: a case study in Bucharest,Romania

ABSTRACT

In Bucharest, new subway tunnels are under construction since 2011. The whole project of extending Bucharest underground infrastructure is due to be finished by 2030. The M-5 artery has been under construction since 2011 and ongoing. In December 2015, dewatering procedures in one of the metro stations caused serious damage to the surface infrastructure above, which subsided and partially collapsed in some locations. This paper relies on multi-temporal interferometry techniques to characterize displacement patterns of the ground surface above M-5 beltway between 2014 and 2018, and presents the capacity of Sentinel-1 satellite imagery to detect potential hazards in urban environments. Two stacks of Synthetic Aperture Radar (SAR) images acquired between October 2014 and October 2018 by the Sentinel-1 A and B satellites on ascending and descending orbits have been processed using the Delft Persistent Scatterer Interferometry algorithm (DePSI). The results indicate atypical acceleration in velocities starting in November 2015, prior to the described events, and manifesting until April 2016, when the ground was completely stabilized. The displacement trends and velocity values in the area of the Eroilor underground station were successfully validated using the ground-based Global Navigation Satellite Systems (GNSS) technique.     

Using C/X-band SAR interferometry and GNSS measurements for the Assisi landslide analysis

This work presents an analysis of the applicability of synthetic aperture radar (SAR) interferometry to landslide monitoring. This analysis was carried out by using different interferometric approaches, different spaceborne SAR data (both in the C-band and in the X-band), and in situ global navigation satellite system (GNSS) measurements. In particular, we investigated both the reliability of displacement monitoring and the issues of the cross-comparison and validation of the interferometric synthetic aperture radar (InSAR) results. The work was focused on the slow-moving landslide that affects a relevant part of the urban area of the historical town of Assisi (Italy).

A C-band ENVISAT advanced synthetic aperture radar (ENVISAT ASAR) dataset acquired between 2003 and 2010 was processed by using two different interferometric techniques, to allow cross-comparison of the obtained displacement maps. Good correspondence between the results was found, and a deeper analysis of the movement field was possible. Results were further compared to a set of GNSS measurements with a 7 year overlap with SAR data. A comparison was made for each GNSS marker with the surrounding SAR scatterers, trying to take into account local topological effects, when possible.

Further, the high-resolution X-band acquired on both ascending and descending tracks by the COSMO-SkyMed (CSK) constellation was processed. The resultant displacement fields show good agreement with C-band and GNSS measurements and a sensible increase in the density of measurements.     

Integrated space geodesy for mapping land deformation over Choushui River Fluvial Plain,Taiwan

Groundwater is an important part of the precious water resources. As the fresh surface water resources become scarcer because of climate change, population growth, and industrial activities, more and more groundwater has been extracted to meet the demands of various water uses (e.g. municipal, industrial, and agricultural). Excessive groundwater extraction leads to severe ground subsidence which compromises the safety of surface and underground infrastructures. Modelling the effects of groundwater extraction is vital to the management and sustainable use of groundwater. However, results of such modelling have to be validated with inputs such as the field survey of ground subsidence. Levelling and continuous global positioning system (GPS) receiver networks are routinely used to collect these field measurements. Unfortunately, these techniques have limitations in terms of areal coverage and density of survey marks and, as a result, subsidence hot spots can be easily missed out. In order to provide a comprehensive picture of subsidence to aid geotechnical modelling and to assess the effectiveness of measures used to mitigate ground subsidence, satellite imaging radar interferometry techniques (interferometric synthetic aperture radar (InSAR) can be used to complement other deformation monitoring techniques. In this study, 20 Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) images acquired from 31 December 2006 to 26 February 2011 were used to map the land displacement over the Choushui River Fluvial Plain (CRFP), Taiwan. The GPS measurements acquired at 10 continuously operating reference stations (CORS) were used to refine the orbit error in the each differential interferogram obtained from each radar image pair. The displacement time series over the distributed scatterers and the persistent scatterers were analysed. Several subsidence bowls were identified in CRFP. A quantitative comparison was conducted to compare the radar measurements to the GPS measurements over 36 GPS CORS stations. Good agreement between both measurements was observed with coefficient of determination (R²) of 0.97, absolute mean difference of 3.2 mm year^?1, and standard deviation of 4 mm year^?1. The InSAR-measured Line-of-Sight displacement and GPS-measured horizontal displacement were integrated to derive the vertical displacement map. Two displacement maps were generated using two ALOS-2 PALSAR-2 pairs acquired between 2015 and 2016. Similar subsidence patterns were found in the two maps compared to the 2006–2011 displacement rate map, suggesting the land over the same region might have continued to fall.     

干涉雷达永久散射体识别方法的对比分析

基于永久散射体的干涉测量技术可以克服卫星合成孔径雷达应用于区域地表形变探测所面临的时空失相关和大气影响.永久散射体的有效识别是干涉系统中的一个关键环节.本文对永久散射体的两种识别方法, 即相关系数阈值法和振幅离差指数阈值法进行了理论上的分析和实验上的对比.以上海市局部地区作为研究对象, 采用26幅欧洲空间局的ERS-1/2卫星C波段SAR影像为源数据, 使用两种识别方法分别进行了永久散射体的提取, 结果表明, 振幅离差指数方法具有更为稳健的抗噪能力.     

Post-launch analysis,calibration, and validation of CCD line of sight for a space-borne push-broom electro-optical sensor using a global image data set

This article describes a technique which estimates line-of-sight (LOS) parameters of each CCD array in a high-resolution electro-optical sensor on board a satellite using statistical information which is extracted automatically from a large number of real images acquired after launch. First, the focal length of panchromatic (PAN) CCD arrays is estimated by using thousands of ground control points (GCPs) converted to raw image space. Second, a model is introduced for deriving LOS parameters for multispectral (MS) CCD arrays in one focal plane assembly (FPA) such as the focal lengths and the first/last detector cell positions from automatically matched band-to-band (B2B) tie-points. Finally, the LOS parameters of all arrays in one FPA are updated using automatically matched tie-points in the overlap zone (OZ) in order to represent the geometrical relationship between the CCD arrays with the same spectral band in two FPAs. The proposed technique was applied to the calibration of a ground segment image processor for a currently operating high-resolution imaging satellite during its initial commissioning phase. This article describes the accuracy and robustness of the LOS parameters estimated by the proposed technique by using more than one hundred images covering full geographical locations and off-nadir tilt angle ranges.     

GNSS-based SAR for urban area imaging: topology optimization and experimental confirmation

Synthetic aperture radar (SAR), which uses the global navigation satellite system (GNSS) satellites as transmitters (GNSS-based SAR), consists of the GNSS transmitter in orbit and reception equipment near the ground. GNSS-based SAR has widespread applications in the remote sensing domain, including urban area imaging, because of its low cost and ease of deployment. However, due to the limited power and bandwidth of a GNSS transmitter, the area of the acquired image is very small (with a typical value less than 1 km²). This study proposed a new multistatic SAR concept with GNSS transmitters and multiple receiving antennas to achieve the 360° coverage and the potential of larger urban area image acquisition. The system design and architecture theory, including the resolution analysis and topology optimization, were established in detail. A multi-angle imaging experiment based on BeiDou-2 navigation satellites was designed to validate the proposed concept and theory, and the experimental results demonstrated the effectiveness of the proposed concept and theory.     

Joint approach using satellite techniques for slope instability detection and monitoring

A joint approach using satellite techniques was applied to two different regions (Sellas and Chalkeio villages) of Peloponissos (Greece) in order to detect and monitor slope instability. In the context of the research effort, a GPS campaign network, along with one permanent GPS station and a corner reflector (CR) network, was established at each region. From the two GPS campaigns that were carried out, ground displacements in the north and east components for Sellas region reached a magnitude of 9 and 8 mm, respectively, whereas for Chalkeio they were of the order of 1 cm and 8 mm, respectively. These results, however, are still preliminary and need validation from additional GPS campaigns that are planned to be carried out in future. The temporal resolution provided by the position time series of the permanent GPS stations highlighted the main features of both instability phenomena, that is, sensitivity at both horizontal components of motion for the Sellas region and slow linear trends for the Chalkeio region. The achieved precision of the daily solutions for both permanent GPS stations was found to be 1–3 mm for the horizontal components and 5–8 mm for the vertical components. Regarding the preliminary study of differential synthetic aperture radar (SAR) interferometry (DInSAR) in CR network, each reflector has been identified in SAR imagery, but at present the volume of SAR acquisitions is not adequate for providing safe deformation and error estimations. On the other hand, the permanent scatterers interferometry and small baselines subset (SBAS) techniques revealed a discontinuity in retrospective deformation rate along the observed rupture of Chalkeio village of almost 6 mm year^?1.     

Application of special-purpose artificial neural networks for speckle reduction in SAR images

Synthetic aperture radar (SAR) is used extensively for remote-sensing applications due to its ability to operate under all weather conditions and provide high-resolution images. However, high-resolution images constructed from SAR data often suffer from speckle, which makes identification and classification of edges/boundaries a difficult task. Speckle noise is multiplicative in nature and is a result of constructive and destructive interference of signals from randomly distributed scatterers in a resolution cell illuminated by a coherent signal. Usually, speckle is reduced by incoherent averaging of high-resolution image pixels that degrade resolution. The principal goal in all speckle-reduction algorithms is to reduce speckle with minimum loss of resolution. In this investigation, we used specially trained and validated artificial neural networks (ANNs) for speckle reduction in images generated with a radar-depth sounder/imager and compared their performance to the conventional adaptive filtering and Speckle Reducing Anisotropic Diffusion (SRAD) algorithm. We show that by training different ANNs to reduce speckle noise at different levels of signal-to-noise ratio (SNR), rather than training one ANN to operate at all levels of SNR, improved performance in speckle reduction can be obtained. Real SAR images and synthetic noise are used in this research to compare the performance of the proposed ANN-based approaches with that obtained from conventional methods. This investigation shows that on combining the results from a set of properly trained and validated neural networks, the SNRs of the output images improve beyond those obtained from conventional approaches when the input SNRs are greater than or equal to 4 dB. For input SNRs greater than 0 dB, however, the ANNs provide better performance in edge preservation compared with conventional methods. We also found that once a set of ANNs is properly trained to reduce speckle from an image, these ANNs can be used in de-speckling other images without any further training. The merits and demerits of different configurations of the ANNs are studied to find useful speckle noise-tolerant ANN architectures.     

PSI technique for analysing slow landslides: a useful tool to handle with care

Persistent scatterers interferometry (PSI) based on the analysis of satellite synthetic aperture radar (SAR) data in the field of landslide mapping is becoming a widespread tool, commonly used together with traditional geomorphological survey techniques and other monitoring instruments. Having acquired permanent scatterers interferometry SAR (PSInSAR?) data since 2005, the Region of Liguria has in recent years carried out several operational tests to define the correct procedures to provide appropriate interpretations of PSI data sets with respect to landslide mapping and state of activity definition. These experiences have resulted in the elaboration of a semi-automatic procedure using spatial analysis tools provided by any commercial geographic information system (GIS) software to allow a quick overview of huge data and obtain indications of potentially unstable areas. An analysis of the results shows a good general congruity between the potentially unstable areas detected and landslide inventory maps, but also some anomalies.     

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.     

高分辨率极化合成孔径雷达成像研究进展

合成孔径雷达（Synthetic aperture radar,SAR）是一种有效的地球遥感技术,对观测区域进行全天时、全天候的高分辨率大范围成像,在军事侦察、环境监测和地质测绘等领域有着十分广泛的应用。随着雷达技术和地球科学的发展,人们期望能够获取更多的目标特性,传统的单极化SAR已经难以满足越来越多元化的实际应用需求。极化合成孔径雷达（Polarimetric synthetic aperture radar,PolSAR）基于多个极化通道获取目标不同极化状态下的散射特性丰富了SAR图像的信息量,拓展了SAR的应用领域。从极化数据中准确地解译目标的物理特性是PolSAR应用的重要前提。本文对PolSAR的研究进展进行了总结,重点介绍了极化目标分解算法,给出了高分辨率PolSAR实测数据处理结果,并对未来研究方向进行了展望。     

Coastline extraction from SAR images using spatial fuzzy clustering and the active contour method

Coastline extraction from synthetic aperture radar (SAR) data is difficult because of the presence of speckle noise and strong signal returns from the wind-roughened and wave-modulated sea surface. High resolution and weather change independent of SAR data lead to better monitoring of coastal sea. Therefore, SAR coastline extraction has taken up much interest. The active contour method is an efficient algorithm for the edge detection task; however, applying this method to high-resolution images is time-consuming. The current article presents an efficient approach to extracting coastlines from high-resolution SAR images. First, fuzzy clustering with spatial constraints is applied to the input SAR image. This clustering method is robust for noise and shows good performance with noisy images. Next, binarization is carried out using Otsu’s method on the fuzzification results. Third, morphological filters are used on the binary image to eliminate spurious segments after binarization. To extract the coastline, an active contour level set method is used on the initial contours and is applied to the input SAR image to refine the segmentation. Because the proposed approach is based on an active contour model, it does not require preprocessing for SAR speckle reduction. Another advantage of the proposed method is the ability to extract the coastline at full resolution of the input SAR image without degrading the resolution. The proposed approach does not require manual initialization for the level set method and the proposed initialization speeds up the level set evolution. Experimental results on low- and high-resolution SAR images showed good performance for coastline extraction. A criterion based on neighbourhood pixels for the coastline is proposed for the quantitative expression of the accuracy of the method.     

基于GA的SAR图像中主干道路提取

从高分辨率合成孔径雷达(SAR)图像中提取道路及其他线性特征已成为目前遥感图像信息提取研究的热点。由于高分辨率SAR图像中，目标背景复杂，同时由于受相干斑噪声的影响，因此很难直接从原始图像数据中提取道路特征。为了能够从背景复杂，受斑点噪声干扰的高分辨率SAR图像中准确提取道路，提出了一种利用遗传算法提取主干道路的方法。该方法利用模糊C均值聚类法对滤波后的SAR图像进行无监督聚类，首先将图像分为林地、建筑物、道路等基本类，并将道路类像素从图像中分离出来，使问题得到简化；然后根据道路类像素的隶属度和道路像素灰度值的均匀特性来建立具体的道路模型；最后利用遗传算法搜索全局最优道路。实验结果表明，该方法可以很好地从SAR图像中提取各种主干道路。     

Persistent Scatterers Interferometry Hotspot and Cluster Analysis (PSI-HCA) for detection of extremely slow-moving landslides

The synthetic aperture radar (SAR) interferometry (InSAR) technique has already shown its importance in landslide mapping and monitoring applications. However, the usefulness of traditional differential InSAR applications is limited by disturbing factors such as temporal decorrelation and atmospheric disturbances. The Persistent Scatterers Interferometry (PSI) technique is a recently developed InSAR approach. It generates stable radar benchmarks (namely persistent scatterers, PSI point targets) using a multi-interferogram analysis of SAR images. The PSI technique has the advantage of reducing temporal decorrelation and atmospheric artefacts. The PSI technique is suitable for the investigation of extremely slow-moving landslides due to its capability to detect ground displacements with millimetre precision. However, the interpretation of PSI outputs is sometimes difficult for the large number of possible persistent scatterers (PSs). A new approach of PSI Hotspot and Cluster Analysis (PSI-HCA) is introduced here in order to develop a procedure for mapping landslides efficiently and automatically. This analysis has been performed on PSs in hilly and mountainous areas within the Arno river basin (Italy). The aim is to use PSs processed from 4 years (2003–2006) of Radarsat images for identifying areas preferentially affected by extremely slow-moving landslides. The Getis–Ord G_i *?statistic is applied in the study for the PSI-HCA approach. The velocity of PSs is used as weighting factor and the G_i *?index is calculated for each single point target. The results indicate that both high positive and low negative G_i *?values imply the clustering of potential mass movements. High positive values suggest the moving direction towards the sensor along the satellite line-of-sight (LOS), whereas low negative values imply the movement away from the sensor. Furthermore, the kernel function is used to estimate PS density based on these derived G_i *?values. The output is a hotspot map which highlights active mass movements. This spatial statistic approach of PSI-HCA is considered an effective way to extract useful information from PSs at a regional scale, thus providing an innovative approach for rapid mapping of extremely slow-moving landslides over large areas.     

Application of a new algorithm using Doppler information to retrieve complex wind fields over the Black Sea from ENVISAT SAR images

Several algorithms have been proposed to retrieve near-surface wind fields from C-band synthetic aperture radar (SAR) images acquired over the ocean. They mainly differ in the way they retrieve the wind direction. Conventionally, the wind direction is taken from atmospheric models or is extracted from the linear features sometimes visible in SAR images. Recently, a new wind retrieval algorithm has been proposed, which also includes the Doppler shift induced by motions of the sea surface. In this article, we apply three wind retrieval algorithms, including the one using Doppler information, to three complex wind events encountered over the Black Sea and compare the SAR-derived wind fields with model wind fields calculated using the high-resolution weather research and forecasting (WRF) model. It is shown that the new algorithm is very efficient in resolving the 180° ambiguity in the wind direction, which is often a problem in the streak-based wind retrieval algorithms. However, the Doppler-based algorithm only yields good results for wind directions that have a significant component in the look direction of the SAR antenna. Furthermore, it is dependent on good separation of the contributions to the Doppler shift induced by surface currents and wind-related effects (wind drift and wind-sea components of the ocean wave spectrum). We conclude that an optimum wind retrieval algorithm should consist of a combination of the algorithms based on linear features and Doppler information.     

Sea state in the Baltic Sea from space-borne high-resolution synthetic aperture radar imagery

In this work, remote sensing synthetic aperture radar (SAR) data from X-band TerraSAR-X and TanDEM-X (TS-X and TD-X) satellites have been used to adopt the algorithms for estimating sea state parameters in the specific condition of the Baltic Sea with archipelago islands and where short steep sea state dominates. Since the moving targets can be defocused and shifted in SAR images, sea state consisting of short windsea waves with strong local orbital velocities and wave breaking needs additional effort for accurate estimation of the total significant wave height that consists of swell and windsea parts. The XWAVE_C algorithm, developed for the North Sea, where the long swell waves coming from the Atlantic Ocean are present during storms, was further enhanced for the short steep windsea which dominates under ordinary storm conditions in the Baltics. For the empirical XWAVE_C model function, based on the spectral analysis of subscenes as well as on local wind information, an additional term was incorporated for assessment the minimal windsea significant wave height by applying JONSWAP wave spectra. A term to compensate spectral distortions triggered by windsea waves moving in SAR flight direction has also been introduced. In total, 95 TS-X/TD-X StripMap scenes between 2012 and 2017 were acquired in Eastern Baltic Sea, processed and analysed. The wave height results from SAR images were compared with collocated in situ data from 11 available buoys. The analysed data include both high and low windsea conditions. The comparison of SAR-derived wave heights with measured wave heights shows high agreement with a correlation coefficient r of 0.88. The wind speed, estimated from SAR images, was compared to measurements from 14 collocated in situ stations, yielding a high agreement with an r value of 0.90. This article is focused on the algorithm developments; however, it is also the first study of sea state retrieval in the Baltic Sea using high-resolution satellite-based techniques. The results show the local variability in the wave fields connected to atmospheric features. The observed local wave height can increase by 1–2 m in kilometre-size cells that are accompanied by wind gusts. The developed algorithms are installed in the German Aerospace Center’s (DLR) ground station Neustrelitz and can also be used in near-real-time.     

An approach for accurately retrieving the vertical deformation component from two-track InSAR measurements

As is well known, both conventional differential synthetic aperture radar interferometry (D-InSAR) and multi-temporal synthetic aperture radar interferometry (MT-InSAR) have a common limitation that they only can measure the deformation component along the radar line of sight (LOS) direction. However, in the majority of disaster investigations, there is more interest in the vertical deformation component than that of the horizontal direction, for example, in measuring ground subsidence in urban areas, or ground subsidence due to underground mining. To estimate the vertical deformation component accurately, it is in theory necessary to create at least three independent equations, and solve the vertical, the North–South, and the East–West deformation components by exploiting at least three-track InSAR LOS measurements or combining at least two-track InSAR LOS measurements with azimuth measurements. However, these methods are greatly limited and sometimes not even practical because there is typically little chance of obtaining a three-track SAR data set covering the same area in the same time span, and the accuracy of the azimuth measurements is far lower than that of InSAR LOS measurements. In this article, we found that it is possible to solve for the vertical deformation component from two-track InSAR LOS measurements in some circumstances. Then, an approach for accurately retrieving the vertical deformation component from two-track InSAR LOS measurements is proposed, and the analytical expression is presented. The approach is illustrated through an investigation of the ground subsidence in an area of Beijing, China. Unlike previous methods, this approach can accurately retrieve the vertical deformation component from two-track InSAR LOS measurements, and provide more reliable results for improving the interpretation of ground subsidence phenomena.     

A method for the registration of multiview range images acquired in forest areas using a terrestrial laser scanner

Terrestrial laser scanning can provide high-resolution, three-dimensional (3D) surveys of forest canopy surfaces. Applications that aim to build 3D forest scenes or to make plot-level or canopy-level assessments may ultimately require co-registration of range images from multiple viewpoints. Numerous challenges are reported in the co-registration of range images. A method for the registration of multiview range images acquired in forest areas using an inclinometer together with the positions of tree trunks and ground surface information is proposed in this study. Two of the six transformation parameters needed for co-registration were measured by an inclinometer. Another three transformation parameters were determined using the central positions of corresponding trunks in the two range images being registered. The last transformation parameter was determined by the fitness of ground surfaces in the two range images. A vertical filtering method is proposed for the extraction of trunk points. Similar triangles composed of trunks in the two range images were used to find corresponding trunks. Since the overlap of range images acquired at a station and that between stations was different, the registration process was divided into two stages. The range images acquired by prone scanners were first matched with the one acquired by a standing scanner at the same station. Then the range images acquired by standing scanners were used for the registration between stations. The results in our test site showed that an average registration accuracy of 0.74 cm with standard deviation (SD) of 0.23 cm within each station and an average accuracy of 3.0 cm with SD of 1.5 cm between stations were achieved.     

Simulation of SAR images of urban areas by using the ray tracing method with measured values of backscatter coefficients

This study uses the ray tracing method to simulate synthetic aperture radar (SAR) images of urban areas. The images are constructed for polarisations: horizontal-horizontal (HH) and vertical-vertical (VV), and different types of buildings, vegetation, and streets. Simulated images of a given area are compared with real SAR images of the same area acquired by the TerraSAR-X satellite. The simulations use the measured backscatter coefficient for HH and VV polarisations and for five different classes of terrain: houses, trees, shrubs, grass, and ground. For multiple reflections, we apply the generalized bistatic Lambertian model. The results show that, despite the limits of the ray tracing method and the approximations involved in modelling three-dimensional objects in the simulated scene, the simulated SAR images correspond well with the actual scene. All features present in the real image are reproduced in the simulated image; in particular, the double reflections of buildings and the surrounding ground appear clearly. However, discrepancies exist, and these are also discussed.     

Combination of stereo SAR and InSAR for DEM generation using TanDEM-X spotlight data

The objective of this work is to generate accurate digital elevation models (DEMs) from synthetic aperture radar (SAR) interferograms using the spotlight and staring spotlight modes during the TanDEM-X (TDX) science phase. We use stereo SAR with TDX or TerraSAR-X (TSX) to estimate absolute heights of natural or man-made reflectors for input to the unwrapped interferograms. The accuracy of the absolute heights in the DEMs was a few decimetres in flat regions and a few metres in the hilly and rugged terrain.