Implementation of RISAT-1 Hybrid Polarimetric Decomposition Techniques and Analysis Using Corner Reflector Data

With recent advances in polarimetry, Synthetic Aperture Radar (SAR) with Hybrid–polarity architecture, a demonstration of compact polarimetry enabled larger swath coverage, reduced PRF and SAR system complexity as compared to fully polarimetric systems. The first Hybrid Polarimetric Space-borne SAR in Earth Observation orbit, India’s Radar Imaging Satellite (RISAT-1) is a new-fangled gateway to remote sensing user community for land and oceanic applications. In response to a right-circular polarized transmitted signal, based on the derived stokes vectors, Stokes parameters are estimated to produce several useful quantitative measures for generating polarimetric decomposed image. m-delta, m-chi and m-alpha polarimetric decomposition methods along with suitable weighting functions in terms of three principal components are implemented which maps Stokes parameters to RGB image space for representing odd bounce, even bounce and volume scattering targets. Various RISAT-1 Hybrid Fine Resolution Stripmap Single-Look Complex SAR datasets acquired over deployed corner reflectors at calibration site, Shadnagar have been considered over which different hybrid polarimetric decomposition techniques are implemented using in-house developed software. Further analysis produced encouraging results with standard point targets like dihedral and trihedral corner reflectors against distributed targets in the same scene to demonstrate the scattering mechanisms as per their characteristics when interacted with a polarized signal were presented in this paper.     

Global SMOS Soil Moisture Retrievals from The Land Parameter Retrieval Model

A recent study by Van der Schalie et al. (2015) showed good results for applying the Land Parameter Retrieval Model (LPRM) on SMOS observations over southeast Australia and optimizing and evaluating the retrieved soil moisture (θ in m³ m⁻³) against ground measurements from the OzNet sites. In this study, the LPRM parameterization is globally updated for SMOS against modelled θ from MERRA-Land (MERRA) and ERA-Interim/Land (ERA) over the period of July 2010–December 2010, mainly focusing on two parameters: the single scattering albedo (ω) and the roughness (h). The Pearson's coefficient of correlation (r) increased rapidly when increasing the ω up to 0.12 and reached a steady state from thereon, no significant spatial pattern was found in the estimation of the single scattering albedo, which could be an artifact of the used parameter estimation procedure, and a single value of 0.12 was therefore used globally. The h was defined as a function of θ and varied slightly for the different angle bins, with maximum values of 1.1–1.3 as the angle changes from 42.5° to 57.5°.This resulted in an average r of 0.51 and 0.47, with a bias (m³ m⁻³) of −0.02 and −0.01 and an unbiased root mean square error (ubrmse in m³ m⁻³) of 0.054 and 0.056 against MERRA (ascending and descending). For ERA this resulted in an r of 0.61 and 0.53, with a bias of −0.03 and an ubrmse 0.055 and 0.059. The resulting parameterization was then used to run LPRM on SMOS observations over the period of July 2010–December 2013 and evaluated against SMOS Level 3 (L3) θ and available in situ measurements from the International Soil Moisture Network (ISMN). The comparison with L3 shows that the LPRM θ retrievals are very similar, with for the ascending set very high r of over 0.9 in large parts of the globe, with an overall average of 0.85 and the descending set performing less with an average of 0.74, mainly due to the negative r over the Sahara. The mean bias is 0.03, with an ubrmse of 0.038 and 0.044. In this study there are three major areas where the LPRM retrievals do not perform well: very dry sandy areas, densely forested areas and over high latitudes, which are all known limitations of LPRM. The comparison against in situ measurement from the ISMN give very similar results, with average r for LPRM of 0.65 and 0.61 (0.64 and 0.59 for L3) for the ascending and descending sets, while having a comparable bias and ubrmse over the different networks. This shows that LPRM used on SMOS observations produce θ retrievals with a similar quality as the SMOS L3 product.     

Estimation of higher chlorophylla concentrations using field spectral measurement and HJ-1A hyperspectral satellite data in Dianshan Lake,China

Based on in situ water sampling and field spectral measurements in Dianshan Lake, a semi-analytical three-band algorithm was used to estimate Chlorophylla (Chla) content in case II waters. The three bands selected to estimate Chla for high concentrations included 653, 691 and 748 nm. An equation, based on the difference in reciprocal reflectance between 653 and 691 nm, multiplied by reflectance at 748 nm as [R_rs⁻¹(653) − R_rs⁻¹ (691)] R_rs(748), explained 85.57% of variance in Chla concentration with a root mean square error (RMSE) of <6.56 mg/m³. In order to test the utility of this model with satellite data, HJ-1A Hyperspectral Imager (HSI) data were analyzed using comparable wavelengths selected from the in situ data [B₆₇⁻¹(656) − B₈₀⁻¹(716)] B₈₇(753). This model accounted for 84.3% of Chla variation, estimating Chla concentrations with an RMSE of <4.23 mg/m³. The results illustrate that, based on the determined wavelengths, the spectrum-based model can achieve a high estimation accuracy and can be applied to hyperspectral satellite imagery especially for higher Chla concentration waters.     

偏振激光雷达探测大气—水体光学参数廓线

激光雷达在上层水体垂直廓线的遥感中展现出巨大优势。本文研制了一套高垂直分辨率的实时探测偏振激光雷达,提出了一种基于偏振激光雷达回波信号的反演算法,采用Fernald理论和多次散射原理反演非均匀大气—水体的衰减和退偏光学产品,以高效稳定地处理偏振激光雷达实验数据。展示了一个中国内陆水体激光雷达探测实例,观测到了两次气溶胶积聚现象和一次水体浑浊现象。对实验数据的分析表明,退偏比主要由前向多次散射和后向单次散射产生的退偏两部分组成。当多次散射强度较大时,退偏比的变化主要取决于多次前向散射退偏;反之,则主要依赖于单次后向散射退偏。     

基于RPC的TerraSAR-X影像立体定向平差模型

针对新型高分辨率雷达卫星TerraSAR-X立体像对,本文提出采用基于RPC的平差模型,通过少量的地面控制点来拟合因传感器不稳定、平台星历数据不精确及测距误差引起的影像几何畸变,从而达到精确定向目的.为验证RPC平差模型的适用性,通过在立体成像区域均匀市设人工角反射器点的方法验证其模型精度,并评估了其三维定向平差后的精...     

Scattering property based contextual PolSAR speckle filter

Reliability of the scattering model based polarimetric SAR (PolSAR) speckle filter depends upon the accurate decomposition and classification of the scattering mechanisms. This paper presents an improved scattering property based contextual speckle filter based upon an iterative classification of the scattering mechanisms. It applies a Cloude-Pottier eigenvalue-eigenvector decomposition and a fuzzy H/α classification to determine the scattering mechanisms on a pre-estimate of the coherency matrix. The H/α classification identifies pixels with homogeneous scattering properties. A coarse pixel selection rule groups pixels that are either single bounce, double bounce or volume scatterers. A fine pixel selection rule is applied to pixels within each canonical scattering mechanism. We filter the PolSAR data and depending on the type of image scene (urban or rural) use either the coarse or fine pixel selection rule. Iterative refinement of the Wishart H/α classification reduces the speckle in the PolSAR data. Effectiveness of this new filter is demonstrated by using both simulated and real PolSAR data. It is compared with the refined Lee filter, the scattering model based filter and the non-local means filter. The study concludes that the proposed filter compares favorably with other polarimetric speckle filters in preserving polarimetric information, point scatterers and subtle features in PolSAR data.     

Prediction of UT1–UTC,LOD and AAM χ<Subscript>3</Subscript> by combination of least-squares and multivariate stochastic methods

This article presents the application of a multivariate prediction technique for predicting universal time (UT1–UTC), length of day (LOD) and the axial component of atmospheric angular momentum (AAM χ ₃). The multivariate predictions of LOD and UT1–UTC are generated by means of the combination of (1) least-squares (LS) extrapolation of models for annual, semiannual, 18.6-year, 9.3-year oscillations and for the linear trend, and (2) multivariate autoregressive (MAR) stochastic prediction of LS residuals (LS + MAR). The MAR technique enables the use of the AAM χ ₃ time-series as the explanatory variable for the computation of LOD or UT1–UTC predictions. In order to evaluate the performance of this approach, two other prediction schemes are also applied: (1) LS extrapolation, (2) combination of LS extrapolation and univariate autoregressive (AR) prediction of LS residuals (LS + AR). The multivariate predictions of AAM χ ₃ data, however, are computed as a combination of the extrapolation of the LS model for annual and semiannual oscillations and the LS + MAR. The AAM χ ₃ predictions are also compared with LS extrapolation and LS + AR prediction. It is shown that the predictions of LOD and UT1–UTC based on LS + MAR taking into account the axial component of AAM are more accurate than the predictions of LOD and UT1–UTC based on LS extrapolation or on LS + AR. In particular, the UT1–UTC predictions based on LS + MAR during El Niño/La Niña events exhibit considerably smaller prediction errors than those calculated by means of LS or LS + AR. The AAM χ ₃ time-series is predicted using LS + MAR with higher accuracy than applying LS extrapolation itself in the case of medium-term predictions (up to 100 days in the future). However, the predictions of AAM χ ₃ reveal the best accuracy for LS + AR.     

Hyperion波段模拟的宽波段遥感影像一致性评价

由于外部成像环境和传感器本身设计指标的差异,不同遥感平台同一波段影像之间常常存在不一致。在多源遥感定量研究中,对外部成像环境导致的差异关注较多,而对以光谱响应函数（SRF）和空间点扩散函数（PSF）为代表的值感器本身设计指标,导致的影像不一致性（差异性）则考虑相对较少,这给后续研究结果的分析与讨论带来一定不确定性。为了提供一种全面、客观对不同遥感平台同一波段影像一致性评价方法,本文采用控制变量法的评价策略,介绍了利用Hyperion高光谱影像结合光谱响应函数模拟各种宽波段影像的方法,并将其用于多平台同一波段影像之间的一致性评价;同时在此基础上探讨了考虑PSF对高-低空间分辨率影像聚合过程的影响,为不同平台、同一波段、不同空间分辨率影像之间的一致性评价提供了技术参考。通过对常见的3种典型传感器Landsat ETM+,Terra MODIS,NOAA AVHRR 3近红外波段进行模拟、比较和一致性评价,结果表明：（1）利用本文所提出的宽波段光谱模拟方法,能较准确地模拟各种宽波段影像（在本文中平均相对误差的绝对值最大为-2.371%）,并可用于多平台同一波段影像的数据评价（从光谱响应的角度）。 （2）为了比较不同平台、同一波段、不同空间分辨率之间的差异性,可将其中高分辨率影像进行尺度上推,得到与其中低分辨率影像相同像元大小的影像,然后再进行评价。在尺度上推过程中,需先考虑PSF效应（可用高斯低通滤波模拟）,然后进行平均值聚合即可。在此基础上进行的一致性评价才是比较客观的,特别是针对异质性区域。本文所采用的评价方法不仅可为评价不同平台波段同一波段影像之间一致性提供很好的解决途径,而且为多源遥感数据选择提供了一种决策依据。     

A new calibration of the effective scattering albedo and soil roughness parameters in the SMOS SM retrieval algorithm

This study focuses on the calibration of the effective vegetation scattering albedo (ω) and surface soil roughness parameters (H_R, and N_Rp, p = H,V) in the Soil Moisture (SM) retrieval from L-band passive microwave observations using the L-band Microwave Emission of the Biosphere (L-MEB) model. In the current Soil Moisture and Ocean Salinity (SMOS) Level 2 (L2), v620, and Level 3 (L3), v300, SM retrieval algorithms, low vegetated areas are parameterized by ω = 0 and H_R = 0.1, whereas values of ω = 0.06 − 0.08 and H_R = 0.3 are used for forests. Several parameterizations of the vegetation and soil roughness parameters (ω, H_R and N_Rp, p = H,V) were tested in this study, treating SMOS SM retrievals as homogeneous over each pixel instead of retrieving SM over a representative fraction of the pixel, as implemented in the operational SMOS L2 and L3 algorithms. Globally-constant values of ω = 0.10, H_R = 0.4 and N_Rp = −1 (p = H,V) were found to yield SM retrievals that compared best with in situ SM data measured at many sites worldwide from the International Soil Moisture Network (ISMN). The calibration was repeated for collections of in situ sites classified in different land cover categories based on the International Geosphere-Biosphere Programme (IGBP) scheme. Depending on the IGBP land cover class, values of ω and H_R varied, respectively, in the range 0.08–0.12 and 0.1–0.5. A validation exercise based on in situ measurements confirmed that using either a global or an IGBP-based calibration, there was an improvement in the accuracy of the SM retrievals compared to the SMOS L3 SM product considering all statistical metrics (R = 0.61, bias = −0.019 m³ m⁻³, ubRMSE = 0.062 m³ m⁻³ for the IGBP-based calibration; against R = 0.54, bias = −0.034 m³ m⁻³ and ubRMSE = 0.070 m³ m⁻³ for the SMOS L3 SM product). This result is a key step in the calibration of the roughness and vegetation parameters in the operational SMOS retrieval algorithm. The approach presented here is the core of a new forthcoming SMOS optimized SM product.     

Mitigation of atmospheric perturbations and solid Earth movements in a TerraSAR-X time-series

The TerraSAR-X (TSX) synthetic aperture radar (SAR) marks the recent emergence of a new generation of spaceborne radar sensors that can for the first time lay claim to localization accuracies in the sub-meter range. The TSX platform’s extremely high orbital stability and the sensor’s hardware timing accuracy combine to enable direct measurements of atmospheric refraction and solid Earth movements. By modeling these effects for individual TSX acquisitions, absolute pixel geolocation accuracy on the order of several centimeters can be achieved without need for even a single tiepoint. A 16-month time series of images was obtained over a fixed test site, making it possible to validate both an atmospheric refraction and a solid Earth tide model, while at the same time establishing the instrument’s long-term stability. These related goals were achieved by placing trihedral corner reflectors (CRs) at the test site and estimating their phase centers with centimeter-level accuracy using differential GPS (DGPS). Oriented in pairs toward a given satellite track, the CRs could be seen as bright “points” in the images, providing a geometric reference set. SAR images from the high-resolution spotlight (HS) mode were obtained in alternating ascending and descending orbit configurations. The highest-resolution products were selected for their small sample dimensions, as positions can be more precisely determined. Based on the delivered product annotations, the CR image positions were predicted, and these predictions were compared with their measured image positions both before and after compensation for atmospheric refraction and systematic solid Earth deviations. It was possible to show that when the atmospheric distortion and Earth tides are taken into account, the TSX HS products have geolocation accuracies far exceeding the specified requirements. Furthermore, this accuracy was maintained for the duration of the 16-month test period. It could be demonstrated that with a correctly calibrated sensor, and after accounting for atmospheric and tidal effects, tiepoint-free geolocation is possible with TSX with an absolute product accuracy of about 5 cm.     

A four-component decomposition of POLSAR images based on the coherency matrix

A four-component decomposition scheme of the coherency matrix is presented here for the analysis of polarimetric synthetic aperture radar (SAR) images. The coherency matrix is used to deal with nonreflection symmetric scattering case, which is an extension of covariance matrix approach. The same decomposition results have been obtained. The advantage of this approach is explicit expressions of four scattering powers in terms of scattering matrix elements, which serve the interpretation of polarimetric SAR data quantitatively.     

基于Freeman散射熵和各向异性度的极化SAR影像分类算法研究

极化SAR影像中阴影、水体和裸露的耕地3种地物类型有非常相似的极化散射特性,常规基于非相干分解的分类方法难以将其有效地区分。对此,本文引入基于Freeman分解的散射熵Hf和各向异性度Af两个特征参数,并将其用于极化SAR影像分类。首先利用Hf和Af参数将阴影和水体提取出来,然后将其他地物按散射机制分为3大类,并对每一类再次利用Hf和Af参数进行细分,最后通过基于Wishart分布的聚类和迭代分类,得到最终的分类结果。通过利用Radarsat-2在河南登封获取的全极化SAR数据进行试验,表明该算法执行效率高,能够有效地区分阴影、水体和裸露的耕地,并且对其他地物类型也有很好的分类效果。     

Dynamics of chromophoric dissolved organic matter in Mandovi and Zuari estuaries — A study through in situ and satellite data

The spatial and temporal distribution of absorption of chromophoric dissolved organic matter at 440 nm (a_CDOM (440)) in the Mandovi and Zuari estuaries situated along the west coast of India, has been analysed. The study was carried out using remotely sensed data, obtained from the Ocean Colour Monitor (OCM) on board the Indian Remote Sensing satellite — P4, together with in situ data during the period January to December 2005. Satellite retrieval of CDOM absorption was carried out by applying an algorithm developed for the site. A good correlation (R=0.98) was obtained between satellite derived CDOM and in situ data. Time series analysis revealed that spatial distribution of CDOM has a direct link with the seasonal hydrodynamics of the estuaries. The effect of remnant fresh water on CDOM distribution could be analysed by delineating a plume in the offshore region of the Zuari estuary. Though fresh water flux from terrestrial input plays a major role in the distribution of CDOM throughout the Mandovi estuary, its role in the Zuari estuary is significant up to the middle zone. Other processes responsible for feeding CDOM in both the estuaries are coastal advection, in situ production and resuspension of bottom settled sediments. The highest value of a_CDOM(440) was observed in the middle zone of the Mandovi estuary during the post-monsoon season. The relation between a_CDOM(440) and S (spectral slope coefficient of CDOM) could differentiate CDOM introduced in to estuaries through multiple sources. The algorithm developed for the Mandovi estuary is S=0.003 [a_CDOM(440)^−0.7091] while for the Zuari estuary, S=0.0031 [a_CDOM(440)^−0.777], respectively.     

结合Freeman分解与子孔径散射特性的极化SAR图像分类

本文结合Freeman分解和子孔径分析,提出一种新的极化SAR图像分类算法。该方法首先利用子孔径分解,产生不同方位观察角度下的子孔径图像,再利用Freeman分解对各个子孔径图像提取三种散射机理成分的功率,平均后对类别进行细分,最后使用Wishart统计分类器对类别进行分类划分得到最终结果。该方法考虑了极化散射机理在不同方位观察角度下的变化,能够取得较好的分类效果,能够保存主要极化散射特性的纯度,同时还可以动态地设定分类类别数。最后利用EMISAR获取的极化SAR数据进行了仿真,验证了该方法的有效性。     

Correlation between ROTI and Ionospheric Scintillation Indices using Hong Kong low-latitude GPS data

The correlation between the rate of TEC index (ROTI) and scintillation indices S ₄ and σ _Φ for low-latitude region is analyzed in this study, using data collected from a Global Positioning System (GPS) scintillation monitoring receiver installed at the south of Hong Kong for the periods June–August of 2012 and May 2013 and July–December of 2013. The analysis indicates that the correlation coefficient between ROTI and S ₄/σ _Φ is about 0.6 if data from all GPS satellites are used together. If each individual satellite is considered, the correlation coefficients are above 0.6 on average and sometimes above 0.8. The analysis also shows that the ratio of ROTI and S ₄ varies between 1 and 4. The ratio ROTI/σ _Φ, varies between 2 and 9. In addition, it is also found that there is a good consistency between the temporal variations of ROTI with scintillation activity under different ionospheric conditions. ROTI has a high correlation relationship with scintillation indices on geomagnetically disturbed days or in solar active months. Moreover, the data observed at low elevation angles have weak correlation between ROTI and scintillation indices. These results demonstrate the feasibility of using ROTI derived from GPS observations recorded by common non-scintillation GPS receivers to characterize ionospheric scintillations.     

A globally applicable, season-specific model for estimating the weighted mean temperature of the atmosphere

In GPS meteorology, the weighted mean temperature is usually obtained by using a linear function of the surface temperature T _s. However, not every GPS station can measure the surface temperature. The current study explores the characteristics of surface temperature and weighted mean temperature based on the global pressure and temperature model (GPT) and the Bevis T _m–T _s relationship (T _m =?a?+?bT _s). A new global weighted mean temperature (GWMT) model has been built which directly uses three-dimensional coordinates and day of the year to calculate the weighted mean temperature. The data of year 2005–2009 from 135 radiosonde stations provided by the Integrated Global Radiosonde Archive were used to calculate the model coefficients, which have been validated through examples. The result shows that the GWMT model is generally better than the existing liner models in most areas according to the statistic indexes (namely, mean absolute error and root mean square). Then we calculated precipitable water vapor, and the result shows that GWMT model can also yield high precision PWV.     

一种改进的精制极化Lee滤波算法

为克服精致极化Lee滤波算法对极化信息保持不够理想的弊端,本文提出一种改进方法.其基本思路是先应用四分量分解算法将像素分成4种散射类型,然后在方向窗口内去除与中心像素散射特性不同的像素,最后基于同质区的局部统计特性进行滤波处理.试验表明,改进后的滤波算法较传统算法有更强的极化信息保持能力.     

星载微波SSM/Ⅰ遥感在中国东北华北农田的辐射特征分析

国家遥感应用工程技术研究中心ＮａｔｉｏｎａｌＥｎｇｉｎｅｅｒｉｎｇＲｅｓｅａｒｃｈＣｅｎｔｅｒｆｏｒＧｅｏｍａｔｉｃｓ（ＮＣＧ）国家遥感应用工程技术研究中心于１９９６年１２月２５日由国家科委正式批准组建（国科发计字［１９９６］６０３号文件）。中国科学...     

Improved amplitude- and phase-scintillation indices derived from wavelet detrended high-latitude GPS data

Accuracy and validity of scintillation indices estimated using the power and phase of the GPS signal depend heavily on the detrending method used and the selection of the cutoff frequency of the associated filter. A Butterworth filter with a constant cutoff frequency of 0.1?Hz is commonly used in detrending GPS data. In this study, the performance of this commonly used filter is evaluated and compared with a new wavelet-based detrending method using GPS data from high latitudes. It was observed that in detrending high-latitude GPS data, a wavelet filter performed better than Butterworth filters as the correlation between amplitude- and phase-scintillation indices in S ₄ and ?? _? improved significantly from 0.53, when using a Butterworth filter, to 0.79, when using the wavelet filtering method. We also introduced an improved phase-scintillation index, ?? _CHAIN, which we think is comparatively a better parameter to represent phase scintillations at high latitudes as the correlation between S ₄ and ?? _CHAIN was as high as 0.90. During the analysis, we also noted that the occurrence of the ??phase scintillation without amplitude scintillation?? phenomenon was significantly reduced when scintillation indices were derived using the wavelet-based detrending method. These results seem to indicate that wavelet-based detrending is better suited for GPS scintillation signals and also that ?? _CHAIN is a better parameter for representing GPS phase scintillations at high latitudes.     

The Gauss–Listing geopotential value W 0 and its rate from altimetric mean sea level and GRACE

In geopotential space, the fundamental geodetic parameter W ₀ defines the Gauss–Listing geoid which can be used to best represent the Earth’s mean sea level (MSL) and hence specifies a conventional zero height level to unify vertical datums employed by mapping agencies throughout the world. Further, W ₀ cannot be considered invariant as the parameter varies temporally as a direct response to sea level change and mass redistributions. This study determines W ₀ and its rate, dW ₀/dt, by utilizing altimetric MSL models and an independent mean dynamic topography (MDT) model to define points on the geoid. W ₀ and dW ₀/dt are estimated by two approaches: (i) by means of a global gravity field model (GGM) and (ii) within normal gravity field space as the geopotential value of the best fitting reference ellipsoid. The study shows that uncertainty in W ₀ is mainly influenced by MDT while the choice of methodology, GGM and MSL data coverage are not significant within reason. Our estimate W ₀ =?62636854.2 ± 0.2 m²?s^?2 at epoch 2005.0 differs by 1.8?m²s^?2 from the International Astronomical Union reference value. This study shows that, at a sub-decadal time scale, the time variation dW ₀/dt stems mainly from sea level change with negligible effect from gravity field variations. dW ₀/dt =?(?2.70 ± 0.03)?×?10^?2?m²?s^?2?year^?1, corresponding to a MSL rise of 2.9?mm?year^?1, is evaluated from sea level change based on 16?years of TOPEX and Jason-1 data.