Layover Effects Research Articles

DIFFERENTIAL SAR TOMOGRAPHY OF LARGE-SCALE WATER CONSERVANCY PROJECTS UNDER STEEP TERRAIN – THE CASE STUDY OF LAXIWA HYDROPOWER STATION

Abstract. Differential SAR Tomography (D-TomoSAR), as an extension of InSAR technology, combines D-InSAR and TomoSAR technology to achieve imaging in the height-deformation rate (s-v) plane. It not only solves the layover problem of SAR imaging, but also obtains the height and deformation rate of each scatterer within the image element. The technique is currently mainly applied to complex scenes in urban areas where the layover problem is serious, and the layover effect also exists for hydropower plants with extremely steep slopes. In this paper, the Differential SAR Tomography technique is applied to the four-dimensional imaging of hydraulic engineering for the first time, taking the La Siwa hydropower station as an example. This experiment establishes the signal model based on permanent scatterer points, so interferometric processing and PS point selection should be performed to obtain the differential interferogram sequence and PS points in the region; the orthogonal matching pursuit (OMP) algorithm is selected for differential SAR tomography imaging processing to reconstruct the elevation-deformation rate backward scattering profile. The experiments use the 23-view TerraSAR-X satellite one-meter resolution time series image dataset for deformation monitoring of the Laxiwa hydropower dam in GuiDe County, Qinghai Province, China, and finally the resolution and reconstruction estimation performance are evaluated by theoretical analysis and application case study. A comparison with the traditional InSAR technique shows that the differential SAR tomography technique not only maintains the advantages of high resolution, but also significantly improves the probability of accurate reconstruction of scattered points, and achieves higher accuracy in estimating the deformation of hydropower dams. This paper mainly discusses the application of differential SAR tomography technology in water conservancy projects, hoping to provide reference and help for the future large-scale application of differential SAR tomography technology in hydroelectric dam deformation monitoring.

Interferometric synthetic aperture sonar large scale simulated data benchmark of a ship wreck

AbstractInterferometric synthetic aperture sonar (InSAS) systems produce high resolution seafloor imagery and 3‐D bathymetry by exploiting the phase differences between image pairs formed from data collected by vertically separated arrays. This process is non‐trivial due to the inherent ambiguity of interferometric phase estimates, and the effect of layover, where the response of multiple scatterers with different positions are mapped onto the same pixel during imaging. These effects are particularly problematic for complex scenes with strong bathymetry, such as ship wrecks. This is an unsolved problem and improved algorithms for InSAS bathymetry estimation are needed. However, developing and assessing such algorithms using data from fielded InSAS systems is difficult because of a lack of accurate ground truth for the platform motion and the true 3‐D shape of the scene. This paper presents an openly available synthetic data set as an alternative to field‐collected data for use by InSAS algorithm developers. The dataset is derived from a high‐resolution 3‐D photogrammetry scan of the SS Thistlegorm wreck. It was produced by a point‐based diffraction model using parameters similar to the Minehunting UUV for Shallow water Covert Littoral Expeditions (MUSCLE) InSAS.

Remote Monitoring of Ground Motion Hazards in High Mountain Terrain Using InSAR: A Case Study of the Lake Sarez Area, Tajikistan

High mountain terrains, with steep slopes and deep valleys, are generally challenging areas to monitor using satellite earth observation techniques since the terrain creates perspective distortions and differences in illumination that can occlude or obfuscate a significant proportion of the land. This is particularly prominent in synthetic aperture radar (SAR) data, where the oblique geometry can result in large areas of layover and shadow, which must be excluded from any analysis. Interferometric SAR (InSAR) is an established technique for monitoring ground motion and this study assesses its potential for geohazard monitoring in mountainous areas using Lake Sarez in Tajikistan as a case study, applying SAR data from the Sentinel-1 mission. It is shown that, although the effect of layover and shadow is severe, a judicious combination of ascending and descending satellite passes is still capable of surveying 88% of the land surface. It is also demonstrated that, through the use of an advanced InSAR technique (the APSIS™ Intermittent Small Baseline Subset technique), near-complete coverage of ground motion measurements is possible, despite intermittent snow cover. Moreover, this is achieved without the need for ground control, which can be hazardous to establish in such areas. It is concluded that a combination of satellite passes and advanced InSAR techniques greatly facilitates the remote monitoring of ground motion hazards in high mountain areas.

Integrating RELAX with PS-InSAR Technique to Improve Identification of Persistent Scatterers for Land Subsidence Monitoring

Identifying Persistent Scatterers (PSs) is one of the key processing steps of the Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique. The number, density, and reliability of identified PSs directly affect the monitoring accuracy of land subsidence, especially in higher density urban environments. As a result of the side-looking viewing geometry of SAR, the layover effect poses a major challenge to the PS identification. This research proposes joint modeling of the PS-InSAR technique and RELAX algorithm for SAR tomography (PS-InSAR+RELAX) to detect single and double scatterers and to improve the identification and reliability of PSs. It has been demonstrated that RELAX improves separation of the scatterers when compared to two other spectral analysis methods for SAR tomography, Beam-Forming (BF) and Singular Value Decomposition (SVD). RELAX exhibits the least noise when the number of baseline changes from 15 to 30, and it can separate the scatterers at a lower Normal-Slant-Range (NSR) height than the two other methods. As RELAX can better identify, separate, and then filter out layover scatterers, the number and density of PSs identified by PS-InSAR+RELAX is reduced and visually simplified, suggesting that the method can effectively reduce the influence of the layover effect on the PS identification. Also, the PSs identified by PS-InSAR+RELAX are more coherent than those identified by the traditional PS-InSAR technique. The proposed technique has been applied to Sentinel-1A data acquired from 2014 to 2016, to monitor land subsidence in the city of Beijing, China. When evaluated against the leveling measurements, PS-InSAR+RELAX performs better than the traditional PS-InSAR technique, with the correlation coefficients (r) of r = 0.98 and r = 0.95, respectively.

Impact of Ocean Waves on Guanlan’s IRA Measurement Error

The National Laboratory for Marine Science and Technology of China proposed the Guanlan ocean science satellite project in order to observe mesoscale and submesoscale ocean phenomena more effectively. In the project, the interferometric radar altimeter (IRA) is a main payload to be used to retrieve sea surface height (SSH) by means of interferometric imaging technology. Sea state is one of the important factors that affect the accuracy of the SSH that is retrieved by IRA. In the present work, the effects of velocity bunching and layover induced by sea waves are numerically simulated. The results demonstrate that the SSH would be significantly underestimated due to velocity bunching. On the other hand, the layover effect of sea waves along range direction would decrease (destroy) the coherence between the master-slave IRA images and then increase the random altimetry noise. Spatial smoothing is one of the main methods for reducing the residual error of sea waves. Here, we propose a theoretical formula to evaluate the residual error of sea waves for different wavelength, significant wave height and wave direction. The conclusions obtained in this work are helpful for better understanding the influence of sea state on the SSH retrieved by IRA.

Land subsidence monitoring based on PS-InSAR Persistent Scatterers identification with spectral analysis method

Abstract. Layover occurs as a consequence of the slant range scale distortion in Synthetic Aperture Radar (SAR) data and it is commonly observed in the images acquired over urban areas. There may be two or more Persistent Scatterers (PSs) in one pixel. Moreover, these PSs do not have amplitude stability and spatial coherence. The threshold method used in the Persistent Scatterer Interferometric (PSI) SAR technique cannot identify the PS with two scatterers in urban, the accuracy of urban land subsidence is reduced. To solve this problem, we used Fast Fourier Transform (FFT) convert PSs in frequency domain during PS identification process of PSI, by observing their characteristics in the frequency domain, the layover scatterers can be identified and separated. The results of simulation experiment show that by analyzing the peak distribution characteristics of PSs in the elevation direction under the relatively even space baseline, PSI with FFT can identify single scatterers and layover scatterers. After separating the layover scatterers, the reliability of PSs identification are improved. For the real data experiment, we use 31 Sentinel-1A IW images covering Beijing from 2014 to 2016 as data sources. The results show that the proposed method can effectively identify layover scatterers which cannot be identified by the threshold method in urban, reducing the effect of layover scatterers, improving the accuracy of urban land subsidence monitoring.

Fusion of SAR, Optical Imagery and Airborne LiDAR for Surface Water Detection

The detection and monitoring of surface water and its extent are critical for understanding floodwater hazards. Flooding and undermining caused by surface water flow can result in damage to critical infrastructure and changes in ecosystems. Along major transportation corridors, such as railways, even small bodies of water can pose significant hazards resulting in eroded or washed out tracks. In this study, heterogeneous data from synthetic aperture radar (SAR) satellite missions, optical satellite-based imagery and airborne light detection and ranging (LiDAR) were fused for surface water detection. Each dataset was independently classified for surface water and then fused classification models of the three datasets were created. A multi-level decision tree was developed to create an optimal water mask by minimizing the differences between models originating from single datasets. Results show a water classification uncertainty of 4–9% using the final fused models compared to 17–23% uncertainty using single polarization SAR. Of note is the use of a high resolution LiDAR digital elevation model (DEM) to remove shadow and layover effects in the SAR observations, which reduces overestimation of surface water with growing vegetation. Overall, the results highlight the advantages of fusing multiple heterogeneous remote sensing techniques to detect surface water in a predominantly natural landscape.

River flood mapping in urban areas combining Radarsat-2 data and flood return period data

Near-real-time flood maps are essential to organize and coordinate emergency services' response actions during flooding events. Thanks to its capacity to acquire synoptic and detailed data during day and night, and in all weather conditions, Synthetic Aperture Radar (SAR) satellite remote sensing is considered one of the best tools for the acquisition of flood mapping information. However, specific factors contributing to SAR backscatter in urban environments, such as shadow and layover effects, and the presence of water surface–like radar response areas, complicate the detection of flood water pixels. This paper describes an approach for near-real-time flood mapping in urban and rural areas. The innovative aspect of the approach is its reliance on the combined use of very-high-resolution SAR satellite imagery (C-band, HH polarization) and hydraulic data, specifically flood return period data estimated for each point of the floodplain. This approach was tested and evaluated using two case studies of the 2011 Richelieu River flood (Canada) observed by the very-high-resolution RADARSAT-2 sensor. In both case studies, the algorithm proved capable of detecting flooding in urban areas with good accuracy, identifying approximately 87% of flooded pixels correctly. The associated false negative and false positive rates are approximately 14%. In rural areas, 97% of flooded pixels were correctly identified, with false negative rates close to 3% and false positive rates between 3% and 35%. These results highlight the capacity of flood return period data to overcome limitations associated with SAR-based flood detection in urban environments, and the relevance of their use in combination with SAR C-band imagery for precise flood extent mapping in urban and rural environments in a crisis management context.

A New Light on SAR Backscattering Coefficient and Interferometric Coherence in Layover Areas

This letter focuses on the analysis of layover effects in interferometric synthetic aperture radar (SAR) data of urban areas. In particular, we derive two formulations to express the backscattering coefficient and the interferometric coherence in this case. These equations show that the backscattering coefficient and the interferometric coherence in layover areas can be seen as a combination of the backscattering coefficients and interferometric coherences of the individual scattering mechanisms. These formulations are then tested on interferometric SAR (InSAR) data and analyzed statistically.

3D surface reconstruction of layover areas in continuous terrain for multi-baseline SAR interferometry using a curve model

It has become a field of intensive research to exploit multi-baseline synthetic aperture radar (SAR) to solve layover effects. However, the traditional layover model is not suitable for 3D surface reconstruction in the case of continuous layover terrain for two major reasons. First, the continuous terrain cannot be precisely described by the traditional layover model. Second, the traditional layover model is formalized for a single range-azimuth resolution cell and does not take full advantage of the relationship among the neighbouring scatterers, producing ragged reconstruction results with large terrain bias. In order to solve these problems, we establish a new curve model and propose a corresponding layover solution method. Rather than rebuilding the layover area in each independent range-azimuth resolution cell, this method reconstructs it as a whole. It exploits both the multi-baseline SAR signal and a priori information of the continuous terrain to achieve better performance. In the final part of this article, the proposed method is applied to 3D surface reconstruction using simulated data and Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) data in comparison with the traditional layover model-based solution method. It is found that the proposed method leads to considerable improvements with regard to accuracy and robustness.

Wide‐field circular SAR imaging: An empirical assessment of layover effects

ABSTRACTIn circular synthetic aperture radar (CSAR), targets are usually scanned over the complete azimuthal aperture of 360°. A major challenge inhibiting successful CSAR image production is encountered in two‐dimensional imaging of relatively large scenes (i.e. wide‐field scenarios). For such cases, the spatially variant radar signature gives rises to image degradations known as layover effects. In this paper, the imaging results for hypothetical and real complex targets using their CSAR data at C band are demonstrated to characterize these effects. In real experiments, a ground‐based, outdoor CSAR system is exploited thanks to the circular balcony of a building that provides 270° view of targets. A spherical back‐projection algorithm is used to focus near‐field data and the reconstructed images are also cleaned out from clutter to more easily visualize the layover artifacts. © 2015 Wiley Periodicals, Inc. Microwave Opt Technol Lett 57:489–497, 2015

Study of the Effects of Target Geometry on Synthetic Aperture Radar Images using Simulation Studies

Abstract. Synthetic aperture radar technology has revolutionized earth observation with very high resolutions of below 5m, making it possible to distinguish individual urban features like buildings and even cars on the surface of the earth. But, the difficulty in interpretation of these images has hindered their use. The geometry of target objects and their orientation with respect to the SAR sensor contribute enormously to unexpected signatures on SAR images. Geometry of objects can cause single, double or multiple reflections which, in turn, affect the brightness value on the SAR images. Occlusions, shadow and layover effects are present in the SAR images as a result of orientation of target objects with respect to the incident microwaves. Simulation of SAR images is the best and easiest way to study and understand the anomalies. This paper discusses synthetic aperture radar image simulation, with the study of effect of target geometry as the main aim. Simulation algorithm has been developed in the time domain to provide greater modularity and to increase the ease of implementation. This algorithm takes into account the sensor and target characteristics, their locations with respect to the earth, 3-dimensional model of the target, sensor velocity, and SAR parameters. two methods have been discussed to obtain position and velocity vectors of SAR sensor – the first, from the metadata of real SAR image used to verify the simulation algorithm, and the second, from satellite orbital parameters. Using these inputs, the SAR image coordinates and backscatter coefficients for each point on the target are calculated. The backscatter coefficients at target points are calculated based on the local incidence angles using Muhleman's backscatter model. The present algorithm has been successfully implemented on radarsat-2 image of San Francisco bay area. Digital elevation models (DEMs) of the area under consideration are used as the 3d models of the target area. DEMs of different resolutions have been used to simulate SAR images in order to study how the target models affect the accuracy of simulation algorithm. The simulated images have been compared with radarsat-2 images to observe the efficiency of the simulation algorithm in accurately representing the locations and extents of different objects in the target area. The simulated algorithm implemented in this paper has given satisfactory results as the simulated images accurately show the different features present in the DEM of the target area.

Performance of Building Height Estimation Using High-Resolution PolInSAR Images

This paper investigates the use of polarimetry to improve the estimation of the height of buildings in high-resolution synthetic aperture radar (SAR) images. Polarimetric coherence optimization techniques solve the problem of layover effects in urban scenes by allowing a phase separation of the scatterers sharing the same resolution cell. Bare soil elevation estimation is also improved by the polarimetric phase diversity. First, we present an analysis of the statistical modeling of the generalized coherence set. A building height estimation method is then derived from this analysis. Finally, the method is tested and quantitatively validated over an X-band polarimetric interferometric SAR (PolInSAR) airborne image acquired in a single-pass mode, containing a set of 140 different buildings with ground truth.

SOURCES OF ARTEFACTS IN SYNTHETIC APERTURE RADAR INTERFEROMETRY DATA SETS

Abstract. In recent years, much attention has been devoted to digital elevation models (DEMs) produced using Synthetic Aperture Radar Interferometry (InSAR). This has been triggered by the relative novelty of the InSAR method and its world-famous product—the Shuttle Radar Topography Mission (SRTM) DEM. However, much less attention, if at all, has been paid to sources of artefacts in SRTM. In this work, we focus not on the missing pixels (null pixels) due to shadows or the layover effect, but rather on outliers that were undetected by the SRTM validation process. The aim of this study is to identify some of the causes of the elevation outliers in SRTM. Such knowledge may be helpful to mitigate similar problems in future InSAR DEMs, notably the ones currently being developed from data acquired by the TanDEM-X mission. We analysed many cross-sections derived from SRTM. These cross-sections were extracted over the elevation test areas, which are available from the Global Elevation Data Testing Facility (GEDTF) whose database contains about 8,500 runways with known vertical profiles. Whenever a significant discrepancy between the known runway profile and the SRTM cross-section was detected, a visual interpretation of the high-resolution satellite image was carried out to identify the objects causing the irregularities. A distance and a bearing from the outlier to the object were recorded. Moreover, we considered the SRTM look direction parameter. A comprehensive analysis of the acquired data allows us to establish that large metallic structures, such as hangars or car parking lots, are causing the outliers. Water areas or plain wet terrains may also cause an InSAR outlier. The look direction and the depression angle of the InSAR system in relation to the suspected objects influence the magnitude of the outliers. We hope that these findings will be helpful in designing the error detection routines of future InSAR or, in fact, any microwave aerial- or space-based survey. The presence of outliers in SRTM was first reported in Becek, K. (2008). Investigating error structure of shuttle radar topography mission elevation data product, Geophys. Res. Lett., 35, L15403.

Road Extraction from High-Resolution SAR Images via Automatic Local Detecting and Human-Guided Global Tracking

Because of existence of various kinds of disturbances, layover effects, and shadowing, it is difficult to extract road from high-resolution SAR images. A new road center-point searching method is proposed by two alternant steps: local detection and global tracking. In local detection step, double window model is set, which consists of the outer fixed square window and the inner rotary rectangular one. The outer window is used to obtain the local road direction by using orientation histogram, based on the fact that the surrounding objects always range along with roads. The inner window rotates its orientation in accordance with the result of local road direction calculation and searches the center points of a road segment. In global tracking step, particle filter of variable-step is used to deal with the problem of tracking frequently broken by shelters along the roadside and obstacles on the road. Finally, the center-points are linked by quadratic curve fitting. In 1 m high-resolution airborne SAR image experiment, the results show that this method is effective.

Tomographic Imaging and Monitoring of Buildings With Very High Resolution SAR Data

Layover is frequent in imaging and monitoring with synthetic aperture radar (SAR) areas characterized by a high density of scatterers with steep topography, e.g., in urban environment. Using medium-resolution SAR data tomographic techniques has been proven to be capable of separating multiple scatterers interfering (in layover) in the same pixel. With the advent of the new generation of high-resolution sensors, the layover effect on buildings becomes more evident. In this letter, we exploit the potential of the 4-D imaging applied to a set of TerraSAR-X spotlight acquisitions. Results show that the combination of high-resolution data and advanced coherent processing techniques can lead to impressive reconstruction and monitoring capabilities of the whole 3-D structure of buildings.

Fatigue in Airline Pilots After an Additional Day's Layover Period

We investigated the effect of an additional day's layover on reducing fatigue in two different duties: a two-pilot crew flying between Auckland and Brisbane, and a three-pilot crew flying between Auckland and Los Angeles. Pilots completed a reaction time task, the Samn-Perelli fatigue scale, and the Karolinska Sleepiness Scale on both outward and return flights. The flights were conducted with and without a 1-d layover (Brisbane) and with a 1- or 2-d layover (Los Angeles). On the Brisbane route, the addition of a layover resulted in a significant reduction of fatigue, sleepiness, and reaction time. At top of descent, Samn-Perelli fatigue was reduced from over 5.0 to under 4.5. In contrast, the addition of an extra day layover in Los Angeles had no significant effect on the same measures during the return flight; on both flights Samn-Perelli fatigue was over 5.0 at top of descent. The results suggest that the addition of an extra night's layover has different effects depending on the type of operation. Layover periods need to ensure adequate opportunity to recover from any sleep deficit arising from the outbound journey, but the benefit of increased layover time may be limited if time-zone shifts cause a mismatch between local time and the circadian rhythm of sleep.

Stereo analysis of high-resolution SAR images for building height estimation in cases of orthogonal aspect directions

SAR stereo image analysis for 3D information extraction is mostly carried out based on imagery taken under same-side or opposite-side viewing conditions. For urban scenes in practice stereo is up to now usually restricted to the first configuration, because increasing image dissimilarity connected with rising illumination direction differences leads to a lack of suitable features for matching, especially in the case of low or medium resolution data. However, due to two developments SAR stereo from arbitrary viewing conditions becomes an interesting option for urban information extraction. The first one is the availability of airborne sensor systems, which are capable of more flexible data acquisition in comparison to satellite sensors. This flexibility enables multi-aspect analysis of objects in built-up areas for various kinds of purpose, such as building recognition, road network extraction, or traffic monitoring. The second development is the significant improvement of the geometric resolution providing a high level of detail especially of roof features, which can be observed from a wide span of viewpoints. In this paper, high-resolution SAR images of an urban scene are analyzed in order to infer buildings and their height from the different layover effects in views taken from orthogonal aspect angles. High level object matching is proposed that relies on symbolic data, representing suitable features of urban objects. Here, a knowledge-based approach is applied, which is realized by a production system that codes a set of suitable principles of perceptual grouping in its production rules. The images are analyzed separately for the presence of certain object groups and their characteristics frequently appearing on buildings, such as salient rows of point targets, rectangular structures or symmetries. The stereo analysis is then accomplished by means of productions that combine and match these 2D image objects and infer their height by 3D clustering. The approach is tested using real SAR data of an urban scene.

Building extraction based on stereo analysis of high-resolution SAR images taken from orthogonal aspect directions

In this paper high-resolution SAR images of an urban scene are analyzed in order to infer buildings and their heights from the different layover effects in perpendicular taken views. Due to the strong dependence of the appearance of objects on the lighting and viewing direction, it is unlikely that a simple image-matching method would succeed. Instead, higher level object matching is proposed. Here, a knowledge-based approach is applied, a production system. The images are analyzed separately for the presence of certain object groups and their characteristics frequently appearing on buildings, such as salient rows, rectangular structures, or symmetries. The stereo analysis is then accomplished locally by means of productions that combine and match these image objects and infer the height. The approach is tested using real SAR data of an urban scene.

Model Order Selection in Multi-baseline Interferometric Radar Systems

Synthetic aperture radar interferometry (InSAR) is a powerful technique to derive three-dimensional terrain images. Interest is growing in exploiting the advanced multi-baseline mode of InSAR to solve layover effects from complex orography, which generate reception of unexpected multicomponent signals that degrade imagery of both terrain radar reflectivity and height. This work addresses a few problems related to the implementation into interferometric processing of nonlinear algorithms for estimating the number of signal components, including a system trade-off analysis. Performance of various eigenvalues-based information-theoretic criteria (ITC) algorithms is numerically investigated under some realistic conditions. In particular, speckle effects from surface and volume scattering are taken into account as multiplicative noise in the signal model. Robustness to leakage of signal power into the noise eigenvalues and operation with a small number of looks are investigated. The issue of baseline optimization for detection is also addressed. The use of diagonally loaded ITC methods is then proposed as a tool for robust operation in the presence of speckle decorrelation. Finally, case studies of a nonuniform array are studied and recommendations for a proper combination of ITC methods and system configuration are given.