The negative alpha filter: a new Processing technique for polarimetric SAR interferometry

In this letter we develop a new concept, the negative alpha filter, which we suggest has application for quantitative estimation of surface parameters beneath vegetation using polarimetric synthetic aperture radar (SAR) interferometry (POLInSAR). We first derive the filter and then validate it using simulations of L-band coherent forest scattering. We then show initial results of applying the filter to airborne data from the German Aerospace Center's E-SAR L-band sensor.     

基于ALOS PALSAR数据进行雷达差分干涉提取玉树地震同震地表形变场

本文针对2010年4月14日玉树地震引起的地表形变,使用日本ALOS卫星PALSAR L波段雷达影像数据,应用两轨雷达差分干涉(DInSAR)处理得到了以玉树为中心11 000km2范围内的同震形变场,空间分辨率为8m,并在此基础上对玉树地震的震源机制和发震机理进行了分析。研究结果表明L波段雷达数据适合在地形起伏较大的地区进行DInSAR形变探测。该同震形变场信息可为玉树地震的同震形变反演提供参考数据。该研究进一步证实DInSAR技术在大规模地表形变探测和地学研究领域具有广阔的应用前景。     

利用L波段星载重复轨道干涉SAR提取DEM及大气效应分析

以四川省茂县、安县地区的ALOS PALSAR L波段雷达影像为数据源,在对地形复杂区的配准、解缠等算法研究的基础上,结合SAR特有的成像几何结构,对两幅SAR图像进行快速自动配准,配准误差小于0.2个像元;在去除平地引起的干涉相位变化后,运用MCF对缠绕相位进行解缠,在此基础上提取研究区的数字高程模型(DEM),分析发现精度受多种因素影响,其中波长较长的L波段数据比波长较短的时间相关性好,此外为消除大气效应,采用改进的相位累积法去除大气的影响,在一定程度上提高DEM精度。其误差范围在±10m左右,对快速提取地形信息具有一定的借鉴意义。     

卫星雷达遥感在滑坡灾害探测和监测中的应用:挑战与对策

将卫星雷达遥感应用于滑坡灾害的探测与监测，不仅可以从空间尺度上大范围捕捉到滑坡信号，而且可以从时间尺度上以较长周期追踪滑坡的运动状态。但是，卫星雷达遥感本身的局限性和滑坡所处的复杂地形环境使这一应用面临一些挑战。对卫星雷达遥感技术的4个主要挑战进行了总结与分析，同时给出了相应的解决方案:①通过提高卫星雷达影像的空间、时间分辨率，使用较长波段雷达信号或采用增强型时间序列分析技术，可降低密集植被覆盖对相干性的影响。另外，采用像素点偏移量追踪或距离向分频干涉测量方法，可克服传统干涉测量中大梯度形变引起的相位失相干。②大气延迟对卫星遥感的影响较大，尤其是地处山区的滑坡探测和监测，利用通用型卫星雷达大气改正系统可显著减弱干涉影像的大气信号并进一步简化时间序列分析，提高缓慢运动滑坡的探测和监测质量。③对于中等分辨率的雷达影像而言，利用数字高程模型可提前量化分析雷达几何畸变（如叠掩、阴影等）引发的滑坡探测监测的适用性；而对于高分辨率的雷达影像而言，利用机器学习方法无需外部高分辨率数字高程模型即可精确识别雷达影像的阴影和叠掩区并进行掩膜，从而大幅度提高数据处理效率。④针对高坡度地区残余的地形相位引起的解缠误差，可通过基线线性组合的方法予以减弱。此外，提出了一个基于多源对地观测的滑坡探测/监测系统框架，综合卫星雷达遥感与其他对地观测数据（如地基雷达、激光雷达、全球导航定位系统），搭建了一个自动化滑坡探测与监测系统。该研究旨在阐明卫星雷达遥感的优缺点，进一步深化其在滑坡灾害监测方面的应用和推广，引出未来侧重发展方向的思考与探讨。     

Detecting the slope movement after the 2018 Baige Landslides based on ground-based and space-borne radar observations

On Oct. 11 and Nov. 3, 2018, two large-scale landslides occurred in the same location in Baige Village, Tibet, and massive rocks fell and encroached into the Jingsha River. These landslides posed a severe risk to the upstream and downstream areas. The occurrence, development and evolution of landslides are accompanied by a large number of changes in measurable variables. The deformation data are one of most important parameters for characterizing change and development trends of a landslide. This paper is centered on the results derived from ground-based radar and space-borne Synthetic Aperture Radar (SAR) images in the post-event phase to monitor the Baige landslides and to assess their residual risk. Two technologies play important roles in identifying and characterizing impending catastrophic slope failures: ground-based radar reveals the horizontal deformation, and satellite SAR images reveal the azimuth and range offset deformation. By combining satellite and ground-based SAR observations, we obtained high-precision three-dimensional (3D) deformation results and found that the vast majority of the instability regions mainly occur in the source area of the slope failures and that the direction of collapse converges from all sides to the middle. Additional information from UAV orthophoto maps and GNSS measurements also reveal that several cracks are distributed on the trailing edge of the landslide and are still moving. The comprehensive results revealed that the moving rock mass has still been remarkably active after the two landslide events. This study combined ground-based and space-borne SAR data to develop a long-term monitoring and stability evaluation process for implementation after a large landslide disaster. Based on the distribution characteristics of the 3D deformation fields, the present and future stability of the Baige Landslide was analyzed.     

Remarks on correcting ionospheric distortions in L-band radar interferometry

The L-band synthetic aperture radar (SAR) interferometry (InSAR) technique has a lower accuracy due to ionospheric phase distortions. Recently, a multiple-aperture interferometry (MAI)-based ionospheric correction method has been proposed. Using four types of ionosphere-distorted interferograms, the performance of the correction method was evaluated and then analyzed the feasibility of the correction method. The test interferograms contained severe azimuth streaking, low-frequency ionospheric phase distortion and drastic phase change due to the ionosphere. The results showed that (i) the existence and magnitude of ionospheric phase distortions can be recognized from MAI interferograms and (ii) the MAI-based ionospheric correction method efficiently reduced severe azimuth streaking and low-frequency distortion but did not mitigate the drastic phase change perfectly. It is allowed (i) to determine whether a given SAR interferogram has an ionospheric distortion and (ii) to predict whether the ionospheric distortion can be corrected by using the MAI-based ionospheric correction method.     

基于D-InSAR技术的金沙江地区滑坡形变监测与分析

滑坡是发生在我国山区的主要地质灾害类型,金沙江地区由于地势较高、地形复杂、多云多雨的特点,给传统的滑坡监测增加了难度。合成孔径雷达差分干涉测量技术(Differential interferometry synthetic aperture radar,D-InSAR)已在滑坡地面沉降监测中得到了广泛应用。本文选取金沙江上游沿岸作为研究区域,基于2018年8月11日与9月28日的Sentinel-1A影像及SRTM1数据,利用GAMMA软件及D-InSAR技术监测到金沙江地区的地表形变,成功识别出金沙江右岸的一处滑坡灾害。研究结果显示,在此滑坡的坡顶部分出现了约2.5 cm的沉降,而在坡底部分由于崩塌物的累积,地面出现了约3 cm的抬升。从实验结果可以得出,InSAR技术是一种有效的滑坡变形监测手段,利用Sentinel-1A卫星的SAR数据对滑坡区域进行形变监测,可以得到较好的干涉结果。     

干涉雷达永久散射体自动探测--算法与实验结果

基于理论与模拟实验分析,提出并实现“双重阈值”PS自动探测算法,即时序相关系数阈值法和振幅离差指数阈值法相结合,达到PS自动探测时间效率与可靠性的统一。选用覆盖上海地区的26幅ERS-1/2 C波段SAR图像(1992~2002年),双重阈值PS探测算法得到了检验,实验结果表明,该方法能够有效地提取可靠的PS目标。     

干涉雷达时间序列分析方法在地面沉降监测中的应用

地面沉降已经成为全球性问题，传统的大地测量技术在日益严重的大范围地面沉降监测方面越来越显得难以胜任，新兴的 雷达干涉测量技术正好提供了一种大覆盖、高空间和高时间分辨率的地面沉降监测手段。本文以天津地区为实验区，介绍并实现了 利用PS点的InSAR时间序列分析方法，取得了较好的实验结果。     

利用最小二乘的雷达干涉PS相位解缠方法

常规DInSAR技术中,时空失相关及大气延迟等因素的影响限制了相位解缠结果的精度。永久散射体(PS)InSAR方法间接克服了常规雷达干涉中的时空失相关问题,单独对PS这种高相干目标进行相位解缠可以避免失相关噪声对解缠结果的影响。本文在已有相位解缠方法的基础上,提出基于最小二乘的稀疏PS点相位解缠方法,陈述了相应的建模思想及相关数据处理方法;分别基于模拟数据和真实数据(日本ALOS卫星获取的PALSAR L波段数据)对所提方法进行了实验验证。结果表明,该方法能够有效地对PS数据集进行相位解缠。     

Surface deformation associated with the 2008 Ms8.0 Wenchuan earthquake from ALOS L-band SAR interferometry

The Ms8.0 Wenchuan earthquake (in China) occurred on 12 May 2008 as a result of slip on the northeastern-striking Longmen Shan (LMS) faults beneath the rugged margin between the Qinghai-Tibet Plateau and Sichuan Basin. The catastrophic event caused significant surface ruptures and permanent ground displacement in a wide area. This paper concentrates on mapping surface deformation caused by the main shock with the interferometric synthetic aperture radar (InSAR) technology. The coseismic interferogram covering an area of over 83,000 km² is computed with use of 46 SAR images that were collected along 6 adjacent ascending orbits by the L-band SAR sensor onboard the Japanese Advanced Land Observing Satellite (ALOS). The displacements measured at 16 GPS sites are used to check the accuracy of the InSAR deformation measurements. The radar coherence is computed and analyzed in relation to the topography and the normalized difference vegetation index (NDVI) estimated from the Landsat-7 imagery. The results show that the coseismic surface deformation can be mapped up to a centimeter-accuracy level even over the highly mountainous and heavily vegetated area with the L-band interferometer. It is also demonstrated that the L-band interferograms with time interval of months to years can still maintain acceptable radar coherence for deformation extraction over the area under the extreme conditions. The extracted InSAR deformation measurements show that the lands in the Sichuan Basin had moved 0.1–1.3 m toward the satellite along the radar line of sight (LOS) direction with an azimuth of 349.8° and an elevation angle of 51.3°, while the lands in the LMS area had moved 1.4 m at most away from the satellite.     

青海玉树地震差分干涉雷达同震形变测量

2010-04-14青海玉树发生7.1级地震后,作者利用震前和震后获取的日本ALOS卫星PALSAR遥感数据,开展了差分干涉雷达(D-InSAR)地震同震形变测量与分析。结果表明:玉树地震引起较大范围地表变形,地震变形沿玉树—甘孜断裂带向南东东方向扩展,在N33.7°,E96.81°附近达到最大形变量,D-InSAR监测到雷达视向上的最大形变量为35cm。地表形变特征对于评价玉树地震破坏程度、推断断层性质、研究地震形变和地震孕育特征具有重要的参考价值。     

Advanced differential interferometry synthetic aperture radar techniques for deformation monitoring: a review on sensors and recent research development

This paper reviews the advanced differential interferometry synthetic aperture radar (A-DInSAR) techniques, with two major components in focus. First is the basic concepts, synthetic aperture radar (SAR) data sources and the different algorithms documented in the literature, primarily focusing on persistent scatterers. In the second part, the techniques are compared in order to establish more linkage in terms of the variability of their applications, strength and validation of the interpreted results. Also, current issues in sensor and algorithm development are discussed. The study identified six existing A-DInSAR algorithms used for monitoring various deformation types. Generally, reports of their performance indicate that all the techniques are capable of measuring deformation phenomena at varying spatial resolution with high level of accuracy. However, their usability in suburban and vegetated areas yields poor results, compared to urbanized areas, due to inadequate permanent features that could provide sufficient coherent point targets. Meanwhile, there is continuous development in sensors and algorithms to expand the applicability domain of the technology for a wide range of deformable surfaces and displacement patterns with higher precision. On the sensor side, most of the latest SAR sensors employ longer wavelength (X and P bands) to increase the penetrating power of the signal and two other sensors (ALOS-2 PALSA-2 and SENTINEL-1) are scheduled to be launched in 2013. Researchers are investigating the possibility of using single-pass sensors with different look angles for SAR data collection. With these, it is expected that more data will be available for various applications. Algorithms such as corner reflector interferometry SAR, along track interferometry, liqui-InSAR, and squeeSAR are emerging to increase reliable estimation of deformation from different surfaces.     

Calculating vertical deformation using a single InSAR pair based on singular value decomposition in mining areas

Vertical deformation estimation can be a significant tool in preventing geological hazards and managing environment impacts of underground mining. Common ground surface vertical deformation calculations are challenged by difficult data collection and dependence on prior knowledge. SVD (singular value decomposition) method was applied to estimate ground surface vertical deformation from single pair SAR (synthetic aperture radar) data in a mining region. During the study, LOS (line of sight) and azimuth displacement was obtained using two pass D-InSAR (differential interferometry synthetic aperture radar) and MAI (multi-aperture radar interferometry) technology, respectively. Two adjustment equations were composed using the imaging geometry of D-InSAR and MAI. The singular value decomposition theorem was used to acquire M-P (Moore-Penrose) generalized inverse of the rank deficiency coefficient matrix. From this, the optimal approximation solution of unknown parameters was calculated using weighted least squares. A working panel in the Datong mining area, Shanxi province, China, was selected to verify the SVD approach using the two ascending Sentinel-1A data. The accuracy of vertical deformation estimated by SVD approach is reliable. The RMSE (root mean square error) of vertical deformation is 2.64 mm (along upright profile) and 4.95 mm (along horizontal profile). These results suggest that the SVD approach will complement widely used vertical ground surface deformation calculations. Further study is needed to validate the method from other deformation scenarios from landslides, groundwater loss, earthquakes, underground mining, and glacier movement.     

INSAR技术在海州露天矿边坡变形监测中的应用研究

露天矿边坡的变形监测一直是矿山安全生产的重要工作,运用合成孔径雷达干涉(INSAR)测量技术对边坡进行监测是近年来微波遥感研究的一个重要方向。本文分析了INSAR技术在边坡变形监测中的技术优势及研究的进展情况,并利用海州露天矿传统监测实测数据和INSAR监测进行比较,结果表明,INSAR技术可以实现对大型露天矿边坡有效地监测,具有一定的技术优势和广阔的应用前景。     

多频率InSAR提取沼泽湿地DEM精度对比分析

选取3种波长的干涉SAR数据对提取沼泽湿地区域的DEM，并随机从1：10 000地形图中选取111个点数据进行精度验证，最后对比分析了沼泽湿地植被对于不同SAR波长的干涉相干性差异。结果表明：L-band ALOS-1 PALSAR精细模式的HH单视复数数据与1：10 000地形图数据吻合度较好，76.58%的高程值差异在3 m以内，其相干系数比C-band Sentinel-1A IW模式的VV单视复数数据和X-band TerraSAR HH单视复数数据要高；更适合利用雷达干涉测量技术提取沼泽湿地的DEM；不同湿地植被类型的相干系数有较大差异，岛状林和灌草结合的湿地植被分布区相干系数值较大，而浅水沼泽植被区和深水沼泽植被区相对较低。     

River dike deformation measurement with airborne SAR

Due to extremely high water levels or extremely dry periods, river dikes can deform and eventually burst. The deformation can be measured with repeat-pass synthetic aperture radar (SAR) interferometry. Two flights (5.5-day interval) with an airborne C-band SAR were carried out to verify a particular case. During the second flight, the dike was deliberately deformed. Interferogram analyses showed that the dike deformed by at most 2 mm on this day, in approximate agreement with tachymeter measurements. Corner reflector analysis showed a deformation of about 1 cm during the 5.5-day interval, in good agreement with ground measurements.     

Assessment of number and distribution of persistent scatterers prior to radar acquisition using open access land cover and topographical data

Persistent scatterer synthetic aperture radar interferometry (PSI) is a powerful remote sensing technique to detect and measure deformation of the Earth‘s crust – such as subsidence and landslides – with an accuracy of a few millimeters. Deformation is measured at specific points in a radar image called persistent scatterers (PS), which are characterized by long-term constant backscattering properties (high coherence) of the radar signal. Reliable PSI processing requires a stack of 15–50 SAR images and more, and processing is time-consuming (computational costs) and expensive (referring to both, costs for the SAR data and labor costs). Previous research for PS assessment used already acquired SAR data. This paper presents two new methods for predicting PS prior to the radar recording of the area of interest using freely available or low-cost land cover data, topographical maps and OpenStreetMap data. In the procedure, the distance between the assessed PS is calculated and classified regarding to the applicability for PSI processing. Additionally, the dispersion of the assessed PS within the site is analyzed. The results of the two assessment methods are validated using data of real PSI processing. Here, we show that the developed PS assessment techniques are fast and reliable tools to test the spatial applicability of PSI.     

基于观测时间配准的升降轨InSAR数据二维形变场解算

传统差分干涉技术只能获取雷达视线方向的一维形变场,极大地限制该技术的应用。联合升降轨InSAR数据,可以解算出地表二维形变场。然而,受卫星轨道参数的限制,即使是不同的卫星,也很难做到对同一目标的同步观测,造成升降轨观测时间的不一致,进而降低二维形变解算精度。针对上述问题,文中提出一种升降轨观测时间配准方法,即以其中一轨SAR时序数据的采集时刻为参考,采用数据插值技术,对另一轨SAR时序数据获取的时间累积形变量进行内插,得到对应参考时刻点的形变量。最后,联合解算时间配准后的两个一维形变量,获取研究区域的二维形变场。为验证所提方法的有效性,文中以苏锡常地区为例,开展二维形变场的解算实验。研究结果表明,所提方法可以更加准确地反演地表二维形变场。     

In Search of the Statistical Properties of High-Resolution Polarimetric SAR Data for the Measurements of Forest Biomass Beyond the RCS Saturation Limits

The purpose of this letter is to present the results on the study of searching effective parameters that describe the relation between high-resolution synthetic aperture radar (SAR) images and forest parameters. The study is based on the non-Gaussian texture analysis of the polarimetric airborne Pi-SAR data over coniferous forests in Hokkaido, Japan. The radar cross section (RCS) in terms of a forest biomass is first analyzed. It is found that the L-band RCS increases steadily with the biomass and saturates at approximately 40 tons/ha. These results are similar to the previous studies. The probability density function of the image amplitude is then investigated, and among Rayleigh, log-normal, Weibull, and K-distributions, the K-distribution is found to fit best to the L-band data of all polarizations, although the Weibull distribution fits equally well. Further, the correlation between the tree biomass and the order parameter of the K-distribution in the cross-polarization images is found to be very high, and the order parameter increases consistently with the biomass to approximately 100 tons/ha, which is well beyond the saturation limit of the L-band RCS. Thus, the order parameter of the K-distribution can be a promising new parameter to estimate the forest biomass from high-resolution polarimetric SAR data in a much wider range than the conventional RCS method