Coastal wind field retrieval from polarimetric synthetic aperture radar

Coastal winds are strongly influenced by topology and discontinuity between land and sea surfaces. Wind assessment from remote sensing in such a complex area remains a challenge. Space-borne scatterometer does not provide any information about the coastal wind field, as the coarse spatial resolution hampers the radar backscattering. Synthetic aperture radar （SAR） with a high spatial resolution and all-weather observation abilities has become one of the most important tools for ocean wind retrieval, especially in the coastal area. Conventional methods of wind field retrieval from SAR, however, require wind direction as initial information, such as the wind direction from numerical weather prediction models （NWP）, which may not match the time of SAR image acquiring. Fortunately, the polarimetric observations of SAR enable independent wind retrieval from SAR images alone. In order to accurately measure coastal wind fields, this paper proposes a new method of using co-polarization backscattering coefficients from polarimetric SAR observations up to polarimetric correlation backscattering coefficients, which are acquired from the conjugate product of co-polarization backscatter and cross-polarization backscatter. Co-polarization backscattering coefficients and polarimetric correlation backscattering coefficients are obtained form Radarsat-2 single-look complex （SLC） data.The maximum likelihood estimation is used to gain the initial results followed by the coarse spatial filtering and fine spatial filtering. Wind direction accuracy of the final inversion results is 10.67 with a wind speed accuracy of 0.32 m/s. Unlike previous methods, the methods described in this article utilize the SAR data itself to obtain the wind vectors and do not need external wind directional information. High spatial resolution and high accuracy are the most important features of the method described herein since the use of full polarimetric observations contains more information about the space measured.This article is a useful addition to the work of independent SAR wind retrieval. The experimental results herein show that it is feasible to employ the co-polarimetric backscattering coefficients and the polarimetric correlation backscattering coefficients for coastal wind field retrieval.

The polarimetric features of oil spills in full polarimetric synthetic aperture radar images

Compared with single-polarized synthetic aperture radar （SAR） images, full polarimetric SAIl images contain not only geometrical and backward scattering characteristics, but also the polarization features of the scattering targets. Therefore, the polarimetric SAR has more advantages for oil spill detection on the sea surface. As a crucial step in the oil spill detection, a feature extraction directly influences the accuracy of oil spill discrimination. The polarimetric features of sea oil spills, such as polarimetric entropy, average scatter angle, in the full polarimetric SAR images are analyzed firstly. And a new polarimetric parameter P which reflects the proportion between Bragg and specular scattering signals is proposed. In order to investigate the capability of the polarimetric features for observing an oil spill, systematic comparisons and analyses of the multipolarization features are provided on the basis of the full polarimetric SAR images acquired by SIR-C/X-SAR and Radarsat-2. The experiment results show that in C-band SAR images the oil spills can be detected more easily than in L-band SAR images under low to moderate wind speed conditions. Moreover, it also finds that the new polarimetric parameter is sensitive to the sea surface scattering mechanisms. And the experiment results demonstrate that the new polarimetric parameter and pedestal height perform better than other polarimetric parameters for the oil spill detection in the C-band SAR images.

Application of Interferometric Spaceborne Synthetic Aperture Radar to Morphotectonic Research in the Bengcuo Area of Tibet

Using ELLS-1/2 radar satellite data, we generated a Digital Elevation Model by Interferometric Synthetic Aperture Radar, and the ERS-1/2 DEM that we generated is obviously superior to both the 1/25 ten thousand-scale DEM of the National Fundamental Geographic Information System of China and the 90-m spatial resolution＇s SRTM DEM that America published in 2004 when it showed the characteristics of tiny structure relief. By analyzing the relief characteristics of the Bengcuo fault zone based on ERS-1/2 DEM, we find that the relief on the connection location of the Bengcuo and Pengcuo fault zones has complex characteristics. A structure relief that is similar to the Pengcuo fault zone crosses through the Dazi-Dasha fault on the the Bengcuo fault zone, while the Dazi-Dasha fault crosses through a gully at this place. This indicates that the Dazi-Dasha fault has been active at this place recently. At the same time, the Naka-Naduiduo fault is severed by the gully which was cut through by the Dazi-Dasha fault. Therefore, the Naka-Naduiduo fault was formed earlier than the Dazi-Dasha fault.

Effect of digital elevation models on monitoring slope displacements in open-pit mine by differential interferometry synthetic aperture radar

Displacement monitoring in open-pit mines is one of the important tasks for safe management of mining processes.Differential interferometric synthetic aperture radar(DInSAR),mounted on an artificial satellite,has the potential to be a cost-effective method for monitoring surface displacements over extensive areas,such as open-pit mines.DInSAR requires the ground surface elevation data in the process of its analysis as a digital elevation model(DEM).However,since the topography of the ground surface in open-pit mines changes largely due to excavations,measurement errors can occur due to insufficient information on the elevation of mining areas.In this paper,effect of different elevation models on the accuracy of the displacement monitoring results by DInSAR is investigated at a limestone quarry.In addition,validity of the DInSAR results using an appropriate DEM is examined by comparing them with the results obtained by global positioning system(GPS)monitoring conducted for three years at the same limestone quarry.It is found that the uncertainty of DEMs induces large errors in the displacement monitoring results if the baseline length of the satellites between the master and the slave data is longer than a few hundred meters.Comparing the monitoring results of DInSAR and GPS,the root mean square error(RMSE)of the discrepancy between the two sets of results is less than 10 mm if an appropriate DEM,considering the excavation processes,is used.It is proven that DInSAR can be applied for monitoring the displacements of mine slopes with centimeter-level accuracy.

A Review on Applications of Imaging Synthetic Aperture Radar with a Special Focus on Cryospheric Studies

The cryosphere is the frozen part of the Earth’s system. Snow and ice are the main constituents of the cryosphere and may be found in different states, such as snow, freshwater ice, sea ice, perma-frost, and continental ice masses in the form of glaciers and ice sheets. The present review mainly deals with state-of-the-art applications of synthetic aperture radar (SAR) with a special emphasize on cryospheric information extraction. SAR is the most important active microwave remote sensing (RS) instrument for ice monitoring, which provides high-resolution images of the Earth’s surface. SAR is an ideal sensor in RS technology, which works in all-weather and day and night conditions to provide useful unprecedented information, especially in the cryospheric regions which are almost inaccessible areas on Earth. This paper addresses the technological evolution of SAR and its applications in studying the various components of the cryosphere. The arrival of SAR radically changed the capabilities of information extraction related to ice type, new ice formation, and ice thickness. SAR applications can be divided into two broad classes-polarimetric applications and interferometric applications. Polarimetric SAR has been effectively used for mapping calving fronts, crevasses, surface structures, sea ice, detection of icebergs, etc. The paper also summarizes both the operational and climate change research by using SAR for sea ice parameter detection. Digital elevation model (DEM) generation and glacier velocity mapping are the two most important applications used in cryosphere using SAR interferometry or interferometric SAR (InSAR). Space-borne InSAR techniques for measuring ice flow velocity and topography have developed rapidly over the last decade. InSAR is capable of measuring ice motion that has radically changed the science of glaciers and ice sheets. Measurement of temperate glacier velocities and surface characteristics by using airborne and space-borne interferometric satellite images have been the significant application in glaciology and cryospheric studies. Space-borne InSAR has contributed to major evolution in many research areas of glaciological study by measuring ice-stream flow velocity, improving understanding of ice-shelf processes, yielding velocity for flux-gate based mass-balance assessment, and mapping flow of mountain glaciers. The present review summarizes the salient development of SAR applications in cryosphere and glaciology.

Potential sliding zone recognition method for the slow-moving landslide based on the Hurst exponent

The abrupt occurrence of the Zhongbao landslide is totally unexpected,resulting in the destruction of local infrastructure and river blockage.To review the deformation history of the Zhongbao landslide and prevent the threat of secondary disasters,the small baseline subsets(SBAS)technology is applied to process 59 synthetic aperture radar(SAR)images captured from Sentinel-1A satellite.Firstly,the time series deformation of the Zhongbao landslide along the radar line of sight(LOS)direction is calculated by SBAS technology.Then,the projection transformation is conducted to determine the slope displacement.Furthermore,the Hurst exponent of the surface deformation along the two directions is calculated to quantify the hidden deformation development trend and identify the unstable deformation areas.Given the suddenness of the Zhongbao landslide failure,the multi-temporal interferometric synthetic aperture radar(InSAR)technology is the ideal tool to obtain the surface deformation history without any monitoring equipment.The obtained deformation process indicates that the Zhongbao landslide is generally stable with slow creep deformation before failure.Moreover,the Hurst exponent distribution on the landslide surface in different time stages reveals more deformation evolution information of the Zhongbao landslide,with partially unstable areas detected before the failure.Two potential unstable areas after the Zhongbao landslide disaster are revealed by the Hurst exponent distribution and verified by the GNSS monitoring results and deformation mechanism discussion.The method combining SBASInSAR and Hurst exponent proposed in this study could help prevent and control secondary landslide disasters.

The 2023 M_(w)6.8 Adassil Earthquake(Chichaoua,Morocco)on a steep reverse fault in the deep crust and its geodynamic implications

The Mw 6.8 Adassil earthquake that occurred in the High Atlas on September 8,2023,was a catastrophic event that provided a rare opportunity to study the mechanics of deep crustal seismicity.This research aimed to decipher the rupture characteristics of the Adassil earthquake by analyzing teleseismic waveform data in conjunction with interferometric synthetic aperture radar(InSAR)observations from both ascending and descending orbits.Our analysis revealed a reverse fault mechanism with a centroid depth of approximately 28 km,exceeding the typical range for crustal earthquakes.This result suggests the presence of cooler temperatures in the lower crust,which facilitates the accumulation of tectonic stress.The earthquake exhibited a steep reverse mechanism,dipping at 70°,accompanied by minor strike-slip motion.Within the geotectonic framework of the High Atlas,known for its volcanic legacy and resulting thermal irregularities,we investigated the potential contributions of these factors to the initiation of the Adassil earthquake.Deep seismicity within the lower crust,away from plate boundaries,calls for extensive research to elucidate its implications for regional seismic hazard assessment.Our findings highlight the critical importance of studying and preparing for significant seismic events in similar geological settings,which would provide valuable insights into regional seismic hazard assessments and geodynamic paradigms.

Dry/wet snow mapping based on the synergistic use of dual polarimetric SAR and multispectral data

We propose a multi-sensor multi-spectral and bi-temporal dual-polarimetric Synthetic Aperture Radar(SAR) data integration scheme for dry/wet snow mapping using Sentinel-2 and Sentinel-1 data which are freely available to the research community. The integration is carried out by incorporating the information retrieved from ratio images of the conventional method for wet snow mapping and the multispectral data in two different frameworks. Firstly, a simple differencing scheme is employed for dry/wet snow mapping, where the snow cover area is derived using the Normalized Differenced Snow Index(NDSI). In the second framework, the ratio images are stacked with the multispectral bands and this stack is used for supervised and unsupervised classification using support vector machines for dry/wet snow mapping. We also investigate the potential of a state of the art backscatter model for the identification of dry/wet snow using Sentinel-1 data. The results are validated using a reference map derived from RADARSAT-2 full polarimetric SAR data. A good agreement was observed between the results and the reference data with an overall accuracy greater than 0.78 for the different blending techniques examined. For all the proposed frameworks, the wet snow was better identified. The coefficient of determination between the snow wetness derived from the backscatter model and the reference based on RADARSAT-2 data was observed to be 0.58 with a significantly higher root mean square error of 1.03 % by volume.

Improved SMB speckle filtering of polarimetric SAR data with synergistic use of orientation angle compensation and spatial majority rule

The scattering-model-based(SMB)speckle filtering for polarimetric SAR(Pol SAR)data is reasonably effective in preserving dominant scattering mechanisms.However,the efficiency strongly depends on the accuracies of both the decomposition and classification of the scattering properties.In addition,a relatively weak speckle reduction particularly in distributed media was reported in the related literatures.In this work,an improved SMB filtering strategy is proposed considering the aforementioned deficiencies.First,the orientation angle compensation is incorporated into the SMB filtering process to remedy the overestimation of the volume scattering contribution in the Freeman-Durden decomposition.In addition,an algorithm to select the homogenous pixels is developed based on the spatial majority rule for adaptive speckle reduction.We demonstrate the superiority of the proposed methods in terms of scattering property preservation and speckle noise reduction using L-band Pol SAR data sets of San Francisco that were acquired by the NASA/JPL airborne SAR(AIRSAR)system.

Integration of SAR Polarimetric Features and Multi-spectral Data for Object-Based Land Cover Classification

An object-based approach is proposed for land cover classification using optimal polarimetric parameters.The ability to identify targets is effectively enhanced by the integration of SAR and optical images.The innovation of the presented method can be summarized in the following two main points:①estimating polarimetric parameters(H-A-Alpha decomposition)through the optical image as a driver;②a multi-resolution segmentation based on the optical image only is deployed to refine classification results.The proposed method is verified by using Sentinel-1/2 datasets over the Bakersfield area,California.The results are compared against those from pixel-based SVM classification using the ground truth from the National Land Cover Database(NLCD).A detailed accuracy assessment complied with seven classes shows that the proposed method outperforms the conventional approach by around 10%,with an overall accuracy of 92.6%over regions with rich texture.

MCJ-UNet:一种双/多通道联合InSAR相位解缠网络

干涉合成孔径雷达(InSAR)可实现地表高程的高效获取,在地形测绘中应用广泛。双/多通道InSAR技术可借助不同通道(基线、频点)的高程模糊度差异,解决相位欠采样问题,完成高程陡变区域的干涉相位解缠,实现InSAR技术在测绘困难区域的有效应用。该文即面向高效高精度相位解缠需求,利用深度学习这一有力工具,结合不同通道的相位特征及相互约束关系,提出了一种双/多通道联合干涉相位解缠网络:Multi-Channel-Joint-UNet(MCJ-UNet)。该网络的构建以双通道(双频、双基线)InSAR为基本观测构型,并可实现向多通道构型的扩展,其构建的核心思路主要包括3点:首先,将干涉相位解缠中的模糊数估计问题转化为语义分割问题,并采用UNet网络完成分割处理;其次,引入挤压激励模块(SE)动态调整信息权重,以增强网络不同通道对其所需信息的感知能力;最后,利用多通道联合约束下的相位残差优化损失函数,实现网络调谐。此外,为避免语义分割结果的边缘细节误差对解缠效果的影响,该文还提出了一种基于多通道联合约束的解缠误差自修正方法,以保证解缠质量。模拟地形仿真数据、真实地形仿真数据以及TerraSAR-X实测数据验证了所提方法的有效性。

一种天基双基地InSAR系统的相位同步方法及验证情况

以德国的TanDEM-X双星编队干涉合成孔径雷达(InSAR)卫星系统为背景,提出了基于点频连续波同步信号双向对传,实现编队卫星InSAR系统相位同步的方法。文中给出了该同步方法实现的框架,对该相位同步方法的原理进行了理论推导,得出了补偿相位差的表达式,并对影响同步精度的因素进行了初步的分析。该方法可用于天基双/多基地合成孔径雷达系统相位同步链路的设计,仿真分析的结果验证了该方法的理论可行性。此外,通过搭建实物系统对系统的工程可实现精度进行了验证,结果表明获取的载波频率相位同步精度与倍频器件的频率精度和一致性密切相关。该相位同步方法为与TanDEM-X相近InSAR系统的设计提供参考。

基于极化SAR梯度和复Wishart分类器的舰船检测

舰船检测是极化SAR系统的重要应用之一。现有的舰船检测方法容易受到旁瓣泄露的干扰,使得舰船目标的形态难以提取,导致检测结果不符合真实情况。此外,在舰船过于密集、尺度不一致的情况下,相邻舰船由于旁瓣的影响有时会被认为是单个目标,从而造成漏检。针对这些问题,该文提出一种基于极化SAR梯度和复Wishart分类器的舰船检测方法。首先,将似然比检验(LRT)梯度引入对数比值梯度框架,使其适用于极化SAR数据;基于LRT梯度图进行恒虚警(CFAR)检测,提取舰船的边缘信息,消除伪影的同时抑制强旁瓣对舰船精细轮廓提取的影响。其次,利用复Wishart迭代分类器对舰船强散射部分进行检测,可排除大部分的杂波干扰且保持舰船形态细节。最后,将二者信息融合,从而可以保持舰船形态细节的同时克服旁瓣和伪信号的虚警。该文在3幅来自ALOS-2卫星的极化SAR图像上进行了对比实验,实验表明与其他方法相比,该文所提算法具有更少的虚警和漏检,且能够有效克服旁瓣泄露,保持舰船形态细节。

基于InSAR技术的大跨桥梁温度变形监测研究

以国内某高速铁路钢拱桥为研究对象,选取2017—2018年期间59幅C波段Senti⁃nel-1号雷达卫星影像,利用PS-InSAR技术处理影像获得桥梁的视线向(Line of Sight,LOS)位移,根据SAR成像空间几何关系解算出支座的纵向位移.研究结果表明:支座纵向位移的时空特性与实际桥梁结构相符合,验证了PS-InSAR技术观测桥梁结构位移的可行性.建立支座纵向位移与温度的线性相关模型,并与结构健康监测系统的实测结果进行对比.两者吻合良好,相对误差控制在10%以内,验证了PS-InSAR测量桥梁结构位移的可靠性.利用有限元模拟温度作用下桥梁支座的位移变化,并与PS-InSAR位移时间序列进行对比.两者趋势基本一致,LOS向位移误差在[-10,10]mm,验证了PS-InSAR测量桥梁结构位移的准确性.

Effect of orbital errors on the geosynchronous circular synthetic aperture radar imaging and interferometric processing

The geosynchronous circular synthetic aperture radar (GEOCSAR) is an innovative SAR system,which can produce high resolution three-dimensional (3D) images and has the potential to provide 3D deformation measurement.With an orbit altitude of approximately 36 000 km,the orbit motion and orbit disturbance effects of GEOCSAR behave differently from those of the conventional spaceborne SAR.In this paper,we analyze the effects of orbit errors on GEOCSAR imaging and interferometric processing.First,we present the GEOCSAR imaging geometry and the orbit errors model based on perturbation analysis.Then,we give the GEOCSAR signal formulation based on imaging geometry,and analyze the effect of the orbit error on the output focused signal.By interferometric processing on the 3D reconstructed images,the relationship between satellite orbit errors and the interferometric phase is deduced.Simulations demonstrate the effects of orbit errors on the GEOCSAR images,interferograms,and the deformations.The conclusions are that the required relative accuracy of orbit estimation should be at centimeter level for GEOCSAR imaging at L-band,and that millimeter-scale accuracy is needed for GEOCSAR interferometric processing.

面向目视解译的全极化SAR船只精细化特征表征方法

随着卫星技术的发展,极化合成孔径雷达(PolSAR)数据的分辨率和数据质量得到大幅提升,为人造目标的精细化目视解译提供了良好的数据条件。目前主要采用多分量分解的方法,但是易造成像素错分问题,为此,该文结合Yamaguchi极化分解和极化熵提出了一种非固定阈值划分的方法用于实现全极化SAR图像船只结构精细化特征表征。Yamaguchi极化分解能够识别基本散射机制,其修正后的体散射模型更符合实测数据,可有效对人造目标进行表征。极化熵H在弱去极化状态下可以看成某一指定等效点的目标散射机制,能够有效突出船只主散射特征。因此,该文通过将Yamaguchi极化分解算法的非固定三分量与极化熵的低中高熵内嵌,将其分为非固定阈值的九分类成分,从而降低硬阈值处理在阈值边界处受噪声影响产生的类别随机性。并且将二次散射和单次散射均显著的区域称为混合散射(MSM),以更好匹配实验中船只典型结构的散射类型。在此基础上,利用广义相似性参数进一步缩短类内距离,采用改进后的GSP-Wishart分类器进行迭代聚类,旨在通过提高二次散射和混合散射机制以提高不同类型船只可区分度。最后,该文采用中国上海某港口的高分三号全极化SAR数据进行实验,为了验证每艘船只特征表征正确性,通过船舶自动识别系统(AIS)收集并筛选了该港口船只信息及光学数据,并与极化SAR数据中每艘船只进行匹配。实验结果表明该方法可有效区分散货船、集装箱船和油轮3种类型船只。

采空区地表InSAR形变监测与安全稳定性评价

为探明河南省平顶山市某变电站拟建场地的安全稳定性,避免采空区地表沉降或倾斜给变电站造成安全隐患,采用永久散射体(PS)合成孔径雷达干涉测量(InSAR)研究平顶山市2015—2022年间的45景Sentinel-1A数据,精细化分析拟建场地的9个代表位置的时序形变特征,进而建立基于InSAR监测的采空区地表场地安全稳定性评价机制,完成对场地的安全稳定性评价。研究结果表明:基于模糊数据集的模糊PS选点法可克服PS点密度低的弊端,有效增加分析可用数据,提升监测结果的准确性;依据基准点校正拟建区内代表点的时序形变后发现,拟建场地整体形变较小且逐渐呈现趋于稳定的趋势,最大沉降量为13.05 mm,最大沉降速度为5.73 mm/a,最大倾斜为0.070 mm/m。基于安全稳定性评价机制分析可知:采空区地表场地移动变形处于稳定状态,变电站地基基础处于安全状态,采空区地表沉降对拟建变电站的影响程度小,综合3种评价指标进行分析,采空区地表场地安全稳定性等级为高,具备建设变电站的可行性。

边坡雷达在重大突发性滑坡应急监测中的应用研究

西南地区突发性重大地质灾害常发生于深切河谷区,在应急抢险过程中,存在人员难到达、地面调查与监测困难、灾害持续变形破坏造成的危害大等问题。以西藏自治区江达县白格滑坡和四川丹巴县阿娘寨滑坡应急抢险为例,应用边坡雷达对白格滑坡残留体和阿娘寨滑坡复活体进行应急监测和变形特征研究。结果表明:通过边坡雷达获取各测点的累计视向变形量、变形速率、变形加速度等监测数据绘制监测区变形云图和监测曲线,判识滑坡区变形破坏及发展趋势、研判各变形区所处的变形演化阶段,快速对临滑破坏区进行识别与预报。边坡雷达能对突发性重大地质灾害开展非接触式全天候实时监测,既能实时掌握灾害变形特征,也保证了监测人员安全,对今后类似的突发性地质灾害应急监测和预警预报具有参考借鉴意义。

Intertidal area classification with generalized extreme value distribution and Markov random field in quad-polarimetric synthetic aperture radar imagery

Classification of intertidal area in synthetic aperture radar(SAR) images is an important yet challenging issue when considering the complicatedly and dramatically changing features of tidal fluctuation. The difficulty of intertidal area classification is compounded because a high proportion of this area is frequently flooded by water, making statistical modeling methods with spatial contextual information often ineffective. Because polarimetric entropy and anisotropy play significant roles in characterizing intertidal areas, in this paper we propose a novel unsupervised contextual classification algorithm. The key point of the method is to combine the generalized extreme value(GEV) statistical model of the polarization features and the Markov random field(MRF) for contextual smoothing. A goodness-of-fit test is added to determine the significance of the components of the statistical model. The final classification results are obtained by effectively combining the results of polarimetric entropy and anisotropy. Experimental results of the polarimetric data obtained by the Chinese Gaofen-3 SAR satellite demonstrate the feasibility and superiority of the proposed classification algorithm.

基于RIME-CNN-SVR模型的麦田土壤水分反演

土壤水分监测对于农业生产和作物产量预估具有重要意义。近年来深度学习技术在土壤水分反演领域得到广泛应用,但大多侧重于模型结构增强和优化,对模型超参数优化研究探索不足。该研究提出了一种基于霜冰优化算法(rime optimization algorithm,RIME)的卷积神经网络(convolutional neural network,CNN)超参数优化模型,结合极化分解技术来校正植被对土壤水分反演精度的影响,以提高冬小麦农田土壤水分反演性能。首先利用RIME优化CNN超参数以构建RIME-CNN模型,然后使用RIME-CNN模型对特征参数进行自适应提取和挖掘,之后对这些特征参数进行正则化处理并输入到支持向量回归(support vector regression,SVR)模型,构建RIME-CNN-SVR模型进行土壤水分估算。为验证所建RIME-CNN-SVR模型的有效性,利用合成孔径雷达(synthetic aperture radar,SAR)数据结合光学遥感数据,在河南省开封市冬小麦农田区进行试验验证和精度分析。结果表明,该方法在不增加模型结构复杂性和可学习参数的前提下,显著提升了模型的预测性能,决定系数可达0.72,均方根误差为2.78%,平均绝对误差为2.20%。该研究可为农业生产提供一个更为准确、可靠的土壤水分监测手段。