一种扩展的基于结构检测的最优多视极化SAR相干斑滤波算法

全极化数据的可得,使得利用极化散射矩阵以减少多视全极化SAR图像中的相干斑成为了可能。其中,被称为最优的多视极化白化滤波器（MPWF）就是一个典型例子。然而,为提高滤波器参数估计的精度,同时能够自适应的检测图像中的结构特征,在滤波时采用适当的窗算法是必要的。本文提出了两个有效的窗算法,并用1994年NASA SIR-C/X-SAR,L band,经过四视处理的天山森林的极化数据进行了仿真。实验结果表明,这两种算法不仅很好的达到了降噪效果,而且对图像的纹理信息以及结构特征（即边缘特征、线性特征、强散射体特征）的保持效果是最佳的。     

利用平地干涉相位进行INSAR初始基线估计

INSAR技术是最有潜力获取高精度DEM的手段之一。在其关键技术中,基线估计是影响最终DEM精度的一个关键因素。通常,较小的基线估计误差将会导致获取的DEM中存在较大的斜坡效应。但是,对于境外等难以获取地面控制点的区域,很难精确地估计出基线参数,从而使获取的DEM误差很大。针对这种情况,从INSAR的基本原理入手,提出了一种新的利用平地干涉相位进行初始基线估计的方法。利用1994年美国NASA航天飞机SIR-C/X-SAR数据和中国科学院电子所机载双天线干涉数据进行了实验,结果表明:该方法适用于无控制地区的基线估计,它无需地面控制点,并且估计出的基线参数比较精确。     

Retrieval of soil moisture using SIR-C polarimetric data

Spaceborne Imaging Radar (SIR-C) polarimetric data acquired over Gujarat test site, India, during April and October 1994 were processed to retrieve soil moisture and surface roughness using multi-polarization techniques. Synchronous field data were collected and compared with the results obtained using SIR-C data. Indian Remote Sensing Satellite (IRS) images in visible region were used for locating groundtruth points. Multi-polarization inversion techniques are found to be sensitive to retrieval of soil moisture and surface roughness parameters. However, the accuracy is not adequate. There is a need to improve the existing inversion models to suit to the Indian agricultural fields.     

利用航天飞机成象雷达干涉数据提取数字高程模型

首先介绍干涉雷达 (INSAR)成象原理和处理方法 ,接着介绍了二维离散包缠 (wrapped)干涉相位纹图的解缠 (unwrapping)算法。利用航天飞机成象雷达 (SIR -C) 1994年 10月获取的昆仑山干涉数据 ,研究了SIR -CINSAR获取数字高程模型的方法 ,显示了INSAR在三维信息获取和动态监测方面的优越性和应用前景     

航天多波段全极化干涉雷达的地物探测

航天飞机成象雷达 3号及X波段合成孔径雷达 (SIR -C/X -SAR)计划是一项包括中国在内有 13个国家合作进行的大型雷达对地观测研究计划。SIR -C/X -SAR具有L、C、X3个波段及L、C波段HH ,HV ,VH ,VV极化 ,X波段VV极化同时成象的能力 ,可获得全极化及干涉雷达数据 ,是本世纪内最先进的航天成象雷达系统。该文系统介绍了SIR -C/X -SAR中国项目开展以来取得的研究成果。重点阐述了中国雷达试验区及与SIR -C/X -SAR成象飞行同步开展的航天—航空—地面立体同步观测试验和对干沙的穿透性试验 ,以及在相关领域和不同地区的应用 ,包括昆仑山火山群的发现 ,广东肇庆植被覆盖区地质体的识别 ,明、隋两代长城的探测与极化响应分析 ,海洋及城市特征研究 ,并介绍了利用干涉雷达数据生成数字地形模型的结果     

基于神经网络方法的极化雷达地表参数反演

人工神经网络（Artificial Neural Network)是一个由独立处理单元以一定拓扑结构高度连接而成的并行分布式信息处理结构，适于解决各种非线性问题，积分方程（Integrated Equation Model)单散射模型可模拟各种地表参数条件下裸露地表后向散射系数，以IEM为基础生成训练数据，用L波段的C波段SIR-CHH，VV极化单散射后向散射系数数据为神经网络输入，通过后向反馈（BP）神经网络模型可同时反演得到裸露地表条件下地表介电常数，地表相关长度和均方根高度等地表参数。     

Discriminating lava flows of different age within Nyamuragira’s volcanic field using spectral mixture analysis

In this study, linear spectral mixture analysis (LSMA) is used to characterize the spectral heterogeneity of lava flows from Nyamuragira volcano, Democratic Republic of Congo, where vegetation and lava are the two main land covers. In order to estimate fractions of vegetation and lava through satellite remote sensing, we made use of 30 m resolution Landsat Enhanced Thematic Mapper Plus (ETM+) and Advanced Land Imager (ALI) imagery. 2 m Pleiades data was used for validation. From the results, we conclude that (1) LSMA is capable of characterizing volcanic fields and discriminating between different types of lava surfaces; (2) three lava endmembers can be identified as lava of old, intermediate and young age, corresponding to different stages in lichen growth and chemical weathering; (3) a strong relationship is observed between vegetation fraction and lava age, where vegetation at Nyamuragira starts to significantly colonize lava flows ∼15 years after eruption and occupies over 50% of the lava surfaces ∼40 years after eruption. Our study demonstrates the capability of spectral unmixing to characterize lava surfaces and vegetation colonization over time, which is particularly useful for poorly known volcanoes or those not accessible for physical or political reasons.     

合成孔径雷达影象提取雪盖信息研究

在分析合成孔径雷达（ＳＡＲ）成象机理及雪盖参数散射特性的基础上，利用航天飞机承载的成象雷达（ＳＩＲ—Ｃ）获取的多波段、多极化ＳＡＲ数据，进行提取雪盖信息的实验。结果表明Ｃ波段ＨＨ、ＶＶ影象能很好地区别湿雪与非雪盖区，而区分干雪与岩石较困难；Ｌ波段ＨＨ、ＶＶ影象较容易将雪盖同其它物体区分开；Ｃ、Ｌ波段的交叉极化ＨＶ、ＶＨ区分干雪与岩石效果很好。故利用多波段、多极化ＳＡＲ进行雪盖制图是可行的。     

基于PALSAR数据的DEM提取方法研究

针对PALSAR Level 1.1数据,研究使用NASA/JPL提供的开源干涉软件包ROI_PAC Version 3.0提取DEM.ROI_PAC的目前版本只能处理Level 1.0数据,因此,文章在分析了ROI_PAC软件包处理流程的基础上,提出处理Level 1.1数据的方法,并用PALSAR Level 1.1数据对该方法做了验证.干涉重建DEM与参考DEM的对比结果表明,二者的差异均值为0.27 m,标准差为±9.24 m,80%像元点的高程误差在±10 m以内.     

航天飞机SIR—C数据对内蒙古额济纳旗北部浅层地下水的探测分析

利用航天飞机3号SIR-C数据对额济纳旗北部中-蒙交界处浅层地下水的分布与形成原因进行研究，分析了在SIR-C图像上呈亮条带的机理，研究得出如下结论：（1）浅层地下水区能被ISR-C图像特别是L-HV以及L-HH极化以亮黄色强烈显示，这是与该带地下水位浅，植被长势好，植被固沙形成沙垄等因素造成雷达波体散射以及后向散射强烈所致；（2）在研究区的中-蒙交界段正是地形由缓向陡转折处，这是与拉张正断层原因导致中方上盘相对下降，并在此处具备储水条件有关。（3）雷达遥感能敏感地探测到微地形的变化，可很好地反映地表植被分布和地表及次地表水分，使其在干旱区应用研究具有极大的优势，此研究可能为西部干旱区寻找浅层地下水提供一条快捷，实用的方法。     

A study on the polarimetric properties of various features using SIR-C data

Spaceborne Imaging Radar (SIR-C) data acquired over Gujarat, India in 1994 were processed and analysed using differnet techniques applicable to polarimetric SAR data such as polarization signatures, polarization index, decomposition of the signal and polarization phase difference and limited groundtruth data. It has been observed that multi-frequency polarimetric data enhances the potential of retrieving geo-physical parameters. The polarization signatures are found to vary with the nature of the target. Target decomposition of the returned signal will be useful for the classification of various features. Polarization Phase Difference (PPD) gives good information about the vegetation parameters.     

Unsupervised Change Detection From Multichannel SAR Images

Multichannel synthetic aperture radar (SAR) data present a good potential for environmental monitoring and disaster management, owing both to their insensitivity to atmospheric and sun-illumination conditions, and to the improved discrimination capability they may provide as compared to single-channel SAR. However, this requires accurate and possibly automatic techniques to generate change maps from multichannel SAR images acquired from the same geographic area at different times. In this letter, an automatic unsupervised contextual change-detection method is proposed for two-date multichannel SAR images, by integrating a SAR-specific extension of the Fisher transform with a variant of the expectation-maximization algorithm and with Markov random fields. The method is validated by experiments on SIR-C/XSAR data     

全极化SAR数据在地表覆盖/利用监测中的应用

SIR-C/X-SAR是运行在地球轨道上的第一个多波段(L、C、X)全极化(HH、VV、VH和HV)成像雷达系统,该系统具有极化测量和干涉测量功能。全极化雷达测量每一个像元的全散射矩阵,所获取的信息非常丰富。但是,由于这些极化合成图像具有较高的相关性,导致了图像信息提取精度的降低。本文基于新疆和田地区的SIR-CL波段全极化雷达数据,利用全散射矩阵的特点合成了HH-VV极化相关图像、极化度图像、目标增强图像和相位差图像。这些图像相关性小,地表覆盖信息丰富,提高了全极化SAR数据在实验区信息提取的准确度。     

利用SIR-C极化数据提取地面参数

本文根据简化的积分公式模型（ＩＥＭ）,分析了面散射过程中后向散射系数与地面参数之间的关系。利用航天飞机成像雷达（ＳＩＲ－Ｃ）获取极化的雷达图像,提取新疆北部地区冲扇的散射系数以及介电常数（湿度）与粗糙度。由图像获得的地面参数数据,可以用于分布冲积扇成因、时代以及其次的关系。     

The inversion method study of sub-canopy soil moisture estimation using repeat pass SIR-C PolInSAR data

From repeat pass SIR-C L band polarimetric SAR interferometric data and fully maximum likelihood inversion decomposition model of PolInSAR, a method for sub-canopy soil moisture estimation using repeat pass SIR-C PolInSAR data is proposed. At the same time, the potential and validity of fully maximum likelihood inversion decomposition model of PolInSAR for sub-canopy soil moisture inversion is investigated. Firstly, from the random oriented volume over ground two layer coherent scattering model and the statistical characteristics of Pol-InSAR coherency matrix, the fully maximum likelihood inversion decomposition model is used to reconstruct or recover the surface polarimetric coherency matrix with volume scattering components significantly removed; then, from recovered surface polarimetric coherency matrix, co-HH, VV and cross-HV polarization backscattering coefficient are obtained, and the sub-canopy soil moisture are inverted from Oh and Dihedral scattering model. At last, Compared the inversion result with the field measurement and the climate data of hetan region from 1951 to 2006, the preliminary result indicates that the proposed method based on fully maximum likelihood inversion decomposition model has enough high inversion accuracy, if the new spaceborne or airborne polarimetric SAR interferometric data with synchronously spaceborne or airborne-ground measurement will be acquired, the validity and accuracy of proposed inversion method will be further investigated and validated.     

基于MODIS影像的森林火灾火线检测方法

结合归一化火灾差异指数NDBR(normalized difference burn ratio)和MODIS多波段影像梯度边缘分析手段检测火线, 应用B样条函数拟合火线并确定火势蔓延方向。为对比验证, 基于火线的Kriging插值实现火灾外推预测, 与30min后的火灾参考数据目视对比与统计：火线的预测变化与参考影像基本保持一致, 火灾外推影像的均值和熵约为参考影像的86%和81%, 火迹地检测的Kappa系数达80.2%。试验表明, 提出的森林火线特征自动检测方法在动态火灾监测中是可行、有效的。     

Spectral properties of volcanic materials from hyperspectral field and satellite data compared with LiDAR data at Mt. Etna

Spectral properties of volcanic materials in the optical region (350–2500 nm) of the electromagnetic spectrum are analyzed. The goal is to characterize air-fall deposits, recent lava flows, and old lava flows based on their spectral reflectance properties and on the textural characteristics (grain size) of pyroclastic deposits at an active basaltic volcano. Data were acquired during a spectroradiometric field survey at Mt. Etna (Italy) in summer 2003 and combined with hyperspectral satellite (Hyperion) and airborne LiDAR (Light Detection and Ranging) data. In addition, air-fall deposits produced by the highly explosive 2002–2003 eruption have been sampled and spectrally characterized at different distances from the new vents. The spectral analysis shows that air-fall deposits are characterized by low reflectance values besides variations in grain size. This distinguishes them from other surface materials. Old lava flows show highest reflectance values due to weathering and vegetation cover. The spectral data set derived from the field survey has been compared to corrected satellite hyperspectral data in order to investigate the Hyperion capabilities to differentiate the surface cover using the reflectance properties. This has allowed us to identify the 2002–2003 air-fall deposits in a thematic image just few months after their emplacement. Moreover, the observed differences in the field spectra of volcanic surfaces have been compared with differences in the signal intensity detected by airborne LiDAR survey showing the possibility to include information on the texture of volcanic surfaces at Mt. Etna. The approach presented here may be particularly useful for remote and inaccessible volcanic areas and also represents a potentially powerful tool for the exploration of extraterrestrial volcanic surfaces.     

Two Approaches of Textural Classification for the Location of the Flows of Lava on the Volcanic Site of the Mountain Cameroon

Abstract

This study presents two approaches of textural classification on a synthetic aperture radar (SAR) ERS‐2 image, with the aim of the location of the flows of lava and of the serviced zones around the volcanic site of the Mountain Cameroon. The first approach is a method of progressive supervised classification, where a single class is extracted at the same moment, by using 7 parameters of texture stemming from the run length method. Three classes of texture were extracted by this method and the images from the three classes were merged by the red green blue coloured composition to produce the final map. For purposes of comparison, a not supervised classification was applied to the same image. The applied not supervised classification uses parameters of texture stemming from the co‐occurrence matrix method, and it lays on the detection of the peaks of a histogram. The results obtained by the two methods are coherent, and the validation of the results was made by observations during a recent mission on the site of study.     

CLASSIFICATION OF FOREST TYPES FROM TEXTURAL CHARACTERISTICS OF SIR-C RADAR IMAGES

Methods for classifying land-cover types on the basis of image texture through processing of synthetic-aperture radar (SAR) imagery are described. A combination of statistical characteristics, as well as matrices of conversion probabilities for amplitudes of readings of SAR images, are used in the analysis of texture values. The results of the processing of SIR-C SAR images recorded from aboard the Shuttle spacecraft using these methods are presented for the purpose of classification of forest types.     

DIGITAL PLOTTERS: CURRENT STATUS AND FUTURE DEVELOPMENTS

This paper reviews the requirements and equipment for the photogrammetric restitution of digital data. Advances in computer technology have made it possible to process and display image data in very fast time; this has made real time movement of images on a display screen a reality and hence, together with stereoscopic viewing, a digital version of the analytical plotter. The necessary components are discussed and the implementations which have been made. The use of parallel processing for additional speed is also discussed and the alternatives of using standard workstations are considered. A system developed at University College London is described and some pointers to the future are provided.