Deriving Changjiang coastal zone wind from C-band SAR and its application to salinity simulation

Wind plays an important role in hydrodynamic processes such as the expansion of Changjiang （Yangtze） River Diluted Water （CDW）, and shelf circulation in the Changjiang estuary. Thus, it is essential to include wind in the numerical simulation of these phenomena. Synthetic aperture radar （SAR） with high resolution and wide spatial coverage is valuable for measuring spatially inhomogeneous ocean surface wind fields. We have collected 87 ERS-2 SAR images with wind-induced streaks that cover the Cbangjiang coastal area, to verify and improve the validity of wind direction retrieval using the 2D fast Fourier transform method. We then used these wind directions as inputs to derive SAR wind speeds using the C-band model. To demonstrate the applicability of the algorithms, we validated the SAR-retrieved wind fields using QuikSCAT measurements and the atmospheric Weather Research Forecasting model. In general, we found good agreement between the datasets, indicating the reliability and applicability of SAR- retrieved algorithms under different atmospheric conditions. We investigated the main error sources of this process, and conducted sensitivity analyses to estimate the wind speed errors caused by the effect of speckle, uncertainties in wind direction, and inaccuracies in the normalized radar cross section. Finally, we used the SAR-retrieved wind fields to simulate the salinity distribution off the Changjiang estuary. The findings of this study will be valuable for wind resource assessment and the development of future numerical ocean models based on SAR images.     

Swift时代伽马暴的观测及研究进展

Swift卫星从2004年11月20日升空开始运转到现在已有2年多时间.到目前为止,它-共观测到了200多个伽马暴及其余辉现象.由于Swift观测到了早期X射线余辉、短暴余辉和高红移伽马暴等新的重要现象,伽马暴研究进入了新的时代.该文首先对伽马暴的研究历史做简短回顾,然后简要介绍伽马暴的物理图像和Swift卫星的构成及特点,最后全面评述Swift的观测成就及由此引起的理论挑战.     

Spatial structure and land use control in Extended Metropolitan Region of Zhujiang River Delta,China

The Zhujiang (Pearl) River Delta is one of the most developed Extended Metropolitan Regions (EMR) in China.With the rapid urbanization,the agglomeration of population and industries has emerged,which has led to dramatic changes of spatial structure and land use in this region.With data of high resolution TM remote sensing images and Google Earth maps,this paper identified and analyzed the spatial pattern of the Zhujiang River Delta EMR using Envy and ArcGIS tools.It was found that 1) the industrial land uses were expanding substantially,particularly on the bank sides of the Zhujiang River estuary;2) large-scale housing developments were concentrated in the fringe of metropolitan areas such as those of Guangzhou and Shenzhen;3) a regional transportation network with the spatial pattern of ″1 circle +2 pieces + 3 axes″ had significantly affected the location choice of manufacture enterprises.At the same time,both highly specialized land use and severely mixed land use patterns were identified.As a consequence of the latter,land use efficiency of the whole EMR areas was reduced.Moreover,ecologic and environmental problems were severe.Based on the above analysis,suggestions were given from the viewpoint of spatial safety,land use efficiency,and the reorganization of spatial structure in the Zhujiang River Delta EMR.     

基于支持向量机的岩石薄片图像分割

支持向量机是对传统学习分类方法的一个良好替代,特别是小样本、高维的情况下,有着良好的泛化能力,利用支持向量机良好的分类特性,将图像分割的问题转化为分类问题,对岩石薄片图像进行分割实验.通过实验表明：支持向量机对于分割颜色分布不均匀、边缘模糊的岩石薄片图像,有很好的应用前景.     

Alternative Fuzzy Cluster segmentation of remote sensing images based on Adaptive Genetic Algorithm

Remote sensing image segmentation is the basis of image understanding and analysis. However, the precision and the speed of segmentation can not meet the need of image analysis, due to strong uncertainty and rich texture details of remote sensing images. We proposed a new segmentation method based on Adaptive Genetic Algorithm (AGA) and Alternative Fuzzy C-Means (AFCM). Segmentation thresholds were identified by AGA. Then the image was segmented by AFCM. The results indicate that the precision and the speed of segmentation have been greatly increased, and the accuracy of threshold selection is much higher compared with traditional Otsu and Fuzzy C-Means (FCM) segmentation methods. The segmentation results also show that multi-thresholds segmentation has been achieved by combining AGA with AFCM.     

港珠澳大桥水下结构物的多手段探测

介绍了利用侧扫声纳、浅地层剖面仪和磁力仪开展港珠澳大桥水下结构物的探测方法和过程,并将探测的结果与调查收集的资料比较,分析水下结构物的分布情况,不同探测方法得出的结果也可以相互印证。     

无惩罚系数SVM高光谱影像分类算法研究

惩罚系数是支持向量机(SVM)机器学习中的一个重要参数,它的设置对分类结果有很大影响。但它没有规律可循,高光谱影像数据量大、数据复杂,为其选择合适的惩罚系数非常困难。提出无惩罚系数的SVM算法,利用最近点算法(NPA)计算二分类,对错分数据不设惩罚系数,而是对其重新构造凸集,计算最优超平面,迭代循环直到错分率达到所设的阈值为止。此算法简化了计算过程,降低了误分率。最后用AVIRIS高光谱影像进行实验,实验效果显示,本算法的分类精度和速度都得到很大提高。     

CBERS-02B星数据融合方法评价

CBERS—02B星(以下简称02B星)多光谱CCD数据与全色HR数据空间分辨率相差较大,给图像融合带来一定困难。在对IHS变换、主成分分析变换、Brovey 变换、GS变换等融合算法分析的基础上,利用02B星数据进行了融合试验。通过对试验结果的目视评价与定量分析发现,PC变换和GS变换方法融合图像纹理信息较清晰,光谱保真度较好。在GS变换融合中,可利用02B星CCD相机第5波段模拟GS变换的低分辨率输入,融合结果统计值优于PC变换。     

CBERS-02B星数据在“5·12”地震灾害监测中的应用——以唐家山堰塞湖动态监测为例

利用CBERS-02B星获取的多时相CCD数据,采用人机交互方式对唐家山堰塞湖进行水体信息提取,对湖泊面积变化进行统计分析,从而了解湖面的动态变化及发展趋势,为地质灾情评估与灾害防治提供了定量化依据。     

未知DEM下的机载SAR图像几何校正方法研究

针对机载环境复杂,不确定因素众多,与图像相对应的DEM不能精确获得等影响校正的不利因素,研究基于先验条件而不依赖DEM的机载SAR图像几何校正方法.从产生畸变的原理和校正过程的本质出发,将不同的几何校正理论在成像原理层面进行统一;在此基础上,分析精确校正所需要的条件,并提出当条件不能满足时的基于统计模型的几何校正方法;继而提出基于不同先验条件的校正方案决策模型.仿真实验及基于配准区域的保真度评价结果验证了所提方法的有效性.