Distribution of the nonlinear random ocean wave period

Because of the intrinsic difficulty in determining distributions for wave periods, previous studies on wave period distribution models have not taken nonlinearity into account and have not performed well in terms of describing and statistically analyzing the probability density distribution of ocean waves. In this study, a statistical model of random waves is developed using Stokes wave theory of water wave dynamics. In addition, a new nonlinear probability distribution function for the wave period is presented with the parameters of spectral density width and nonlinear wave steepness, which is more reasonable as a physical mechanism. The magnitude of wave steepness determines the intensity of the nonlinear effect, while the spectral width only changes the energy distribution. The wave steepness is found to be an important parameter in terms of not only dynamics but also statistics. The value of wave steepness reflects the degree that the wave period distribution skews from the Cauchy distribution, and it also describes the variation in the distribution function, which resembles that of the wave surface elevation distribution and wave height distribution. We found that the distribution curves skew leftward and upward as the wave steepness increases. The wave period observations for the SZFII-1 buoy, made off the coast of Weihai (37°27.6′ N, 122°15.1′ E), China, are used to verify the new distribution. The coefficient of the correlation between the new distribution and the buoy data at different spectral widths (ν=0.3−0.5) is within the range of 0.968 6 to 0.991 7. In addition, the Longuet-Higgins (1975) and Sun (1988) distributions and the new distribution presented in this work are compared. The validations and comparisons indicate that the new nonlinear probability density distribution fits the buoy measurements better than the Longuet-Higgins and Sun distributions do. We believe that adoption of the new wave period distribution would improve traditional statistical wave theory.     

自适应空间邻域分析和瑞利-高斯分布的多时相遥感影像变化检测

提出了一种基于自适应空间邻域分析和瑞利-高斯模型(Rayleigh-Gauss models, RGM)分布的多时相遥感影像自动变化检测方法。该方法把自适应空间邻域信息和改进的差值影像与比值影像乘积变换融合 法(improved multiplying transform fusion, IMTF)结合构造差异影像, 可以有效地抑制噪声和消除多时相影像之间配准误差的影响, 具有更强的鲁棒性。在对差异影像的分割处理中, 运用瑞利和高斯模型分别模拟变化类像元和非变化类像元的分布情况, 然后估计出两类像元的概率     

地理数据的不确定性研究

目前地理数据不确定性是制约遥感(RS)与地理信息系统(GIS)发展的主要因素之一,直接影响地理数据分析的空间决策支持系统输出的可信度。如何识别、量化、跟踪、减少、可视化表达地理数据不确定性,已引起地理信息科学领域专家的广泛重视,成为3S领域新的研究热点。本文先阐述地理数据不确定性研究的重要性,然后分析地理数据不确定性产生的根源,最后提出开展地理数据不确定性研究的方法及地理数据不确定性的优先研究领域。     

浅析城镇地籍调查质量控制

结合生产实际,介绍了城镇地籍调查在不同作业阶段进行质量控制的一些经验。     

大瑶山隧道主要工程地质问题

大瑶山隧道地质条件复杂,施工中遇到了较多的水文地质工程地质问题。本文在论述隧道围岩基本工程地质特征的基础上,探讨了隧道围岩的稳定性、变形破坏以及隧道水害等主要工程地质问题。     

原始数据误差对工测多级电磁波测距导线(网)精度的影响

本文探讨原始数据误差在工测多级电磁波测距导线中的传播问题和对其精度的影响。在分析对导线精度的影响时，采用了考虑各级原始数据误差影响下的点位和相对点位误差椭圆。因此，可以对点位和相对点位精度在各方向上的影响程度、其影响在各级网的传播情况、影响大小在各级网中的分布情况等问题，进行全面的分析，并归纳出若干规律。这对多级导线网的设计、完整的精度分析和精度评定方法，以及对工测规范中多级导线网有关条文的制定，都有一定的参考作用。     

河津县普及地震知识取得显著效果

山西省河津县地震观测站,在普及地震知识中狠抓重点单位,采取多种形式广泛宣传,3年来全县约10万余人受到不同程度的地震知识教育,最近,被省地震局评为地震系统的先进单位.     

山东新生代火山岩微量元素地球化学

本文测定了山东新生代玄武质火山岩的化学成分、微量元素及稀土元素含量，它们在丰度模式上，除相容元素外，均有富集。根据丰度特征及相互关系表明它们是地幔岩浆源直接演化的产物，推测其成岩过程可以由低部分熔融的亏损源和富集源组分以不同的比例混合而成。