苏北沿岸流对浒苔暴发及漂移过程的影响

根据2009年5月的温度、盐度和溶解氧观测数据,应用"对应分析法"对水团的分布范围和特性进行了分析,并探讨了苏北沿岸流对浒苔(Enteromorpha prolifera)暴发及漂移过程的影响。结果表明,春季苏北沿岸流向东南流动过程中,可以将海水中悬浮的浒苔繁殖体向南输运至长江冲淡水与苏北沿岸流交汇处,此处的浒苔繁殖体在适宜的条件下生长繁殖。在夏季风的作用下,长江口北部的浒苔与苏北沿岸海域的浒苔,随表层海流向北漂移,在地球偏转力作用下,漂移路径不断向右偏转,并最终在山东半岛南部海域聚集堆积。苏北沿岸流在浒苔暴发初期将繁殖体输送到条件适宜的生长区,并对浒苔向北漂移起到了重要作用。长江冲淡水向北扩展范围的增大对于浒苔的生长和繁殖起到了促进作用。查明浒苔扩散路径及输运机制不仅具有重要环境意义,而且对深入了解沿岸和河口区泥沙及污染物的扩散和输运机制具有指示作用。     

Novel Folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing

As a widely used approach for feature extraction and data reduction, Principal Components Analysis (PCA) suffers from high computational cost, large memory requirement and low efficacy in dealing with large dimensional datasets such as Hyperspectral Imaging (HSI). Consequently, a novel Folded-PCA is proposed, where the spectral vector is folded into a matrix to allow the covariance matrix to be determined more efficiently. With this matrix-based representation, both global and local structures are extracted to provide additional information for data classification. Moreover, both the computational cost and the memory requirement have been significantly reduced. Using Support Vector Machine (SVM) for classification on two well-known HSI datasets and one Synthetic Aperture Radar (SAR) dataset in remote sensing, quantitative results are generated for objective evaluations. Comprehensive results have indicated that the proposed Folded-PCA approach not only outperforms the conventional PCA but also the baseline approach where the whole feature sets are used.     

经验模态分解和独立分量分解在航磁数据处理中的应用

以东天山1∶20万航磁数据为例,利用经验模态分解(EMD)方法对航磁数据进行分解,然后利用独立分量分析(ICA)方法对分解出的固有模态函数(IMF)数据进行重构。分解出来的从高频到低频IMF与地质体的分布具有一定的相关性,不同频率的IMF代表了一定的地质意义。经过ICA重构后的独立分量(IC)能够对异常IMF函数从盲源分离的角度进行有效的重构,其结果可以在一定程度上解释不同的地质事件对磁异常的贡献,并对构造识别和构造区域划分具有一定的指示意义。     

层次分析及 GIS空间分析在矿山岩溶塌陷预测评估中的应用--以某大理石矿为例

以某大理石矿矿山地质环境调查资料为基础,通过对矿山岩溶塌陷的机理分析,采用层次分析法,选取地下水活动、覆盖层特征、岩溶发育程度和人类活动强度四个方面,共6个评价指标,建立某大理石矿岩溶塌陷预测评估体系。在确定各评价指标权重和各评价因子分级标准的基础上,以 MAPGIS 空间分析作为数据处理工具和系统运行平台,生成某大理石矿岩溶塌陷易发性分区图。     

云南省施甸县东山铅锌矿成因分析

云南省施甸县东山铅锌矿为一中型铅锌矿床.矿体赋存于二叠系沙子坡组,主要受近SN向的区域断裂F2和F18及次级断裂构造控制,岩石（性）控矿也十分明显,成矿与构造、深部断裂、岩浆热液活动密切相关.成矿地质背景及成矿地质条件有利,通过对矿床成因分析,展示了矿区较好的找矿前景和资源潜力.     

Assessment of recharge capacity potential of groundwater using comparative multi-criteria decision analysis approaches

Journal of Geographical Sciences - Groundwater resources have always been some of the most valuable resources of human settlements. Climate changes and ever-increasing water demands registered in...     

流星雷达测距精度的改进

针对目前流星雷达测距误差大的问题，本文提出了提高流星雷达测距精度的新方法，即提高采样速率，用相关分析确定回波脉冲参考点的方法。该方法使流星雷达的测距精度提高一个数量级，测距误差降到±１４ｍ，使流星雷达不仅可以用来观测研究流星，还可用于监测飞机、火箭的飞行等，扩大流星雷达的应用。     

利用扫描电镜-电子探针研究四川杨柳坪镍铜硫化物矿床铂钯的赋存状态及沉淀机制

本文利用电子探针和配备能谱分析功能的扫描电镜对四川杨柳坪镍-铜硫化物矿床中铂钯的赋存状态进行了研究。结果表明,铂以独立矿物相砷铂矿和自然铂存在;钯以碲化物、碲铋化物、碲锑化物、锑化物及自然钯独立矿物相存在,也以类质同象形式分布在碲镍矿中(钯含量约10%),另外还以锑铋钯碲矿、六方锑碲钯矿、碲钯矿独立矿物相存,并以类质同象形式分布在Vavrinite(钯含量5%)和砷铂矿(钯含量1%~5%)中。杨柳坪矿床中铂钯元素沉淀与贱金属矿物(BMS)及晚期热液蚀变矿物蛇纹石、方解石密切相关,其沉淀经历了3个阶段:1早期高温阶段(1200~900℃),铂钯元素沉淀并包裹在BMS中;2中期中高温阶段(650~250℃),分离结晶作用使铂钯元素沉淀并分布BMS矿物的边部,同时该阶段热液来源的铂钯元素沉淀于BMS粒间;3晚期热液蚀变阶段(500~300℃),热液蚀变作用引起铂钯元素沉淀在蚀变矿物中或嵌布在BMS裂隙。本文研究成果为认识该矿床及同类型镍-铜硫化物矿床的铂钯成矿过程提供了新的依据。     

独立分量分析改进的图像去噪方法

针对传统去噪算法在复杂噪声污染图像处理中能力较弱的问题,该文基于信号高阶统计量的独立分量分析,通过其自适应变换,分离出源信号中的统计独立的分量,在分析对比传统图像去噪方法的基础上,讨论了独立分量分析的基本模型及原理;提出了一种结合中值滤波与wiener滤波的最大似然估计的图像去噪改进方法。仿真实验表明改进的独立分量分析去噪方法具有较大的优越性。     

Fusion of TerraSAR-x and Landsat ETM+ data for protected area mapping in Uganda

TerraSAR-X satellite acquires very high spatial resolution data with potential for detailed land cover mapping. A known problem with synthetic aperture radar (SAR) data is the lack of spectral information. Fusion of SAR and multispectral data provides opportunities for better image interpretation and information extraction. The aim of this study was to investigate the fusion between TerraSAR-X and Landsat ETM+ for protected area mapping using high pass filtering (HPF), principal component analysis with band substitution (PCA) and principal component with wavelet transform (WPCA). A total of thirteen land cover classes were identified for classification using a non-parametric C 4.5 decision tree classifier. Overall classification accuracies of 74.99%, 83.12% and 85.38% and kappa indices of 0.7220, 0.8100 and 0.8369 were obtained for HPF, PCA and WPCA fusion approaches respectively. These results indicate a high potential for a combined use of TerraSAR-X and Landsat ETM+ data for protected area mapping in Uganda.