Simulation of normal distributed smooth fields by Karhunen-Loéve expansion in combination with kriging

Simulation of multigaussian stochastic fields can be made after a Karhunen-Loéve expansion of a given covariance function. This method is also called simulation by Empirical Orthogonal Functions. The simulations are made by drawing stochastic coefficients from a random generator. These numbers are multiplied with eigenfunctions and eigenvalues derived from the predefined covariance model. The number of eigenfunctions necessary to reproduce the stochastic process within a predefined variance error, turns out to be a cardinal question. Some ordinary analytical covariance functions are used to evaluate how quickly the series of eigenfunctions can be truncated. This analysis demonstrates extremely quick convergence to 99.5% of total variance for the 2nd order exponential (‘gaussian’) covariance function, while the opposite is true for the 1st order exponential covariance function. Due to these convergence characteristics, the Karhunen-Loéve method is most suitable for simulating smooth fields with ‘gaussian’ shaped covariance functions. Practical applications of Karhunen-Loéve simulations can be improved by spatial interpolation of the eigenfunctions. In this paper, we suggest interpolation by kriging and limits for reproduction of the predefined covariance functions are evaluated.     

Simulation of normal distributed smooth fields by Karhunen-Loéve expansion in combination with kriging

Simulation of multigaussian stochastic fields can be made after a Karhunen-Loéve expansion of a given covariance function. This method is also called simulation by Empirical Orthogonal Functions. The simulations are made by drawing stochastic coefficients from a random generator. These numbers are multiplied with eigenfunctions and eigenvalues derived from the predefined covariance model. The number of eigenfunctions necessary to reproduce the stochastic process within a predefined variance error, turns out to be a cardinal question. Some ordinary analytical covariance functions are used to evaluate how quickly the series of eigenfunctions can be truncated. This analysis demonstrates extremely quick convergence to 99.5% of total variance for the 2nd order exponential (‘gaussian’) covariance function, while the opposite is true for the 1st order exponential covariance function. Due to these convergence characteristics, the Karhunen-Loéve method is most suitable for simulating smooth fields with ‘gaussian’ shaped covariance functions. Practical applications of Karhunen-Loéve simulations can be improved by spatial interpolation of the eigenfunctions. In this paper, we suggest interpolation by kriging and limits for reproduction of the predefined covariance functions are evaluated.     

结合BM3D和多级非线性加权平均中值滤波的遥感影像混合噪声去噪方法

提出了一种基于三维块匹配（BM3D）和多级非线性加权平均中值滤波的遥感影像混合噪声去噪方法,使用coief3小波和sym2小波替换传统三维块匹配算法中的bior1.5和hear参数,将三维块匹配算法和多级非线性加权平均中值滤波相结合以提高算法对混合噪声的去噪能力。进行一个仿真对比试验和一个真实遥感影像去噪试验,试验表明,本文提出的方法在遥感影像混合噪声去噪方面效果要优于传统混合噪声去噪方法。     

基于支持向量机的京津冀城市群热环境时空形态模拟

城市群热环境作为区域生态重要组成部分,已成为近年来的研究热点。而如何选择针对城市群这种复杂地地貌特征的热环境量化工具一直是亟待解决的技术难点,基于此本研究提出了一种解决多样本、非线性、非平稳及高维函数拟合的计算方法,并建立了基于支持向量机(SVM)的京津冀城市群热环境曲面模型来揭示城市群热环境的时空形态变化。研究结果表明：① SVM模型在刻画多核心、多种土地利用类型城市群热环境的空间分布方面具有理论与实践可行性,能够根据热环境的整体空间布局通过高斯核函数进行局部优化差值,最大限度减少缺省值对模型拟合结果的影响。相比于对照方法可以模拟出更高精度的复杂地貌特征城市群热岛空间分布格局;② 在SVM模型曲面拟合的过程中,拟合精度和拟合时间是衡量拟合结果的重要指标,而原始影像的分辨率则是影响该指标的决定性因素;③ 2003-2013年区域内北京市与天津市的城市热岛效应变化最为明显,热岛面积分别增加7091 km²与4196 km²,空间上呈现出逐年接近连片发展趋势,热岛重心移动轨迹具有明显的时空分异性。北京城市热岛特征为东南部地区异速增长,西部地区缓慢增长;天津城市热岛特征为以城市中心为圆心向周围扩展。本研究进一步丰富了城市群热环境评测的定量方法,可以在实践上对城市群的城市规划、城市建设、环境保护和区域可持续发展等提供定量化、可视化的决策支持。     

Strain segmentation and lateral membrane deformation rate of the subducted Ryukyu slab

Abstract Focal mechanisms of intermediate-depth earthquakes within the subducted Ryukyu slab indicate a systematic pattern of down-dip extension in the northern part under Kyushu. These mechanisms switch rapidly around the Tokara channel to down-dip compression in the southern part toward Taiwan. This intriguing pattern of strain segmentation, together with the differences between the slab geometry of the northern and southern parts, has raised the question of whether stress segmentation, as defined possibly by a tear fault, might exist in the slab. However the Ryukyu trench has a concave oceanward shape in the northern segment while it is convex in the southern oceanward part toward Taiwan. The inflection zone is located around the Tokara channel. The concept of Gaussian curvature of a curved surface suggests that the along-arc variation of the geometric configuration of a subducted slab is related to the shape of the trench. This is in order to accommodate the lateral membrane deformation of the slab as the oceanic lithosphere subducts from a spherical shell to the geometry delineated by the Wadati-Benioff zone. The membrane deformation regime of the subducted Ryukyu slab and its relation with the trench geometry was examined by assuming that the subduction be modelled by the flow field of a thin viscous sheet. A projection operator was utilized to compute the membrane strain-rate tensor of an arbitrary non-Euclidean surface. Numerical experiments indicated that the northern segment of the slab was dominated by lateral compression and down-dip extension and the southern part by lateral extension and down-dip compression. This transition is sharply located near the Tokara channel. These patterns were compatible with what had been observed from studies of focal mechanisms, suggesting that the strain segmentation might be controlled, at least in part, by the lateral membrane deformation within the slab due to the trench shape in this subduction zone. The slab geometry was predicted by minimizing the integrated total dissipation power; this revealed distinct features that were consistent with observations. This implies that the slab geometry may also be affected by the membrane deformation in a systematic fashion.     

Analytical calculations related to facies simulation

The paper presents calculations related to the volumes of different facies types. Asymptotic distributions are derived approximating the volumes of facies proportions. The number of bodies required to meet net-gross specifications are shown to follow an inverse gaussian distribution. The calculations typically are performed prior to simulations of reservoir facies and may add substantially to the understanding of the model. In particular, analytical results are useful when it comes to assessing parameters of complex simulation models. The theoretical distributions agree well with results based on marked point process simulations of a turbiditic reservoir.     

基于FAST和SURF的遥感图像自动配准方法

提出了基于加速分割检测特征(features from accelerated segment test,FAST)和加速鲁棒性特征(speeded - up robust features,SURF)的遥感图像自动配准方法.首先对参考图像与待配准图像进行HSI变换和高斯金字塔建立;然后检测并提取FAST角点,计算各角点的SURF描述子,用K-D树匹配搜索策略得到2幅图像的匹配点对;再使用最小二乘迭代法剔除错误匹配点并拟合几何变换系数;最后执行几何变换,得到配准后的图像.将该方法分别与基于SURF自动配准方法和ENVI软件中自动获取配准点的方法进行对比实验,结果表明,利用该方法能够获得更多的匹配点对,具有更高的几何配准精度,但在尺度不变性方面略逊于SURF算法.     

综合应用测井及地震资料建立复杂断块地质模型

针对滩海油田具有完钻井少,以地震资料为主的特点,采用井震结合的方法进行地质建模。复杂断块油藏具有许多内部断层,充分利用地震解释层位和断层成果建立合理的构造模型。采用“多步建模”的思路,选用序贯高斯同位协同模拟算法建立储层参数模型。以测井资料为硬数据,地震反演数据为软数据,先后建立自然伽玛模型、泥质含量模型和砂泥岩相模型,然后以砂泥岩相模型为约束,建立储层参数模型。经研究表明,综合使用地震解释成果和三维地震数据体,有助于建立准确、合理的构造模型;而采用“多步建模”的思路,利用序贯高斯同位协同模拟算法,并综合测井资料、地震资料建立储层参数模型,有助于从地质的角度对储层参数模拟进行约束,提高储层随机建模精度,保证储层参数模型的准确和可靠性。     

一种灰度体素结构分割模型下的机载LiDAR 3D滤波算法

针对现有的基于机载LiDAR数据的滤波算法未能充分利用数据提供的所有信息及其所采用的数据结构表达复杂、存在信息损失等缺陷,提出了一种灰度体素结构分割模型下的机载LiDAR 3D滤波算法。算法首先以综合利用机载LiDAR数据的高程及强度信息为目的将点云数据规则化为灰度（体素内激光点的平均强度的离散化表示）体素结构,然后基于各体素间的空间连通性和灰度相似性准则,将灰度体素结构分割并标记为若干个3D连通区域,最后依据地面与其它目标的高差特性提取与其对应的3D连通区域。算法优势在于:基于体素结构设计,为3D滤波算法;综合利用了地面目标的几何及辐射特征,对比传统滤波算法可应用于更复杂的场景;滤波结果为3D地面体素形式,可直接用于创建地面3D模型。实验采用国际摄影测量与遥感协会（International Society for Photogrammetry and Remote Sensing, ISPRS）提供的不同密度的机载LiDAR基准测试数据测试了邻域尺度参数的敏感性及提出的算法的有效性,并和其他经典滤波算法做对比。定量评价的结果表明,51邻域为最佳空间邻域尺度;点云密度为0.67点/m²的数据集1的滤波平均完整率、正确率及质量分别为0.9611、0.9248及0.8934;点云密度为4点/m²的数据集2的滤波平均完整率、正确率及质量分别为0.8490、0.8531及0.7404;对比其全经典滤波算法本文算法在高密度点云数据滤波时表现更佳。     

An Advanced Probabilistic Neural Network for the Design of Breakwater Armor Blocks

In this study,an advanced probabilistic neural network(APNN)method is proposed to reflect the global probability density function(PDF)by summing up the heterogeneous local PDF which is automatically determined in the individual standard deviation of variables.The APNN is applied to predict the stability number of armor blocks of breakwaters using the experimental data of van der Meer,and the estimated results of the APNN are compared with those of an empirical formula and a previous artificial neural network(ANN)model.The APNN shows better results in predicting the stability number of armor blocks of breakwater and it provided the promising probabilistic viewpoints by using the individual standard deviation in a variable.