应用多种测量软件对地图后期处理

随着电子地图的出现和各种测量软件的开发，地形图实现了美观化和统一化。而各种测绘软件提供的开放性，也使我们可以在不同的测绘软件中对地形图加以编辑和修改，充分利用各个测绘软件的优势。本文结合实际工作经验，针对具体工作中遇到的一些问题，利用各种测绘软件的结合，使一些问题得到解决，并使图形更趋于美观化。     

高分辨率影像定位的一种新方法

提出了利用小比例尺地形图和多分辨率影像实现高分辨率遥感影像定位的方法。阐述了利用线状地物代替点状地物实现低分辨率影像相对于小比例尺地形图纠正定位的方法，并通过金字塔结构的多分辨率影像逐级匹配，使高分辨率影像上的细致目标得以绝对定位。     

一种基于Cross-Validation的盲图像恢复方法

图像盲复原所面临的主要问题是可利用的信息不足，目前已有的图像盲复原算法一般都是有先验知识，如非负和有限支持域的限制。但在实际中目标的支持域是未知的。文中介绍了CV(cross-validation)的基本原理，给出了一种基于CV原理的支持域确定方法的详细步骤；并针对计算大的问题提出了一定的改进。最后给出了实验结果，证明CV确定支持域的方法对于图像盲复原是有一定价值的。     

基于紧支径向基函数的点插值无网格方法

紧支径向基函数能使支配方程中的刚度矩阵具有稀疏性,很适合应用于无网格方法中,其缺点是在插值计算时精度不高.点插值方法的插值函数具有Delta函数性质,可以很方便的施加本质边界条件,但在计算插值函数时矩阵易出现奇异.为了提高计算精度并避免点插值法的局限性,首先对紧支径向基函数进行完备性修正,然后用完备性修正的紧支径向基函数代替多项式来形成插值函数,建立了紧支径向基函数点插值方法.由于该方法中的形函数满足Delta函数性质,因此本质边界条件可以像传统的有限元方法一样很容易施加.然后将该方法用于二维弹性静力问题的求解,导出了其相应的离散方程.最后将该方法应用于一个悬臂梁的分析中,初步验证了该方法的有效性与合理性.     

流域水资源承载能力综合评价的多目标决策-理想区间模型

水资源承载能力评价，是一个由多目标组成的复杂巨系统，其难点是如何合理地建立评价该系统的数学模型。由于评价标准是区间概念而非点的概念，因而传统的多目标决策一理想点法把评价标准处理成理想点存在一定缺陷。为了克服这种缺陷，对多目标决策理想点法进行了改进，提出了一种新的评价模型——多目标决策一理想区间模型(MODMIIM)，介绍了MODMIIM的原理，给出了其构成方法，并用MODMIIM对淮河流域的水资源承载能力进行了综合评价，结论为淮河流域的水资源承载能力总体上较弱。MODMIIM可操作性强，计算结果稳定、合理。与多目标决策一理想点法相比，MODMIIM具有更大的适用性。MODMIIM可广泛应用于各种水资源综合评价问题中。     

突变理论在断层检测中的应用尝试

简述了突变理论中的尖点突变模型及其表达式，将地震信号转化为尖点突变的标准形式，在时间域内计算突跳势、突跳时间等突跳参数，发现突跳参数曲线上异常的位置与地下断层的位置有关。在这里尝试将突变理论应用于断层的检测，分析了突变理论在断层检测理论上的可行性，对实际地震剖面进行分析解释，取得了一定的效果。这说明利用突变参数进行断层的检测是可行的，突变理论将为地震资料解释提供一种新的途径。     

3D Building Modelling with Digital Map, Lidar Data and Video Image Sequences

Three-dimensional (3D) reconstruction and texture mapping of buildings or other man-made objects are key aspects for 3D city landscapes. An effective coarse-to-fine approach for 3D building model generation and texture mapping based on digital photogrammetric techniques is proposed. Three video image sequences, two oblique views of building walls and one vertical view of building roofs, acquired by a digital video camera mounted on a helicopter, are used as input images. Lidar data and a coarse two-dimensional (2D) digital vector map used for car navigation are also used as information sources. Automatic aerial triangulation (AAT) suitable for a high overlap image sequence is used to give initial values of camera parameters of each image. To obtain accurate image lines, the correspondence between outlines of the building and their line features in the image sequences is determined with a coarse-to-fine strategy. A hybrid point/line bundle adjustment is used to ensure the stability and accuracy of reconstruction. Reconstructed buildings with fine textures superimposed on a digital elevation model (DEM) and ortho-image are realistically visualised. Experimental results show that the proposed approach of 3D city model generation has a promising future in many applications.     

网解和PPP解的等价性

证明了PPP解与网解的等价性,比较了网解和PPP解模式下的位置和对流层延迟参数的解算结果,实验验证了这两种GPS解算模式下参数解的等价性。     

用PPP技术确定南极Amery冰架的三维运动速度

基于GPS精密点定位(precise point positioning,PPP)技术,利用IGS的精密星历数据编制软件处理了在Amery冰架获取的连续5d的GPS卫星跟踪观测资料,初步获得了冰架前端观测点处的冰流速度和冰流方向。根据定位解算出的高程系列的周期变化,初步推求出观测点处的海潮周日变化参数。研究成果可为后续的物质平衡计算提供依据。     

Sign-constrained robust least squares, subjective breakdown point and the effect of weights of observations on robustness

The findings of this paper are summarized as follows: (1) We propose a sign-constrained robust estimation method, which can tolerate 50% of data contamination and meanwhile achieve high, least-squares-comparable efficiency. Since the objective function is identical with least squares, the method may also be called sign-constrained robust least squares. An iterative version of the method has been implemented and shown to be capable of resisting against more than 50% of contamination. As a by-product, a robust estimate of scale parameter can also be obtained. Unlike the least median of squares method and repeated medians, which use a least possible number of data to derive the solution, the sign-constrained robust least squares method attempts to employ a maximum possible number of good data to derive the robust solution, and thus will not be affected by partial near multi-collinearity among part of the data or if some of the data are clustered together; (2) although M-estimates have been reported to have a breakdown point of 1/(t+1), we have shown that the weights of observations can readily deteriorate such results and bring the breakdown point of M-estimates of Huber’s type to zero. The same zero breakdown point of the L ₁-norm method is also derived, again due to the weights of observations; (3) by assuming a prior distribution for the signs of outliers, we have developed the concept of subjective breakdown point, which may be thought of as an extension of stochastic breakdown by Donoho and Huber but can be important in explaining real-life problems in Earth Sciences and image reconstruction; and finally, (4) We have shown that the least median of squares method can still break down with a single outlier, even if no highly concentrated good data nor highly concentrated outliers exist. An erratum to this article is available at .