面向地理国情监测的变化检测与地表覆盖信息更新方法

常态化地理国情监测能够全面、动态地掌握地理国情信息及其变化,为经济建设和社会发展提供数据基础。地理国情普查成果是按照统一规范标准、经过内业解译和外业核查形成的矢量数据。如何在普查成果的基础上,利用多时相遥感影像实现变化信息提取与更新是地理国情监测的关键。针对地理国情普查成果的特点与监测需求,以多时相遥感影像处理分析为基础,构建了针对地理国情监测的变化检测方法体系,提出了像元—对象结合的多时相影像变化检测、基于对象实体统计分析的变化识别方法,实现了综合地理国情普查成果和遥感影像的地理国情变化检测与数据更新。基于像元—对象结合的多时相影像变化检测首先根据传统的变化矢量分析法提取基于像元的变化检测结果,再以地理国情普查的矢量对象为统计单元计算对象内变化像元的比例,以此判断该矢量对象是否发生了变化,并根据变化像元的比例计算其变化强度。基于对象实体统计分析的变化检测方法直接以地理国情矢量为对象进行特征提取和差异构造,再将差异影像进行阈值分割得到基于地理国情对象的变化检测图。最后,根据变化检测结果,对变化区域进行面向对象分割,并从上一期未变化区域选取训练样本训练分类器模型以得到变化区域的地表覆盖类型,将变化区域与未变化区域结合得到更新后的地理国情矢量图。选取江阴市地理国情普查成果和两期高分辨率遥感影像进行试验,结果表明本文提出的方法在准确提取和解释变化区域的同时,明显提高了变化检测和数据更新的效率,可用于常态化地理国情监测。     

利用自适应最优极化对比增强检测SAR影像边缘

针对边缘检测中极化信息利用率不高的问题,提出了一种结合自适应最优对比增强与均值比的合成孔径雷达边缘检测新方法,并分析新算法特性后,推导了其快速版本。实验结果表明,新方法具有更好的检测性能。     

Burnt area delineation from a uni-temporal perspective based on Landsat TM imagery classification using Support Vector Machines

Information on burnt area is of critical importance in many applications as for example in assessing the disturbance of natural ecosystems due to a fire or in proving important information to policy makers on the land cover changes for establishing restoration policies of fire-affected regions. Such information is commonly obtained through remote sensing image thematic classification and a wide range of classifiers have been suggested for this purpose. The objective of the present study has been to investigate the use of Support Vector Machines (SVMs) classifier combined with multispectral Landsat TM image for obtaining burnt area mapping. As a case study a typical Mediterranean landscape in Greece was used, in which occurred one of the most devastating fires during the summer of 2007. Accuracy assessment was based on the classification overall statistical accuracy results and also on comparisons of the derived burnt area estimates versus validated estimates from the Risk-EOS Burnt Scar Mapping service. Results from the implementation of the SVM using diverse kernel functions showed an average overall classification accuracy of 95.87% and a mean kappa coefficient of 0.948, with the burnt area class always clearly separable from all the other classes used in the classification scheme. Total burnt area estimate computed from the SVM was also in close agreement with that from Risk-EOS (mean difference of less than 1%). Analysis also indicated that, at least for the studied here fire, the inclusion of the two middle infrared spectral bands TM5 and TM7 of TM sensor as well as the selection of the kernel function in SVM implementation have a negligible effect in both the overall classification performance and in the delineation of total burnt area. Overall, results exemplified the appropriateness of the spatial and spectral resolution of the Landsat TM imagery combined with the SVM in obtaining rapid and cost-effective post-fire analysis. This is of considerable scientific and practical value, given the present open access to the archived and new observations from this satellite radiometer globally.     

基于MOS方法的风向预测方案对比研究

基于MOS方法的数值预报产品释用技术是要素预测较好手段,风向的释用预测方案一般采用标量式的释用预测方案,效果并不理想。本文给出一种基于MOS方法的风向矢量预测方案,利用相关系数和逐步回归方法分别得到u风和v风在不同站点和不同时效的风向模型,根据模型预测u风和v风合成风向。试验选择风向矢量、风向标量和模式的直接输出三种方案进行对比。试验选择T639模式逐日多个物理量观测场,其中建模样本选择2008-2012年每年5月15日至9月15日的数据,验证样本选择2012年6月1-30日的数据,数值试验预测北京地区20个站点未来4个时次的定点定时风向。结果表明：基于MOS方法的风向矢量预测方案12、24、36h和48h的准确率比基于MOS的风向标量观测方案的各时效准确率分别提高了85.0%、26.3%、113.0%和19.9%,比模式直接输出结果方案的各时效准确率分别提高了35.3%、20.2%、43.6%和21.0%。总体来看,基于MOS方法的风向矢量预测方案在风向方面有较好的预测能力。对于个别站点,可能对因子模型的估计不理想或风向变化较为频繁,导致预测难度较大。     

Iceberg Detection Using Compact Polarimetric Synthetic Aperture Radar

In recent years, the use of synthetic aperture radar (SAR) for iceberg detection has been increasing thanks to the greater availability and coverage of SAR data, particularly polarimetric data. Greater amounts of polarimetric information can increase detection performance, preventing false alarms and missed detections. However, quad-polarization (quad-pol) SAR systems have increased data rate and power usage requirements, causing quad-pol modes to have generally half the swath width of dual-polarization (dual-pol) modes. Compact polarimetry is a compromise that allows the approximation of quad-pol information (referred to as “pseudo quad-pol”) using a dual-pol SAR. In this paper, using compact polarimetric data simulated from RADARSAT-2 quad-pol imagery, we show how pseudo-quad-pol data can be used for iceberg detection using the likelihood ratio test method. We show that use of the pseudo-quad-pol HV intensity can augment the detection performance of a compact polarimetric SAR system. We also compare the performance of the various compact polarimetric configurations to linearly polarized dual-pol and quad-pol data.

[Traduit par la rédaction] Ces dernières années, le radar à synthèse d'ouverture (RSO) a été de plus en plus utilisé pour la détection des icebergs grâce à une meilleure disponibilité et une meilleure couverture des données RSO, en particulier des données polarimétriques. De plus grandes quantités d'informations polarimétiques peuvent améliorer la performance de détection, ce qui évite les fausses alarmes et les détections manquées. Cependant, les systèmes RSO à quadruple polarisation (quad-pol) exigent des débits binaires et une consommation d’énergie plus élevés, de telle sorte que les modes quad-pol utilisent généralement une largeur de couloir la moitié moindre que celle des modes à double polarisation (dual-pol). La polarimétrie compacte est un compromis qui permet d'approximer l'information quad-pol (alors appelée « pseudo-quad-pol ») au moyen d'un RSO dual-pol. Dans cet article, en utilisant des données de polarimétrie compacte simulées à partir de l'imagerie RADARSAT-2 quad-pol, nous montrons comment les données pseudo-quad-pol peuvent servir à la détection des icebergs au moyen de la méthode du test du rapport des vraisemblances. Nous montrons que l'utilisation de l'intensité HV pseudo-quad-pol peut augmenter la performance de détection d'un système RSO polarimétrique compact. Nous comparons aussi la performance des diverses configurations polarimétriques compactes aux données dual-pol et quad-pol linéairement polarisées.     

跨孔观测地震数据的速度重建

利用矢量射线追踪正演模拟技术 ,计算地震波传播的路径及走时 ,进而利用射线走时及路径的内插 ,发展了弯曲射线迭代反演技术 .该方法可用来重建井间地层的速度图像 .基于所发展的方法 ,我们对两种较为复杂的典型地质模型进行了井间速度重建 .结果表明该方法是一项快速、高精度的跨孔数据速度重建技术     

Dichroic Filters For Astronomical X-Ray Polarimetry

We describe a programme of research to investigate materials which exhibit linear dichroism at X-ray wavelengths, and to assess their potential as astronomical X-ray polarimeters. The availability of polarising filters for X-rays would offer an efficient method of quantifying the polarisation of X-ray radiation from distant, cosmic sources. A polarising dichroic filter is expected to be a compact, low mass device which could add polarimetry capability to an instrument by being introduced into the optical path ahead of a detector. We provide estimates of sensitivity in the context of the proposed XEUS observatory, which compare favourably with those for the most promising alternative technology. We also discuss a number of astrophysical sources which are suited to polarimetric study at discrete energies offered by the X-ray dichroic filter design.     

汉字矢量字形输出的新途径

汉字矢量字形的输出是实现地图图面注记自动化的关键。汉字信息处理可采用用户程序级、操作系统级和硬件级三种方式。一、三两种方式已经过多年的实践,表明都有不尽人意之处。本文从操作系统级出发,将供显示和打印用的点阵式字模转化为适合绘图仪输出的矢量数据。这一方法可利用国标一、二级字库的汉字信息资源,并可以获得地图图面注记所需要的各种字体和字形的汉字。     

图形软件中矢量汉字的生成与应用

在研制岩土工程制图软件时，摸索出两种矢量汉字的生成技术，现作一介绍，以便为有同样问题的读者提供参考，避免不必要的重要工作。     

基于TerraSAR-X影像的格陵兰岛海岸水边线提取

海岸线是海洋与陆地的交界线,全球气候变化将引起海岸线的变迁,极地区域拥有最大的冰川,冰川的消融将导致全球海岸线的迅速变迁,因此研究极地海岸线具有重要的科学意义。由于潮汐等影响,卫星影像提取的海洋与陆地的交界线只是海岸水边线,本文以格陵兰岛海岸为实验对象,采用Gamma滤波方法对合成孔径雷达(SAR)数据的相干斑进行预处理,提出了应用支持向量机(SVM)和Canny边缘检测算子的海岸水边线提取方法,基于Terra SARX影像的实验结果表明,本文提取的格陵兰海岸水边线准确率都达60%以上。