基于GPS和大气传输模型的InSAR大气改正方法研究

利用GPS数据改正InSAR大气影响中,GPS站网的低空间密度是限制改正精度的一个主要因素.文中引入大气传输模型（ATM）来考虑大气状态在时间上的演化,并兼顾了风向的估计,把GPS-ZWD（GPS湿延迟）时间序列观测值转换为空间上分布比较稠密的GPS-ZWD网络,然后利用该稠密网络在空间上内插产生水汽延迟图,来更好地模拟InSAR影像获取时刻的水汽场,提高大气改正精度.实验结果表明,在研究地区有限的数据条件下（即只有6个GPS点的情况下）,GPS+ATM算法在重现大气信号能力方面比单纯的使用影像获取时刻的GPS-ZWD数据要强,并且其对长波的大气误差去除更明显;用来做实验的三幅差分干涉图中,GPS+ATM算法对两幅以长波信号为主的干涉图中的大气影响分别降低了21.7%和22.6%,比仅使用SAR过境时刻GPS-ZWD数据时的结果分别改进了4.5%和8.7%.而对以短波信号为主的干涉图没有明显提高.     

利用MERIS水汽数据改正ASAR干涉图中的大气影响

大气对流层对雷达信号的传播延迟是制约重复轨道InSAR高精度测量应用的重要因素之一.本文描述了MERIS水汽数据用于ASAR干涉图大气改正的方法;并以美国南加州地区为例,选取4对ENVISAT ASAR数据进行了大气改正的研究.结果显示对这4幅干涉图,经过MERIS水汽数据改正后InSAR与GPS差异的RMS分别〖JP2〗降低了41.7%,65.2%,19.3%和39.4%.平均改善程度达41.4%.更重要的是,经过MERIS水汽改正后,从2005~2007年〖JP〗干涉图和2004~2007年干涉图中,能清楚地识别出三处形变最明显的区域：Long Beach-Santa Ana 盆地、Pomona-Ontario和San Bernardino,其形变速率从-8 mm/a到-28 mm/a,大部分在-20 mm/a左右,与这些地区2003年以前的历史形变速率基本一致.因此,采用无云条件下的MERIS水蒸汽数据改正同步获取的ASAR干涉图,可以显著地降低大气水汽对干涉图相位的影响,从而更真实地反映地表形变等地球物理信号.     

高光谱遥感数据的改正暗目标大气校正方法研究

高光谱遥感数据常用的大气校正方法均侧重于去除水汽及其他吸收气体的影响, 主要研究了从高光谱影像同时去除气溶胶与水汽影响的方法. 由于高光谱遥感数据波段众多, 常规暗目标方法一直难以适用于高光谱遥感数据的大气校正. 通过选取小麦作为新的暗目标对象, 着重讨论了使用多波段线性回归与插值的方法对常规暗目标方法进行改正使之充分利用高光谱的众多波段特性, 从而把改进的暗目标方法扩展应用于高光谱遥感数据的大气校正. 为了同时去除大气中水汽的影响, 大气校正全过程采用了循环迭代的算法. 以山东济宁地区EO-1卫星搭载的Hyperion高光谱数据为应用实例, 通过使用MODTRAN建立的查找表直接从影像估算出气溶胶与水汽含量, 实现了对该数据的大气校正. 大气校正的结果表明, 改正暗目标大气校正算法可以有效地对高光谱遥感数据进行大气校正.     

InSAR大气误差改正及其在活动断层形变监测中的应用

为了获取青藏高原东北缘老虎山断裂带精确的震间形变速率场,通过对短时间基线干涉图大气改正效果的评价,从3种外部大气数据(MERIS, ERA-Ⅰ, WRF)中确定出最优的大气改正方法,用于长时间基线干涉图中的大气信号改正;然后利用层叠法(stacking)累积平均经大气和轨道改正后的干涉图,获取了研究区的震间形变速率场.结果显示:海原断裂系统区域内,MERIS和ERA-Ⅰ的大气改正效果优于WRF;MERIS和ERA-Ⅰ的改正结果给出了相似的形变速率场,断层两盘相对形变速率为视线向2.5 mm/a,转换成平行于断层方向为6.5 mm/a,与GPS结果一致;在近断层5 km的范围内,出现了较大的形变梯度,揭示了浅层蠕滑的存在.      

基于MERIS水汽数据的ASAR干涉图改正

水汽延迟是InSAR技术的重要误差源,已成为高精度差分干涉测量的主要限制.本文比较分析了GPS与MERIS可降水量反演结果以及水汽变化量探测结果,研究发现两者探测到的水汽含量和水汽变化量均存在较好一致性.在此基础上,以南加州地区为例验证了差分MERIS PWV用于同步ASAR干涉图水汽改正的可行性,经过水汽改正干涉图质量提高了约23%,并进一步对比了InSAR形变监测结果与GPS探测到的形变,比较结果表明,消除水汽影响后干涉图形变结果可靠性提高了19%.     

利用ENVISAT/AATSR资料反演黄土高原陇东地区地表温度

由于ENVISAT/AATSR资料不同角度热辐射亮度值之间存在较高的相关性从而导致较大误差的产生,本文尝试避开这种误差源,只选取天底观测数据对黄土高原陇东地区整层大气水汽含量及地表温度进行反演.与MODIS整层大气水汽含量产品对比验证表明,本文结果与MODIS产品有一定差异,但是可以直接用于大气透过率的估算.结合野外观测数据对地表温度反演结果的检验表明,最大绝对误差为4.0 ℃,平均相对误差为5.0％,因此,该算法在黄土高原陇东地区应用比较成功.     

利用HJ-1B热红外数据估算晴天大气下行长波辐射

针对HJ-1B红外相机只有一个热红外通道的特点,本文利用大气辐射传输模型模拟和统计回归方法,发展了一个利用HJ-1B辐射亮温和大气水汽含量反演高分辨率大气下行长波辐射的参数化模型.为了分析模型的适宜性和误差来源,利用模拟数据对模型进行了精度评价,结果表明模型在大多数气候条件下反演结果较好,但在大气水汽含量较高时存在低估现象.误差分析表明,大气水汽含量、传感器辐射亮度、地表与大气的温差等方面的不确定性会对反演结果产生一定的影响.利用2009~2010年HJ-1B数据反演得到黑河流域和海河流域的瞬时下行长波辐射,并利用6个站点的地面观测数据对反演结果进行了验证.结果表明,除花寨子荒漠站外,其他各站点反演值与实测值的一致性较好,均方根误差在20W/m2左右,略好于MODIS数据的反演结果.花寨子站夏季时存在较多的高估现象,主要由地气温差过大引起,经过地气温差校正后,结果得到明显改善.     

一种InSAR大气相位建模与估计方法

为了削弱大气延迟对干涉结果的影响以提高InSAR的测量能力,本文在InSAR大气相位特征分析的基础上,研究了一种新的InSAR大气相位建模与估计方法.首先采用稳健估计确定大气垂直分层部分的模型参数,然后利用基于Matern模型的Kriging插值估计大气紊流部分,最后应用估计的大气垂直分层和紊流资料改正InSAR测量结果.利用覆盖河南义马地区的ASAR数据对本文提出的方法进行了验证,结果表明去除大气影响后,InSAR重建的DEM与参考DEM的高程差异的均方误差由19.5m降至5.3m,精度提高了约72%.同时,改正后的干涉图更合理地揭示了义马矿区的沉降漏斗情况,进一步验证了本文方法的有效性.     

GPS大气掩星技术在全球气候变化研究中的应用

人类活动引起全球变暖,衡量全球气候变化的指标有陆地、大气和海洋温度,水汽含量等等.研究对流层底层大气温度和水汽含量变化的传统方法是用数值天气预报模型和微波声纳,尚未实现用全球均匀覆盖的数据来做精确的定量研究.和GNSS系列卫星计划比较,最近发射的COSMIC卫星气象探测数据的空间、时间以及垂直分辨率都大大提高.采用COSMIC数据可以改进和量化南极洲的大气压力模型,并综合GNSS系列卫星测量的水汽和温度剖面研究全球气候变化.用一维协方差算法估计南极洲及附近海洋的大气压、温度和湿度剖面.把COSMIC卫星密集测量期间演算得到的大气折射率和GNSS系列卫星的结果进行比较.再和独立测量数据进行比较,包括南极洲自动气象观测站资料,数值天气预报模型资料,多种测高卫星水汽资料和海洋表面温度资料以及区域GPS水汽图.上述工作将改进发展中的气象遥感技术并应用于天气预报和空间天气预报及全球气候变化研究.     

基于MODIS晴空数据的森林日净第一性生产力估算

基于光能利用率模型提出了一个基于MODIS数据参数反演的日净第一性生产力估算模型. 其中包括基于植被冠层叶面积指数和地表反照率的光合有效辐射比例能量平衡模型, 基于大气气溶胶光学厚度、水汽含量和Bird模型相结合的光合有效辐射计算模型. 日净第一性生产力模型所需的主要参数从MODIS数据反演获得. 为了验证净第一性生产力结果的估算精度, 用中国生态系统研究网络2003和2004年千烟洲和长白山观测站点的日净第一性生产力观测数据和模型估算结果对比, 结果表明两者具有较好的一致性. 同时也将同期NASA的净第一性生产力产品加以对比, 结果表明千烟洲站点上2004年的NASA产品低估了净第一性生产力值, 但长白山站则高估了净第一性生产力结果.     

Variability of GPS derived water vapor and comparison with MODIS data over the Indo-Gangetic plains

The water vapor is one of the important constituents of the atmosphere that affects the thermodynamics of the atmosphere and has direct impact on the weather conditions. The total column atmospheric water vapor, obtained from Global Positioning System (GPS) and Moderate Resolution Imaging Spectroradiometer (MODIS), is found to be very dynamic over the Indo-Gangetic (IG) plains. In this paper, we present an analysis of GPS data recently deployed (as of May 2007) on the campus of Banaras Hindu University, Varanasi (latitude 25°15′N, longitude 82°59′E). Further, we have compared the variability of water vapor from Kanpur GPS, AERONET and MODIS water vapor data for the year 2007. The monthly variability of water vapor shows characteristic features and dynamics of water vapor between two closely spaced GPS stations, found to be controlled by monsoon dynamics and wind pattern.     

Physical statistical algorithm for precipitable water vapor inversion on land surface based on multi-source remotely sensed data

Water vapor plays a crucial role in atmospheric processes that act over a wide range of temporal and spatial scales, from global climate to micrometeorology. The determination of water vapor distribution in the atmosphere and its changing pattern is very important. Although atmospheric scientists have developed a variety of means to measure precipitable water vapor(PWV) using remote sensing data that have been widely used, there are some limitations in using one kind satellite measurements for PWV retrieval over land. In this paper, a new algorithm is proposed for retrieving PWV over land by combining different kinds of remote sensing data and it would work well under the cloud weather conditions. The PWV retrieval algorithm based on near infrared data is more suitable to clear sky conditions with high precision. The 23.5 GHz microwave remote sensing data is sensitive to water vapor and powerful in cloud-covered areas because of its longer wavelengths that permit viewing into and through the atmosphere. Therefore, the PWV retrieval results from near infrared data and the indices combined by microwave bands remote sensing data which are sensitive to water vapor will be regressed to generate the equation for PWV retrieval under cloud covered areas. The algorithm developed in this paper has the potential to detect PWV under all weather conditions and makes an excellent complement to PWV retrieved by near infrared data. Different types of surface exert different depolarization effects on surface emissions, which would increase the complexity of the algorithm. In this paper, MODIS surface classification data was used to consider this influence. Compared with the GPS results, the root mean square error of our algorithm is 8 mm for cloud covered area. Regional consistency was found between the results from MODIS and our algorithm. Our algorithm can yield reasonable results on the surfaces covered by cloud where MODIS cannot be used to retrieve PWV.     

A Quantitative Assessment of DInSAR Measurements of Interseismic Deformation: The Southern San Andreas Fault Case Study

We investigate the capabilities and limitations of the Differential Interferometric Synthetic Aperture Radar (DInSAR) techniques, in particular of the Small BAseline Subset (SBAS) approach, to measure surface deformation in active seismogenetic areas. The DInSAR analysis of low-amplitude, long-wavelength deformation, such as that due to interseismic strain accumulation, is limited by intrinsic trade-offs between deformation signals and orbital uncertainties of SAR platforms in their contributions to the interferometric phases, the latter being typically well approximated by phase ramps. Such trade-offs can be substantially reduced by employing auxiliary measurements of the long-wavelength velocity field. We use continuous Global Positioning System (GPS) measurements from a properly distributed set of stations to perform a pre-filtering operation of the available DInSAR interferograms. In particular, the GPS measurements are used to estimate the secular velocity signal, approximated by a spatial ramp within the azimuth-range radar imaging plane; the phase ramps derived from the GPS data are then subtracted from the available set of DInSAR interferograms. This pre-filtering step allows us to compensate for the major component of the long-wavelength range change that, within the SBAS procedure, might be wrongly interpreted and filtered out as orbital phase ramps. With this correction, the final results are obtained by simply adding the pre-filtered long-wavelength deformation signal to the SBAS retrieved time series. The proposed approach has been applied to a set of ERS-1/2 SAR data acquired during the 1992–2006 time interval over a 200?×?200?km area around the Coachella Valley section of the San Andreas Fault in Southern California, USA. We present results of the comparison between the SBAS and the Line Of Sight (LOS)—projected GPS time series of the USGC/PBO network, as well as the mean LOS velocity fields derived using SBAS, GPS and stacking techniques. Our analysis demonstrates the effectiveness of the presented approach and provides a quantitative assessment of the accuracy of DInSAR measurements of interseismic deformation in a tectonically active area.     

Atmospheric effects on repeat-pass InSAR measurements over Shanghai region

It is well known that interferometric synthetic aperture radar (InSAR) measurements are affected by the atmosphere especially the troposphere. We use Shanghai as an example to analyze the properties of the effects based on a number of SAR interferograms over the region. First, Radon transform is used to examine the isotropic property of the effects. The results show that the effects in all the interferograms are anisotropic although they exhibit different patterns. Two different methods, the Jarque-Bera and the Hinich tests, are then applied to test the Gaussianity of atmospheric effects. Both of the tests reveal that the atmospheric effects are non-Gaussian. Finally, spectral analysis of the atmospheric effects is carried out and the results show that the power spectra of the atmospheric signatures in all the interferograms studied follow approximately the power law distribution. The scaling exponents estimated show that the atmospheric signatures in all the interferograms are non-stationary but with stationary increments. It is estimated based on the estimated scaling exponents that external data with spatial resolutions as high as about 0.3 km, are required to determine and correct for over 90% of the atmospheric effects in the SAR interferograms.     

内蒙古乌梁素海“黄苔”暴发卫星遥感动态监测

通过综合分析"黄苔"、芦苇、明水体和陆地等地物在EOS/MODIS图像上不同波段的光谱特征,提出了利用EOS/MODIS可见光、近红外波段数据提取"黄苔"信息的方法.结合乌梁素海"黄苔"实地考察资料和高空间分辨率的中巴资源卫星CBERS/CCD数据对MODIS数据监测"黄苔"的结果进行了比对验证.研究结果表明,本文提出的方法可以对"黄苔"进行有效的监测.同时提出了简单可行的去除程辐射影响的大气校正方法,利用MODIS 2008年5-10月的数据对内蒙古乌梁素海的"黄苔"灾情进行了动态监测,获得了乌梁素海"黄苔"灾情发生发展的特征信息,乌梁素海在2008年5月初开始出现"黄苔",6-7月份发生大面积"黄苔"暴发,进入8月以后"黄苔"开始逐渐消退,10月份基本消失,并初步分析了"黄苔"暴发的原因.     

Signature of atmospheric oscillations in GPS-measured tropospheric delay

Ground-based GPS finds potential applications in many atmospheric studies such as spatial distribution of columnar water vapor as well as the tidal oscillations in the atmosphere. The zenith tropospheric delay (ZTD) derived from GPS data at two Indian IGS stations are used to establish its potential for studying the atmospheric tidal, intra-seasonal and planetary oscillations. The major tidal oscillations observed in ZTD data are diurnal, semi-diurnal and their harmonics. Prominent intra-seasonal oscillations observed in ZTD are reported for the first time in this context. These intra-seasonal oscillations are Madden–Julian Oscillation (30–70 days, 60–90 days, 100–120 days) and planetary waves (like 27, 16 and 5–10 days periodicities). Quantification of these periodicities will provide a useful handle to improve the empirical models employed in the estimation of tropospheric delay.     

雷达干涉PS网络的基线识别与解算方法

时序雷达干涉图中的永久散射体(PS)可看作“天然GPS点”, 以构成网络用于监测长期的地表形变. 本文提出采用邻接矩阵拓扑模型对基于Delaunay剖分算法生成的PS网络进行基线识别, 并采用时序相干最大化算法求解PS基线的线性形变速度增量和高程误差增量. 该数据模型和计算方法被应用于探测香港地区2006~2007年间的区域地表沉降. 实验研究采用由Envisat卫星ASAR传感器对该地区成像所获取的时序SAR影像作为数据源, 并联合该地区12个GPS连续运行参考站的观测数据予以大气修正和地面控制. 实验结果表明, 该模型和方法应用于地表形变测量是有效的和可靠的, PS网络方法探测地面沉降的精度约为±2.0 mm/a.     

基于全球气象再分析资料的InSAR对流层延迟改正研究

气压、温度和水汽含量等大气物理参数的时空变化导致的对流层延迟是制约合成孔径雷达干涉测量(Interferometric Synthetic Aperture Radar,InSAR)高精度应用的重要因素之一.最新研究显示气象再分析资料在补偿对流层延迟影响方面具有巨大的应用潜力,这促使我们对其有效性和鲁棒性做进一步的研究和探索.本文首先推导了利用气象再分析资料对InSAR进行对流层延迟校正的算法;然后以美国南加州地区的ENVISAT ASAR数据为例,分析了基于两种气象再分析资料(ERA-Interim和North American Regional Reanalysis,NARR)校正InSAR对流层延迟改正的效果;通过与MERIS水汽延迟改正结果比较,验证了该方法的有效性.实验结果表明:(1)不能简单忽略干延迟,可通过气象再分析资料进行有效估计;(2)通过与MERIS水汽产品获得的对流层延迟比较发现,气象再分析资料能够取得接近于MERIS的改善效果;(3)对ERA-Interim和NARR两种气象再分析资料而言,虽然后者具有更高的时间和空间分辨率,但在改正InSAR对流层延迟方面并没有表现出比前者更明显的优势;(4)气象再分析资料可以很好地估计与地形强相关的垂直分层延迟,但对于小尺度的湍流混合延迟的捕捉能力有限.综合分析认为,气象再分析资料的优势在于其数据可随时获得、免费和全球覆盖,它可以显著减弱大尺度的垂直分层延迟对干涉图相位的影响,从而有助于InSAR获取更真实可靠的地形高程和地表形变信息.