基于Coulomb规范势的电导率呈任意各向异性海洋可控源电磁三维非结构化有限元数值模拟

本文以非结构化网格剖分为基础,推导了电导率呈任意各向异性条件下的海洋可控源电磁法二次场磁矢量位、标量位所满足的有限元方程.将不完全LU分解预条件因子(ILU)与Induced dimension reduction(IDR(s))迭代算法相结合对有限元方程进行求解.之后,采用加权移动最小二乘法对二次场矢量位、标量位进行求导得到相应的电磁场各分量.最后,开展了两个地电模型的电磁场计算与分析.结果表明:本文所提出的电导率呈任意各向异性条件下的海洋可控源电磁法三维正演算法正确;不完全LU分解预处理的IDR(s)算法计算效率明显优于常用的ILU-QMR、ILU-BICGSTAB算法;算法具有良好的通用性,可用于陆地电磁、航空电磁、井中电磁等地球物理勘探方法在电导率任意各向异性方面的研究.     

基于矢量有限元的带地形大地电磁三维反演研究

研究了基于矢量有限元方法的大地电磁带地形三维反演算法并开发了三维反演计算程序代码.在大地电磁场正演数值模拟方面,采用并行直接稀疏求解器PARDISO且无需进行散度校正的快速正演方案,对典型地形模型,在中等规模计算条件下,与双共轭梯度法(BICG)计算结果比较,发现PARDISO比BICG快10倍以上;通过理论模型试算,并与前人的有限元法计算结果对比,验证了带地形三维正演计算程序的正确性.在反演方面,本研究基于共轭梯度方法编写了大地电磁带地形三维反演代码,为了避免直接求取雅可比矩阵,将反演中的雅可比矩阵计算问题转为求解两次“拟正演”问题,进而将PARDISO的快速正演方案应用于“拟正演”问题的求解,以提高反演计算效率.利用开发的反演算法对多个带地形地电模型的合成数据进行了三维反演,反演结果能很好地重现理论模型的电性结构,验证了本文开发的三维反演算法的正确性和可靠性.最后,利用该算法反演了某矿区大地电磁实测数据,反演得到的三维电性结构清晰地反映了研究区的地电特征,将反演结果与该区已有地质资料结合进行解释,应用效果明显,进一步验证了本文算法的有效性.     

确定坡面径流过程曼宁糙率系数的实验方法研究

曼宁糙率系数是用水动力学方法进行流速计算的关键参数。坡面流曼宁糙率系数与明渠流的不同。为确定坡面径流过程的曼宁糙率系数,自行研发了一种包括供水系统、实验水槽和数据观测记录系统的室内可变糙率坡面实验系统。通过87场预实验验证了供水系统的稳定性和准确性。以坡度、实测流量、实测水深、不同糙率板上河砂的平均直径和地表粗糙度为自变量,以曼宁糙率系数为因变量,选用均方根误差(RMSE)和决定系数(R ²)为评价指标,对166种实验场景进行了支持向量机(Support Vector Machines, SVM)训练与预测,发现：① 紊流的训练结果难以预测层流和过渡流的曼宁糙率系数,说明流态不同时,实验因素对水流的影响机制不同;② 若要较为准确地预测曼宁糙率系数,至少需要包括实测水深在内的3种因素;③ 当同时考虑4种及更多种因素时,紊流状态下均可对曼宁糙率系数进行较为准确的预测。     

基于SVM的海浪要素预测试验研究

采用支持向量机对海浪要素中的有效波高进行预测,采用风场和波浪场作为学习要素,对比不同特征向量对有效波高预测结果的准确度。取台湾岛东部海区作为实验区域,使用NCEP再分析的数值模式数据作为学习样本。选用支持向量分类机,建立了4组不同特征向量的模型进行海浪有效波高的预测,并对4种模型的结果进行比较和分析。实验表明,当输入的特征向量过多或过少时,会对模型的预测结果和计算效率产生不同的影响。当使用风场和波浪场共同作为特征向量进行学习时,在该区域预测结果与模式预报结果相比更接近,相关系数将近99%,均方根误差约0.2 m。     

经验模态分解和最小二乘支持向量机在大坝变形预测中的应用

由于受到温度、雨水冲刷等外在因素的影响,大坝变形时间序列数据会呈现出非线性和非平稳的曲线特性。为此,提出一种经验模态分解(EMD)和最小二乘支持向量机(LSSVM)相结合的大坝变形预测模型。首先,使用EMD对大坝变形时间序列数据分解成若干个不同尺度的本征模式分量(IMF);然后,利用LSSVM模型对各个IMF进行预测;最后,对预测的结果相加得到大坝变形预测值。以吉林市丰满大坝为算例,构建EMD-LSSVM预测模型,并与LSSVM模型对比分析,结果表明,EMD-LSSVM模型预测效果更好,精度更高,具有更好的实用型。     

Vegetation species mapping in a coastal-dune ecosystem using high resolution satellite imagery

Vegetation mapping is a priority when managing natural protected areas. In this context, very high resolution satellite remote sensing data can be fundamental in providing accurate vegetation cartography at species level. In this work, a complete processing methodology has been developed and validated in a complex vulnerable coastal-dune ecosystem. Specifically, the analysis has been carried out using WorldView-2 imagery, which offers spatial and spectral resolutions. A thorough assessment of 5 atmospheric correction models has been performed using real reflectance measures from a field radiometry campaign. To select the classification methodology, different strategies have been evaluated, including additional spectral (23 vegetation indices) and spatial (4 texture parameters) information to the multispectral bands. Likewise, the application of linear unmixing techniques has been tested and abundance maps of each plant species have been generated using the library of spectral signatures recorded during the campaign. After the analysis conducted, a new methodology has been proposed based on the use of the 6S atmospheric model and the Support Vector Machine classification algorithm applied to a combination of different spectral and spatial input data. Specifically, an overall accuracy of 88,03% was achieved combining the corrected multispectral bands plus a vegetation index (MSAVI2) and texture information (variance of the first principal component). Furthermore, the methodology has been validated by photointerpretation and 3 plant species achieve significant accuracy: Tamarix canariensis (94,9%), Juncus acutus (85,7%) and Launaea arborescens (62,4%). Finally, the classified procedure comparing maps for different seasons has also shown robustness to changes in the phenological state of the vegetation.     

雷暴区域追踪矢量与雷暴单体追踪矢量融合临近预报研究

雷暴追踪矢量的准确性是决定短时临近降水外推预报效果的关键。以TREC（Tracking Radar Echoes by Correlation）为代表的区域追踪和以TITAN（Thunderstorm Identifiation,Tracking,Analysis,and Nowcasting）为代表的单体追踪是追踪雷暴移动矢量的两种典型方法。TREC基于追踪格点雷达回波数据得到,能较好体现层状云降水和对流云降水系统的区域总体移动趋势;TITAN可以识别、分析雷暴的二维和三维属性,自动跟踪雷暴的移动速度和方向,形成雷暴单体移动矢量,能够更好地刻画小尺度雷暴单体的移动速度和方向。将TREC和TITAN两种移动矢量进行融合,生成新的外推移动矢量,既保留了TREC方法在刻画大尺度雷暴总体移动趋势信息方面的特长,又能充分发挥TITAN方法在刻画小尺度雷暴运动细节信息上的优势。融合试验表明,采用TREC和TITAN两种降水移动矢量融合的新技术,可以一定程度改进降水外推移动矢量场估计的准确度,提升降水落区和强度外推预报的准确度,对改善北京地区降水临近预报水平具有一定正效果。      

科普资源发布系统的数据组织与快速入库

首先简述了科普资源发布系统的开发模式及相关组件,介绍了系统设计与实现过程中应用的关键技术,详细给出了矢量栅格图层的匹配原理,图文双向查询的实现思路与方法。     

Landslide susceptibility assessment using SVM machine learning algorithm

This paper introduces the current machine learning approach to solving spatial modeling problems in the domain of landslide susceptibility assessment. The latter is introduced as a classification problem, having multiple (geological, morphological, environmental etc.) attributes and one referent landslide inventory map from which to devise the classification rules. Three different machine learning algorithms were compared: Support Vector Machines, Decision Trees and Logistic Regression. A specific area of the Fruška Gora Mountain (Serbia) was selected to perform the entire modeling procedure, from attribute and referent data preparation/processing, through the classifiers' implementation to the evaluation, carried out in terms of the model's performance and agreement with the referent data. The experiments showed that Support Vector Machines outperformed the other proposed methods, and hence this algorithm was selected as the model of choice to be compared with a common knowledge-driven method – the Analytical Hierarchy Process – to create a landslide susceptibility map of the relevant area. The SVM classifier outperformed the AHP approach in all evaluation metrics (κ index, area under ROC curve and false positive rate in stable ground class).     

海洋电磁法勘探油气的三维正演模拟

针对海底可控源电磁法( MCSEM) 在油气资源勘探中的实用性,应用矢量有限元进行了多种频率的水平电偶源发射电磁场识别油气层的实例研究,并利用矢量有限元对海底的3D 模型进行了正演数值模拟。利用MCSEM 能较好地识别油气层; 归一化后的电场曲线特征表明,浅海下不易测得油气层,在实验频率内,电场源频率越高对油气层识别能力越强。同时证实了MCSEM 识别油气层是建立在波导理论基础上的。