时序InSAR滑坡探测与DEM误差影响分析

以贵州省西南山区为例,针对地质灾害隐患早期识别的实际情况和需求,开展差分干涉测量和时序InSAR方法的对比实验,以验证时序InSAR在抗误差干扰、探测微小形变、捕捉形变序列演化趋势等方面的能力;再基于高精度LiDAR DEM数据进一步研究DEM误差对时序InSAR处理结果的影响。实验表明,时序InSAR方法无法完全剔除DEM误差,从而导致形变速率、形变序列估计不准,在开展精细化InSAR形变分析时应尽可能选取高精度的外部DEM数据,以保证正确估计地质灾害隐患形变特征。     

InSAR数据处理中的误差分析

针对星载雷达 ,从InSAR的基本原理出发 ,综合推导并讨论了相位观测误差、卫星轨道误差、地形误差等各类误差源对不同工作模式 (包括重复飞行InSAR生成DEM ,Two passDInSAR监测地表形变 ,以及Three passDInSAR监测地表形变 )的影响     

InSAR基本原理

作为InSAR系列讲座的第三篇，本文首先介绍干涉相位信号及InSAR测高与探测形变的基本原理。最后比较并讨论其在地表高程和形变测量中的敏感程度。     

InSAR大气延迟误差分析

分析了大气延迟的各分量（干延迟、湿延迟、液态水延迟和电离层延迟）对InSAR观测的影响。结合InSAR／DInSAR的数学模型，推导了对流层延迟对重轨干涉测量模式影响的双差模型、对三轨法和四轨法DInSAR对流层延迟的三差模型。并基于此，依据误差传播定律推导了对流层延迟误差对InSAR产品精度影响的公式。     

利用附加系统参数的InSAR轨道误差估计

针对利用小波分析方法联合二次曲面模型改正合成孔径雷达干涉测量技术(InSAR)轨道误差时观测值的系统误差特性,该文在传统二次多项式的基础上建立了一种附加系统参数的轨道误差改正模型。利用小波分析方法可以有效提取干涉相位中的低频部分,二次多项式法计算简便,附加系统参数平差原理顾及了观测值中其它系统误差项的影响,结合3种方法更准确地求解出了改正模型参数,实现了对InSAR轨道误差的有效估计去除。基于伊朗巴姆地区的ENVISAT ASAR数据实验表明:在使用所提算法去除轨道误差相位后的干涉图中,远离形变区域位置的相位值基本趋近于0rad,轨道残差相位也基本得到消除。     

阿尔金断裂带宽幅InSAR对流层延迟估计方法评估

近年来,宽幅合成孔径雷达干涉测量(interferometric synthetic aperture radar, InSAR)技术已被广泛用于地质灾害普查、地壳形变监测等方面,但对流层相位延迟影响极大限制了大范围、缓慢构造形变监测的精度。以覆盖地形起伏强烈的阿尔金断裂带西段的两类宽幅InSAR时间序列为例,分析了欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts, ECMWF)、InSAR通用型大气改正在线服务(generic atmospheric correction online service for InSAR, GACOS)、地形相关线性模型这3类方法对大尺度对流层延迟的改正效果。结果表明,经GACOS改正后的Envisat ASAR与Sentinel-1宽幅InSAR干涉图序列的相位标准差均值削减量分别可达68.1%和54.5%,整体优于ECMWF和地形相关线性改正方法,能够为国内外InSAR用户开展宽幅InSAR大范围地质灾害监测等应用提供关键可靠的支持。     

宽幅InSAR大地测量学与大尺度形变监测方法

随着人们对大尺度地形信息与地表环境变化监测需求的提升,以及哨兵1号（Sentinel-1A）、大地2号（ALOS-2）等合成孔径雷达（synthetic aperture radar,SAR）卫星的宽幅模式数据不断获取,宽幅雷达干涉测量（SAR interferometry,InSAR）技术已成为大尺度地形测绘、地球动力学（地震、火山、滑坡等）与人工地物结构健康监测等领域的研究热点。分析了两类宽幅SAR数据,即扫描（ScanningSAR,ScanSAR）模式与逐行扫描地形观测（terrain observation by progressive scans SAR,TOPSAR）模式开展干涉测量的主要限制条件与解决方法,探讨了宽幅InSAR形变监测关键误差估计与改正方法、时间序列分析技术与方位向位移观测技术,并给出2008年矩震级Mw 7.1新疆于田地震同震、震后形变监测应用。随着宽幅SAR数据的不断积累,宽幅InSAR大地测量学有望得到深入发展与应用。     

星载InSAR在地形测绘中的误差来源分析

合成孔径雷达干涉（InSAR）技术是最有效的测图手段之一,然而InSAR地形测绘过程中极易受到各类误差的影响。本文探讨了国产SAR卫星无法业务化干涉的主要原因,并从卫星的干涉几何出发,研究了InSAR在地形测绘中的误差来源,研究表明,主星定轨误差、斜距测量误差、基线测量误差以及相位误差是地形测绘中的一级误差源。最终对一级误差带来的高程误差进行了定量分析,并对部分一级误差进行了分解,定位了二级误差源。     

InSAR技术及应用研究进展

合成孔径雷达干涉测量(InSAR)是一种快速发展的大地测量技术,能够全天候获取高精度、连续覆盖的地面高程和地表形变信息.InSAR已在地形测绘、全球环境变化、灾害监测评估等相关领域得到了广泛应用并取得了一系列成果.主要综述了近20 a来InSAR技术的发展,以及该技术在数字高程模型提取和地球科学应用中的研究进展,并对该技术的发展趋势及应用研究进行了展望.     

多分辨率分析的InSAR轨道误差去除算法

针对传统的多项式模型去除InSAR轨道误差时,只能去除由于基线不准导致的平地相位残余误差,而对于基线误差引起的与高程相关的地形相位误差仍保留在干涉图中,提出了一种多分辨率分析的干涉相位轨道误差去除方法.从InSAR成像几何结构出发,分析轨道误差的空间特征,推导了由基线误差引起的平地相位误差及地形相位误差;再通过多分辨率分析把轨道误差与对流层延迟误差相位、外部DEM引起的地形误差相位、噪声相位等进行滤除,最后采用最小二乘计算多项式模型参数,可以更精细的估计出轨道误差相位,吸收与地形相关的误差.结果表明,经过改正的干涉图与DEM的相关系数仅0.033 8,相对于线性模型和二次多项式模型的0.165 5和0.071 9,对地形相关轨道误差的去除改善程度达到79.1％和53.0％,能够更好地去除轨道误差,提高了轨道误差估计精度,吸收了与地形相关的误差.     

Completeness and classification correctness of features on topographic maps: An analysis of the estonian basic map

In an increasingly GIS‐literate world, the availability of quality topographic maps and map databases is critical for the numerous users of spatial data. Particularly governmental agencies, first responders, and utility and transportation services, rely on the completeness and classification correctness of these maps. Estonia has systematically updated its topographic Basic Map in digital form over the past 15 years. An analysis of the Estonian production process in the period 2003‐2006 provides a useful case study of both error types and error frequencies encountered in topographic mapping. Errors of completeness and classification correctness of topographic features are analyzed at two levels of specificity: in general, across all map sheets, and in detail according to the field‐workers who performed the mapping. The structure of errors at the two levels was different by geometry and error types; however, both systematic and individual errors were evident. The systematic errors indicated a need for revision and improvement of the data capture specifications, which was accomplished. The individual errors were addressed by additional training for the field‐workers involved.     

A simulation study of the errors of omission and commission for GRACE RL01 gravity fields

This paper examines the influence that certain omission and commission errors can have on the gravity field models estimated from the initial release of data (RL01) from the Gravity Recovery And Recovery Experiment (GRACE) satellite mission. The effects of omission errors were analyzed by limiting the degree and order to which the GPS and K-band range-rate (KBR) measurement partials were extended in the solution process. The commission error studies focused on the impact of an imperfect mean reference gravity field model on the solution. Combinations of both of these error sources were also explored. The nature of these errors makes them difficult to distinguish from the true gravity signal, so the exploration of these error sources was performed using simulations; however, comparisons to real-data solutions are provided. The results show how each of the specific error sources investigated influences the gravity field solution. The simulations also show how all of the errors examined can be sufficiently mitigated through the appropriate choice of processing parameters.     

Effects of national forest inventory plot location error on forest carbon stock estimation using k-nearest neighbor algorithm

This paper suggested simulation approaches for quantifying and reducing the effects of National Forest Inventory (NFI) plot location error on aboveground forest biomass and carbon stock estimation using the k-Nearest Neighbor (kNN) algorithm. Additionally, the effects of plot location error in pre-GPS and GPS NFI plots were compared. Two South Korean cities, Sejong and Daejeon, were chosen to represent the study area, for which four Landsat TM images were collected together with two NFI datasets established in both the pre-GPS and GPS eras. The effects of plot location error were investigated in two ways: systematic error simulation, and random error simulation. Systematic error simulation was conducted to determine the effect of plot location error due to mis-registration. All of the NFI plots were successively moved against the satellite image in 360° directions, and the systematic error patterns were analyzed on the basis of the changes of the Root Mean Square Error (RMSE) of kNN estimation. In the random error simulation, the inherent random location errors in NFI plots were quantified by Monte Carlo simulation. After removal of both the estimated systematic and random location errors from the NFI plots, the RMSE% were reduced by 11.7% and 17.7% for the two pre-GPS-era datasets, and by 5.5% and 8.0% for the two GPS-era datasets. The experimental results showed that the pre-GPS NFI plots were more subject to plot location error than were the GPS NFI plots. This study’s findings demonstrate a potential remedy for reducing NFI plot location errors which may improve the accuracy of carbon stock estimation in a practical manner, particularly in the case of pre-GPS NFI data.     

相位误差、位置误差和灰度误差三者关系及SAR原始图像像元不确定性

由于SAR遥感的独特优势，使它得到了广泛的应用。因此，对SAR图像的不确定性研究也越来越必要和迫切了。针对数据分析方法的不足，该文着重从机理的角度探讨SAR原始像元的不确定性。相位误差、位置误差和灰度误差三者关系、各种误差分类和综合以及这些误差对SAR原始像元不确定性作用等问题往往是困扰从机理角度对SAR图像不确定性研究的主要障碍，该文重点讨论这些问题。     

相位误差、位置误差和灰度误差三者关系及SAR原始图像像元不确定性

由于SAR遥感的独特优势，使它得到了广泛的应用。因此，对SAR图像的不确定性研究也越来越必要和迫切了。针对数据分析方法的不足，该文着重从机理的角度探讨SAR原始像元的不确定性。相位误差、位置误差和灰度误差三者关系、各种误差分类和综合以及这些误差对SAR原始像元不确定性作用等问题往往是困扰从机理角度对SAR图像不确定性研究的主要障碍，该文重点讨论这些问题。     

Ability to detect and locate gross errors on DEM matching algorithm

Abstract

Digital elevation model (DEM) matching techniques have been extended to DEM deformation detection by substituting a robust estimator for the least squares estimator, in which terrain changes are treated as gross errors. However, all existing methods only emphasise their deformation detecting ability, and neglect another important aspect: only when the gross error can be detected and located, can this system be useful. This paper employs the gross error judgement matrix as a tool to make an in-depth analysis of this problem. The theoretical analyses and experimental results show that observations in the DEM matching algorithm in real applications have the ability to detect and locate gross errors. Therefore, treating the terrain changes as gross errors is theoretically feasible, allowing real DEM deformations to be detected by employing a surface matching technique.     

Single Epoch GPS Deformation Signals Extraction and Gross Error Detection Technique Based on Wavelet Transform

IntroductionGPS technique is widely used for deformationmonitoring thanks for the high precision. Usual-ly , there are three working modes associatedwith GPS deformation observation: periodicalGPS deformation monitoring net , GPS monito-ring array and rea…     

强污染单历元GPS形变信号的提取和粗差识别

阐述了小波分析技术用于强污染GPS单历元形变信号处理的基本原理及其实现方法。以含少量粗差的低信噪比形变信号为例 ,研究了基于Mallat分解和合成算法 ,分离信号趋势项并进行粗差识别的技术。采用小波软阈值降噪的方法去除强污染数据中的随机噪声 ,降噪效果远好于中值滤波。最后对识别的粗差信息进行线性修复 ,获得了令人满意的形变信号     

GNSS形变监测中系统误差的时空相关性研究

通过大量实测数据分析了系统误差的时空变化规律,论证了具有时空相关性的双差观测值系统误差残差的存在,实现了观测值的滤波及求差,提高了分离微小形变量的精度。