TerraSAR-X Stripmap Research Articles

Sub-Nyquist SAR Imaging and Error Correction Via an Optimization-Based Algorithm.

Sub-Nyquist synthetic aperture radar (SAR) based on pseudo-random time-space modulation has been proposed to increase the swath width while preserving the azimuthal resolution. Due to the sub-Nyquist sampling, the scene can be recovered by an optimization-based algorithm. However, these methods suffer from some issues, e.g., manually tuning difficulty and the pre-definition of optimization parameters, and a low signal-noise ratio (SNR) resistance. To address these issues, a reweighted optimization algorithm, named pseudo-ℒ0-norm optimization algorithm, is proposed for the sub-Nyquist SAR system in this paper. A modified regularization model is first built by applying the scene prior information to nearly acquire the number of nonzero elements based on Bayesian estimation, and then this model is solved by the Cauchy-Newton method. Additionally, an error correction method combined with our proposed pseudo-ℒ0-norm optimization algorithm is also present to eliminate defocusing in the motion-induced model. Finally, experiments with simulated signals and strip-map TerraSAR-X images are carried out to demonstrate the effectiveness and superiority of our proposed algorithm.

BUILDING RECONSTRUCTION BASED ON A SMALL NUMBER OF TRACKS USING NONPARAMETRIC SAR TOMOGRAPHIC METHODS

Abstract. Nowadays, the synthetic aperture radar (SAR) tomography (TomoSAR) technique plays a notable role in the 3D reconstruction of urban buildings through several SAR acquisitions with slightly different positions. Nonparametric-based TomoSAR spectral estimation algorithms usually work well when a large number of SAR observations. In this study, with a limited number of SAR images, we have assessed the efficiency of the nonparametric spectral estimation methods, including maximum entropy (ME), singular value decomposition (SVD), linear prediction (LP), Capon, minimum norm (MN), and beamforming (BF) in the reconstruction of the third dimension of urban buildings. The experiments are conducted on both simulated and TerraSAR-X stripmap images to indicate the effectiveness of the LP proposed estimation algorithm. The analysis of the results proves that by minimizing the average output signal power over the antenna array elements, the LP spectral estimation achieves the discrimination of distinct scatterers inside an image pixel. In addition, this low computational estimator improves the sidelobe suppression and the height estimates of the scatterers in the complex multiple-scattering urban environment. Compared to SVD, maximum entropy, Capon, minimum norm, and beamforming, the height of the Eskan tower in Tehran, Iran, obtained with the LP technique, is considerably near to field-based measurement.

Building profile reconstruction based on double subspace TomoSAR

ABSTRACT Synthetic aperture radar (SAR) tomography (TomoSAR) is an attractive technology for the three-dimensional (3D) reconstruction of buildings through multiple coherent SAR images. This technique can overcome the limitations of interferometry in multi-scatterer resolution and play a significant role in the analysis of urban areas. The robustness of the many advanced nonparametric spectral estimation approaches is founded on a high number of observations. In this work, we evaluate the abilities of five nonparametric spectral estimation methods, including double subspace (DS), maximum entropy (ME), minimum norm (MN), Capon, and beamforming (BF), to separate scattering contributions with a small number of SAR images in the tomographic reconstruction of urban environments. DS is a high-resolution estimator based on the existence of non-uniform noise, which assesses the noise subspace via eigendecomposition of some appropriately designed matrix without comprehending the noise covariance matrix. The study results indicate that DS can distinguish the scatterers in one azimuth-range resolution and satisfactorily dissuade the appearance of unpleasant side lobes. To investigate the effectiveness of DS and compare that with other expressed methods, both simulated and real SAR datasets were acquired from TerraSAR-X strip-map images of the city of Tehran, Iran. The experimental results on real SAR images demonstrate that the DS can remarkably enhance building reconstruction in the urban environment. The estimated height of the scatters utilizing the DS technique is similar to the data obtained from ground observations.

Multiparametric sea state fields from synthetic aperture radar for maritime situational awareness

This paper introduces a method for estimating a series of sea state parameters from satellite-borne synthetic aperture radar (SAR). The method was realized in a near real time (NRT) application which allows for the processing of data from different satellites and modes. The algorithm estimates the total significant wave height Hs, dominant and secondary swell and windsea wave heights, first, and second moment wave periods, the mean wave period and the period of wind sea. The algorithm was applied to the Sentinel-1 (S1) C-band Interferometric Wide Swath Mode (IW), Extra Wide (EW) and Wave Mode (WV) Level-1 (L1) products and also extended to X-band TerraSAR-X (TS-X) StripMap (SM) products. The scenes are processed in raster and result in continuous sea state fields, with the exception of S1 WV, where averaged values for sea state parameters for along-orbit imagettes of 20 km × 20 km are presented.The developed empirical algorithm consists of two parts: a first CWAVE_EX (extended CWAVE) part, based on a linear regression approach, and a subsequent machine learning part using the support vector machine (SVM) technique. A series of new data preparation steps (i.e. filtering, denoising) and new features estimated from SAR images are also introduced. The algorithm was tuned and validated using two independent global wave model hindcasts, WaveWatch-3 and MFWAM as well as National Data Buoy Center (NDBC) measurements. The achieved root mean squared errors (RMSE) for CWAVE_EX for the total Hs are 0.60 m for low-resolution modes S1 IW (10 m pixel) and EW (40 m pixel) and 0.35 m for S1 WV and TS-X SM (pixel spacing ca.1–4 m) in comparison to model predictions. The RMSEs of the retrieved wave periods are in the range of 0.45–0.90 s for all of the satellites and models considered. Similarly, the dominant and secondary swell, and wind sea wave height RMSEs are in the range of 0.35–0.80 m. The SVM postprocessing improves the accuracy of the initial results of CWAVE_EX for Hs and reaches an RMSE of 0.25 m for S1 WV. Comparisons to 64 NDBC buoys, collocated at distances shorter than 50 km to S1 WV imagettes worldwide, result in an RMSE of 0.41 m. All results and the methods presented are novel in terms of the accuracy achieved, combining the classical approach with machine learning techniques, and performing an automatic NRT processing of multiparametric sea state fields from L1 data with automatic switching for different satellites and modes.The complete archive of S1 WV L1 Single Look Complex products from December 2014 until February 2021 was processed to create a sea state parameter database and validated using model hindcast and buoy measurements. The derived parameters are available to the public within the scope of the European Space Agency's Climate Change Initiative.

Beijing Land Subsidence Revealed Using PS-InSAR with Long Time Series TerraSAR-X SAR Data

Beijing is a major city suffering from land subsidence due to long-term over-exploitation of groundwater. The South-to-North Water Diversion Project (SNWDP), however, has had a significant impact on the structure of water consumption since the end of 2014, and it is changing the status of land subsidence in Beijing. In this study, we employed Persistent Scatterers Synthetic Aperture Radar Interferometric (PS-InSAR) to investigate the decadal evolution of land subsidence in Beijing with 100 TerraSAR-X stripmap images collected from April 2010 to December 2019. The water resources, historic climate and urban construction data were compiled for the years of 2010 to 2019 to analyze changes in groundwater level, human activity, surface geology, active faults and land subsidence patterns. The results show that the changes in the water supply structure are correlated to a rise in groundwater level after 2015. These changes include an increase in the water supply from the SNWDP, a reduction in groundwater exploitation, the optimization of water consumption, replacing recycled water for environmental water and a reduction in the use of water for agriculture. Land subsidence in the study area was concentrated in the eastern regions, trending towards a decreasing velocity starting about two years after the commencement of SNWDP in 2015. Uneven subsidence in the land subsidence area was related to excavations of underground soil, and the construction of Line 6 and Line 7 led to rapid nonlinear subsidence. Our results have scientific significance for reducing subsidence hazards in the context of SNWDP and urban expansion.

The comparative study of three nonparametric methods of SAR tomography for building reconstruction

Over the past years, synthetic aperture radar (SAR) tomography (TomoSAR) has indicated significant potentials for three-dimensional (3D) reconstruction of buildings in urban areas. A large number of SAR images are thus required to perform tomographic inversions in non-parametric spectral estimators. To this end, in the case of a limited choice of SAR acquisitions, the present study aims to evaluate the capabilities of five non-parametric spectral estimation (SE) techniques, including linear prediction (LP), maximum entropy (ME), and minimum norm (MN), Capon, and beamforming (BF) in the tomographic reconstruction of urban environments. The performance analysis is carried out by using both simulated and real SAR datasets. The study results demonstrate that the proposed efficient LP estimator, minimizing the average output signal power over the antenna array elements, can separate the layover scatterers along the height direction. This low-computational SE method is thus able to clean side lobes while using a small number of observations. The proposed algorithms, as applied on TerraSAR-X strip-map images of the city of Tehran, Iran, verify the effectiveness of the non-parametric LP reconstruction technique for urban buildings. The estimated height of the scatterers also indicates that the LP estimator is similar to the field-based measurements once compared with ME, MN, Capon, and BF reconstruction methods.

Learning Convolutional Sparse Coding on Complex Domain for Interferometric Phase Restoration.

Interferometric phase restoration has been investigated for decades and most of the state-of-the-art methods have achieved promising performances for InSAR phase restoration. These methods generally follow the nonlocal filtering processing chain, aiming at circumventing the staircase effect and preserving the details of phase variations. In this article, we propose an alternative approach for InSAR phase restoration, that is, Complex Convolutional Sparse Coding (ComCSC) and its gradient regularized version. To the best of the authors' knowledge, this is the first time that we solve the InSAR phase restoration problem in a deconvolutional fashion. The proposed methods can not only suppress interferometric phase noise, but also avoid the staircase effect and preserve the details. Furthermore, they provide an insight into the elementary phase components for the interferometric phases. The experimental results on synthetic and realistic high- and medium-resolution data sets from TerraSAR-X StripMap and Sentinel-1 interferometric wide swath mode, respectively, show that our method outperforms those previous state-of-the-art methods based on nonlocal InSAR filters, particularly the state-of-the-art method: InSAR-BM3D. The source code of this article will be made publicly available for reproducible research inside the community.

Using TerraSAR X-Band and Sentinel-1 C-Band SAR Interferometry for Deformation Along Beijing-Tianjin Intercity Railway Analysis

The Beijing-Tianjin Intercity Railway (BTIR) is an important transportation hub connecting Beijing and Tianjin. It is the China's first high-speed railway reaching a speed of 350 km/h and has been in operation for ten years. Since the foundation of the BTIR is made up of soft and loose soil, hence suffers greatly from potential deformation. In order to investigate the impact of ground subsidence on the railway line, 26 TerraSAR-X SpotLight images, 23 TerraSAR-X StripMap images, and 31 Sentinel-1 Interferometric Wide images were processed to obtain the deformation of the Yizhuang areas along the BTIR from January 2015 to March 2017 by permanent scatterers interferometric synthetic aperture radar technology. The deformation results of these three datasets are self-consistent. Through the vertical and horizontal deformation of the railway using fusion of the railway deformation results from different line of sight direction, we found that the deformation of the railway line is mainly in the vertical direction. Furthermore, the high precision spatial-temporal evolution of the deformation along the BTIR is revealed. Finally, the advantages and limitations of different SAR resolution are analyzed and summarized.

Monitoring of tectonic movements of the Gediz Graben by the PSInSAR method and validation with GNSS results

In the eastern part of the Gediz Graben, especially in the Sarigol region, surface deformations that occurred without destructive earthquakes or that continue to occur are frequently observed from the 1969 Alasehir earthquake to the present. Especially in areas where aseismic and tectonic effects are thought to co-exist, such as the Gediz Graben, the general deformation character of the study area cannot be identified precisely from the surface deformations that are determined using the GNSS method as pointwise. However, the general deformation character of the study area can be identified clearly by determining the surface deformations of the study area with the PSInSAR method areally. In this study, in order to determine surface deformations that may be caused by aseismic and/or tectonic effects in the Gediz Graben areally, deformations in the direction of Line of Sight (LOS) were determined by using the persistent scatterer interferometric synthetic aperture radar (PSInSAR) method. In order to determine movements in the LOS direction, TERRASAR-X Stripmap satellite radar images of the German Aerospace Center (DLR) were used. According to the evaluations obtained from the PSInSAR results, it is understood that while there are subsidences in the graben area of the Gediz Graben, there are uplifts in the north and south of the graben. The subsidence values in the graben were obtained to be approximately − 50 mm/year. This result indicates that in addition to creep movement of tectonic origin in the study area, the local soil characteristics and/or seasonal groundwater changes may also increase deformation in areas where deformation occurs.

Snow avalanche detection and mapping in multitemporal and multiorbital radar images from TerraSAR-X and Sentinel-1

Abstract. Snow avalanches can endanger people and infrastructure, especially in densely populated mountainous regions. In Switzerland, the public is informed by an avalanche bulletin issued twice a day during winter which is based on weather information and snow and avalanche reports from a network of observers. During bad weather, however, information about avalanches that have occurred can be scarce or even be missing completely. To assess the potential of weather-independent radar satellites, we compared manual and automatic change detection avalanche mapping results from high-resolution TerraSAR-X (TSX) stripmap images and medium-resolution Sentinel-1 (S1) interferometric wide-swath images for a study site in central Switzerland. The TSX results were also compared to available mapping results from high-resolution SPOT-6 optical satellite images. We found that avalanche outlines from TSX and S1 agree well with each other. Cutoff thresholds of mapped avalanche areas were found with 500 m2 for TSX and 2000 m2 for S1. S1 provides a much higher spatial and temporal coverage and allows for mapping of the entire Alps at least every 6 d with freely available acquisitions. With costly SPOT-6 images the Alps can even be covered in a single day at meter resolution, at least for clear-sky conditions. For the SPOT-6 and TSX mapping results, we found a fair agreement, but the temporal information from radar change detection allows for a better separation of overlapping avalanches. Still, the total mapped avalanche area differed by at least a factor of 3 because with radar mainly the avalanche deposition zone was detected, whereas the release zone was very visible already in SPOT-6 data. With automatic avalanche mapping we detected around 70 % of manually mapped new avalanches, at least when the number of old avalanches is low. To further improve the radar mapping capabilities, we combined S1 images from multiple orbits and polarizations and obtained a notable enhancement of resolution and speckle reduction such that the obtained mapping results are almost comparable to the single-orbit TSX change detection results. In a multiorbital S1 mosaic covering all of Switzerland, we manually counted 7361 new avalanches which occurred during an extreme avalanche period around 4 January 2018.

In-Depth Verification of Sentinel-1 and TerraSAR-X Geolocation Accuracy Using the Australian Corner Reflector Array

This article shows how the array of corner reflectors (CRs) in Queensland, Australia, together with highly accurate geodetic synthetic aperture radar (SAR) techniques-also called imaging geodesy-can be used to measure the absolute and relative geometric fidelity of SAR missions. We describe, in detail, the end-to-end methodology and apply it to TerraSAR-X Stripmap (SM) and ScanSAR (SC) data and to Sentinel-1 interferometric wide swath (IW) data. Geometric distortions within images that are caused by commonly used SAR processor approximations are explained, and we show how to correct them during postprocessing. Our results, supported by the analysis of 140 images across the different SAR modes and using the 40 reflectors of the array, confirm our methodology and achieve the limits predicted by theory for both Sentinel-1 and TerraSAR-X. After our corrections, the Sentinel-1 residual errors are 6 cm in range and 26 cm in azimuth, including all error sources. The findings are confirmed by the mutual independent processing carried out at University of Zurich (UZH) and German Aerospace Center (DLR). This represents an improvement of the geolocation accuracy by approximately a factor of four in range and a factor of two in azimuth compared with the standard Sentinel-1 products. The TerraSAR-X results are even better. The achieved geolocation accuracy now approaches that of the global navigation satellite system (GNSS)-based survey of the CRs positions, which highlights the potential of the end-to-end SAR methodology for imaging geodesy.

Seasonal dynamics of a permafrost landscape, Adventdalen, Svalbard, investigated by InSAR

Nordenskiöld Land in Central Spitsbergen, Svalbard is characterized as a high latitude, high relief periglacial landscape with permafrost occurring both in mountains and lowlands. Freezing and thawing of the active layer causes seasonal frost heave and thaw subsidence, while permafrost-related mass-wasting processes induce downslope ground displacements on valley sides. Displacement rate varies spatially and temporally depending on environmental factors. In our study, we apply Satellite Synthetic Aperture Radar Interferometry (InSAR) to investigate the magnitude, spatial distribution and timing of seasonal ground displacements in and around Adventdalen using TerraSAR-X StripMap Mode (2009–2017) and Sentinel-1 Interferometric Wide Swath Mode (2015–2017) SAR images. First, we show that InSAR results from both sensors highlight consistent patterns and provide a comprehensive overview of the distribution of displacement rates. Secondly, two-dimensional (2D) TerraSAR-X InSAR results from combined ascending and descending geometries document the spatial variability of the vertical and east-west horizontal displacement rates for an average of nine thawing seasons. The remote sensing results are compared to a simplified geomorphological map enabling the identification of specific magnitudes and orientations of displacements for 14 selected geomorphological units. Finally, June to December 2017 6-day sampling interval Sentinel-1 time series was retrieved and compared to active layer ground temperatures from two boreholes. The timing of the subsidence and heave detected by InSAR matches the thawing and freeze-back periods measured by in-situ sensors. Our results highlight the value of InSAR to obtain landscape scale knowledge about the seasonal dynamics of complex periglacial environments.

Study of Digital Elevation Model (DEM) Extraction using Stereo Radargrammetry TerraSAR-X in Madiun Area – Elevation Accuracy Improvement

High resolution images data from Terrasar-X are used to extract digital elevation model (DEM) using stereo radargrammetry in the attempt to achieve better resolution of terrain surface in Indonesia. As sample in this study, stereo pairs images from TerraSAR-X StripMap mode (~3m resolution) on Madiun city is used with difference of incidence angle around ~18.88 degree to extract the elevation of the area. Furthermore, field observation on the selected area will be used on elevation accuracy assessment. The digital surface elevation (DSM) generated by stereo radargrammetry in this study shows us high resolution with spatial pixel spacing 5.57 meter and elevation accuracy around ~4 meter.

On the analysis of a time series of X–band TerraSAR–X SAR imagery over oil seepages

ABSTRACTA large time series of 42 dual–polarimetric co–polarized TerraSAR-X (TSX) StripMap Synthetic Aperture Radar (SAR) measurements are exploited to monitor a well-known oil seep area, i.e., the Taylor Energy site in the Gulf of Mexico. A comprehensive scattering analysis is undertaken to assess the impact of SAR imaging parameters (polarization, angle of incidence – AOI, noise floor) and environmental conditions (wind speed – WS, oil properties) on single-polarization SAR–based sea oil seep observation. The main goal of this study is to evaluate the reliability of the scattering–based information derived from the time series of TSX SAR imagery. A two-scale backscattering model is considered to give a physical framework that supports a better understanding of the effects of the above–mentioned factors.Experimental results showed that the high TSX noise floor significantly limits a reliable interpretation of the slick–free sea surface and oil seep backscattering at AOIs larger than 34 and 26, respectively, since they are contaminated by noise. Hence, it is shown that, at larger AOIs, the joint contribution of noisy SAR measurements and low oil backscattering does not result in a larger oil/sea separability. The latter is not remarkably influenced by polarization and WS, under low–to–moderate conditions. Experiments also demonstrate that, when reliable SAR measurements are available, sea oil seep backscattering is affected by the oil’s damping properties more than its concentration in the water column. The time variability of the polluted area is also estimated using the time series of TSX imagery and the obtained results agree with independent analysis undertaken on the same test site.

Spatiotemporal monitoring of surface motions using DInSAR techniques integrated with geological information: a case study of an iron mine in the Amazon region using TerraSAR-X and RADARSAT-2 data

Instabilities are extremely common in the iron open-pit mines located in the Carajas mineral province, the world´s largest iron reserves located in the Brazilian Amazon. Due to deep excavations in rock products of low geomechanical quality, heavy precipitation, and blasting practices, mining operations in the area present surface displacements that potentially lead to slope instabilities with several risks (personnel, equipment, mining infrastructure, etc.). This paper presents the results related to the N5E mine based on DInSAR Time Series (DTS) and Persistent Scatterer Interferometry (PSI) using a temporal series of 33 StripMap TerraSAR-X (SM TSX) images, and geological information provided from a 3D photointerpretation of an SM TSX and Ultra-Fine RADARSAT-2 (UF RST) stereo-pair, calibrated with field data. Measurement point (DTS, PSI) results were compared with in situ geodetic survey information (total station/prism measurements) and showed good agreement indicating that most of the mine can be considered stable during the period of the TSX coverage. The highest accumulated displacements were spatially related to a thematic unit mapped as a landfill. For other sectors of the mine, lower deformation rates were related to photointerpreted lineaments related to the Carajas fault system suggesting that geological structures can play a key role in controlling some surface displacements. The investigation demonstrated that the strategy based on the use of DTS and PSI techniques integrated with geological data provided a synoptic view of the deformation process that affected the mine. The approach was relevant for ground displacements monitoring of the study area with DInSAR results compared with in situ geodetic measurements showing good statistical correlation.

Radargrammetric approaches to the flat relief of the amazon coast using COSMO-SkyMed and TerraSAR-X datasets

The Amazonian coast consists of extensive flood plains and plateaus characterized by a high discharge of water and sediment from the Amazon River. This wide landscape occurs under a tropical climate with heavy rains and high cloud cover, making it unsuitable for conventional mapping based on optical images. Additionally, the flat relief and vegetation structure of the Brazilian Amazon coast define an incoherent to partially coherent behavior for the microwave signal, rendering radargrammetric models more suitable for the three-dimensional mapping of its surface. This study aimed to assess the digital surface models (DSMs) provided by Cosmo-SkyMed (CSK) and TerraSAR-X (TSX) Stripmap datasets throughout the radargrammetric models from SARscape and Toutin. The DSMs were generated from SAR (synthetic aperture radar) data with an acquisition geometry that addressed the need for a compromise between the intersection angles and low temporal decorrelation. The radargrammetric SARscape and Toutin’s models were developed from different amounts of stereo ground control points (SGCP). The generated DSMs were evaluated considering a set of 40 independent checkpoints (ICP) measured by GNSS in the field, in their entirety and disaggregated by coastal environment. The vertical accuracy was based on the estimation of the discrepancies, bias and precision (standard deviation and root mean square error – RMSE), and the Taylor and Target diagrams were used for a more comprehensive comparison. In the vertical accuracy analysis using all ICPs measured in situ, the DSM obtained by the SARscape’s model from the CSK SAR data resulted in the lowest RMSE (4.34 m) and mean discrepancy (0.05 m), but Toutin’s model had the lowest standard deviation (2.58 m) of the discrepancies. The Taylor and Target diagrams showed fluctuations in accuracy that alternated the DSMs generated from the two types of SAR data, indicating that TSX produced more stable models and CSK produced better vertical accuracy. The Amazon Coastal Plateau and Fluvial Marine Terrace environments defined three-dimensional representations with lower RMSEs (better than 7.8 and 8.9 m, respectively), regardless of the type of SAR data or the radargrammetric model used. The worst performance, which was for the Fluvial Marine Plain, was influenced by the specific characteristics of this coastal environment, such as the structure of the mangrove vegetation and the shoreline. In general, the high resolution and good ability to revisit the SAR data used, together with the radargrammetric models, allowed for the accurate mapping of the flat relief of the Amazon coastal environments, providing detailed spatial information that can be acquired in severe rainfall conditions in a region of intense morphological dynamics.

SAR tomography for point-like and volumetric scatterers using a regularised iterative adaptive approach

ABSTRACTSynthetic aperture radar (SAR) tomography has been shown to be an effective and important tool for the monitoring of infrastructures and the investigation of forest vertical structure. However, the existing tomographic imaging algorithms, including spectral estimation and compressive sensing, can only be applied to SAR dataset over urban areas or over vegetated areas, while providing superresolution capability and working on single-look interferometric data. In this study, we propose a tomographic processing algorithm for SAR tomography based on Tikhonov regularisation and iterative adaptive approach (IAA), referred to as RIAA. As a nonparametric spatial spectral estimation method, RIAA allows the application to scenarios with point-like scatterers as well as with volumetric scatterers. The proposed method also provides superresolution capability and works on single-look SAR images. The performance of the proposed algorithm is verified by simulated data, TerraSAR-X strip-map and BioSAR 2007 P-band datasets over the urban and forested areas, respectively.

Land Subsidence in Coastal Environments: Knowledge Advance in the Venice Coastland by TerraSAR-X PSI

The use of satellite SAR interferometric methods has significantly improved the monitoring of ground movements over the last decades, thus opening new possibilities for a more accurate interpretation of land subsidence and its driving mechanisms. TerraSAR-X has been extensively used to study land subsidence in the Venice Lagoon, Italy, with the aim of quantifying the natural and anthropogenic causes. In this paper, we review and update the main results achieved by three research projects supported by DLR AOs (German Aerospace Center Announcement of Opportunity) and conducted to test the capability of TerraSAR-X PSI (Persistent Scatterer Interferometry) to detect ground movements in the complex physiographic setting of the Venice transitional coastal environment. The investigations have been focused on the historical center of Venice, the lagoon inlets where the MoSE is under construction, salt marshes, and newly built-up areas in the littoral. PSI on stacks of stripmap TerraSAR-X images covering short- to long-time periods (i.e., the years 2008–2009, 2008–2011 and 2008–2013) has proven particularly effective to measure land subsidence in the Venice coastland. The very high spatial resolution (3 m) and the short repeat time interval (11 days) of the TerraSAR-X acquisitions make it possible to investigate ground movements with a detail unavailable in the past. The interferometric products, properly calibrated, allowed for a millimetric vertical accuracy of the land movements at both the regional and local scales, even for short-term analyses, i.e., spanning one year only. The new picture of the land movement resulted from processing TerraSAR-X images has significantly contributed to update the knowledge on the subsidence process at the Venice coast.

Where We Live—A Summary of the Achievements and Planned Evolution of the Global Urban Footprint

The TerraSAR-X (TSX) mission provides a distinguished collection of high resolution satellite images that shows great promise for a global monitoring of human settlements. Hence, the German Aerospace Center (DLR) has developed the Urban Footprint Processor (UFP) that represents an operational framework for the mapping of built-up areas based on a mass processing and analysis of TSX imagery. The UFP includes functionalities for data management, feature extraction, unsupervised classification, mosaicking, and post-editing. Based on >180.000 TSX StripMap scenes, the UFP was used in 2016 to derive a global map of human presence on Earth in a so far unique spatial resolution of 12 m per grid cell: the Global Urban Footprint (GUF). This work provides a comprehensive summary of the major achievements related to the Global Urban Footprint initiative, with dedicated sections focusing on aspects such as UFP methodology, basic product characteristics (specification, accuracy, global figures on urbanization derived from GUF), the user community, and the already initiated future roadmap of follow-on activities and products. The active community of >250 institutions already working with the GUF data documents the relevance and suitability of the GUF initiative and the underlying high-resolution SAR imagery with respect to the provision of key information on the human presence on earth and the global human settlements properties and patterns, respectively.

INVESTIGATION ON INSAR TIME SERIES DEFORMATION MODEL CONSIDERING RHEOLOGICAL PARAMETERS FOR SOFT CLAY SUBGRADE MONITORING

Abstract. The stability control is one of the major technical difficulties in the field of highway subgrade construction engineering. Building deformation model is a crucial step for InSAR time series deformation monitoring. Most of the InSAR deformation models for deformation monitoring are pure empirical mathematical models, without considering the physical mechanism of the monitored object. In this study, we take rheology into consideration, inducing rheological parameters into traditional InSAR deformation models. To assess the feasibility and accuracy for our new model, both simulation and real deformation data over Lungui highway (a typical highway built on soft clay subgrade in Guangdong province, China) are investigated with TerraSAR-X satellite imagery. In order to solve the unknows of the non-linear rheological model, three algorithms: Gauss-Newton (GN), Levenberg-Marquarat (LM), and Genetic Algorithm (GA), are utilized and compared to estimate the unknown parameters. Considering both the calculation efficiency and accuracy, GA is chosen as the final choice for the new model in our case study. Preliminary real data experiment is conducted with use of 17 TerraSAR-X Stripmap images (with a 3-m resolution). With the new deformation model and GA aforementioned, the unknown rheological parameters over all the high coherence points are obtained and the LOS deformation (the low-pass component) sequences are generated.