交通运输最短路径分析系统的设计与实现

针对目前交通运输效力发挥不足的问题,研究道路网络模型构建和道路数据库设计,探讨分析交通运输最短路径分析流程,基于Dijkstra算法的基本原理,设计实现交通运输最短路径分析系统,从而优化运输资源配置,实现高质高效的交通运输。     

亚洲地区EGNOS天顶对流层延迟模型单站修正与精度分析

以亚洲地区46个IGS站2008-2011年实测的高精度天顶对流层延迟（ZTD）数据为参考值,通过对2008-2010年EGNOS模型计算ZTD的日均偏差进行频谱分析,建立了亚洲地区EGNOS模型的单站修正模型（SSIEGNOS）,对EGNOS和SSIEGNOS模型在亚洲地区的精度和适用情况进行了评估,结果表明：（1）EGNOS模型偏差和RMS在时间分布上呈现明显的季节变化规律,而SSIEGNOS模型偏差和RMS变化较小且平稳;（2）在空间分布上,两种模型的偏差随着经纬度和高程的变化均无明显规律,但随着高程或者纬度的增加RMS总体上都有递减的趋势;（3）SSIEGNOS模型预测ZTD的精度相对于EGNOS模型有明显提高。     

甚长基线干涉测量天线参考点和轴线偏差监测方法探讨

高精度监测VLBI天线参考点和轴线偏差等参数,对提高VLBI台站坐标测定精度及天测、测地VLBI资料解析精度等具有重要意义.常规监测方式占用望远镜工作时间,监测效率低,所得参数精度较差.文章提出通过参数化VLBI天线的旋转运动建立天线固连合作目标在局域网中坐标数学模型的方法,有望实现全天候、全自动监测;考察了代表性数学模型,在观测方程构建、解算参数设置和约束条件选取等方面提出了新的见解.最后通过仿真分析,验证了对方程与参数所做调整的有效性,初步结论可供参考.     

重庆万州区山地分类定量化研究

文章在GIS技术支持下,基于水文分析模型,通过DEM数据,结合山地综合分类模型,以重庆市万州区为例,对山地进行定量化分类研究,结果表明:以负地形洼地贡献区域作为山地相对高程的起算面,完全摆脱了人为因素的影响,解决了一直以来难以确定山地相对高度起算范围的难题;以负地形洼地深度作为山地相对高程是正确可行的,且能快速获取山地的相对高程;以山地表面积代替投影面积计算山地率更切合实际.     

巧用GIS空间叠置分析计算遮蔽角

雷达在某个方向上发现目标的最小高低角叫遮蔽角[1]。快速准确计算出气象雷达各方向的最大遮蔽角能够为雷达站的点位和天线高度提供设计依据。本文以某机场为例,在不考虑植被或建筑物高度的提前下,利用等高线数据,采用GIS的空间叠置分析功能快速计算该机场气象雷达每隔2。5°方向的最大遮蔽角。相比传统的断面计算法,GIS空间叠置分析方法大大提高了工作效率,希望能够引导读者注重GIS在工作中的应用。     

高光谱影像纹理特征编码分形特征研究

提出了一种基于分形测度分析高光谱影像纹理的技术。根据高光谱影像纹理单元中相邻光谱矢量的相关关系构造方向性纹理特征,得到了一组纹理特征编码值,从纹理特征编码值本身、相同地物纹理特征编码自相似性和使用不同尺度测量纹理特征编码值构成的曲线所表现出来的幂指数关系三个方面,说明高光谱影像纹理特征编码曲线具有分形特征。设计了纹理特征编码曲线构建模型,采用纹理编码曲线的分形维值表征不同的纹理特征,达到区分和判别不同纹理的目的。试验表明,该方法对提取地物纹理特性具有可行性。     

Cascaded image analysis for dynamic crack detection in material testing

Concrete probes in civil engineering material testing often show fissures or hairline-cracks. These cracks develop dynamically. Starting at a width of a few microns, they usually cannot be detected visually or in an image of a camera imaging the whole probe. Conventional image analysis techniques will detect fissures only if they show a width in the order of one pixel. To be able to detect and measure fissures with a width of a fraction of a pixel at an early stage of their development, a cascaded image analysis approach has been developed, implemented and tested. The basic idea of the approach is to detect discontinuities in dense surface deformation vector fields. These deformation vector fields between consecutive stereo image pairs, which are generated by cross correlation or least squares matching, show a precision in the order of 1/50 pixel. Hairline-cracks can be detected and measured by applying edge detection techniques such as a Sobel operator to the results of the image matching process. Cracks will show up as linear discontinuities in the deformation vector field and can be vectorized by edge chaining. In practical tests of the method, cracks with a width of 1/20 pixel could be detected, and their width could be determined at a precision of 1/50 pixel.     

Singular value decomposition and cluster analysis as regression diagnostics tools for geodetic applications

It is well known that high-leverage observations significantly affect the estimation of parameters. In geodetic literature, mainly redundancy numbers are used for the detection of single high-leverage observations or of single redundant observations. In this paper a further objective method for the detection of groups of important and less important (and thus redundant) observations is developed. In addition, the parameters which are predominantly affected by these groups of observations are identified. This method thus complements other diagnostics tools, such as, e.g., multiple row diagnostics methods as described in statistical literature (see, e.g., Belsley et al. in Regression diagnostics: identifying influential data and sources of collinearity. Wiley, New York, 1980). The method proposed in this paper is based on geometric aspects of adjustment theory and uses the singular value decomposition of the design matrix of an adjustment problem together with cluster analysis methods for regression diagnostics. It can be applied to any geodetic adjustment problem and can be used for the detection of (groups of) observations that significantly affect the estimated parameters or that are of negligible impact. One of the advantages of the proposed method is the improvement of the reliability of observation plans and thus the reduction of the impact of individual observations (and outliers) on the estimated parameters. This is of particular importance for the very long baseline interferometry technique which serves as an application example of the regression diagnostics tool.     

基于主成分分析的ENVISAT ASAR数据在福建省漳州市香蕉园地提取中的应用(英文)

Banana is one of the main economic agrotypes in Zhangzhou, Fujian Province. The multi-temporal ENVISAT ASAR data with different polarization are used to classify the banana fields in this paper. Principal component analysis (PCA) was applied for six pairs of ASAR dual-polarization data. For its large leaves, banana has high backscatter. So the value of banana fields is high and shows very bright in the 1st component, which makes it much easier for banana fields extraction. Dual-polarization data provide more information, and the VV and VH backscatter of banana show different characters with other land covers. Based on the analysis of the radar signature of banana fields and other land covers and the 1st component, banana fields are classified using object-oriented classifier. Compared to the field survey data and ASTER data, the accuracy of banana fields in the study area is 83.5%. It shows that the principal component analysis provides the useful information in SAR images analysis and makes the extraction of banana fields easier. Supported by the Program for New Century Excellent Talents in University (NCET-05-0573), Fujian Science and Technology Project (No.2006I0018), the Science Project of the Education Department of Fujian Province(No. 2006F5022).     

GPS现代化后L2C的信号质量分析

分析了L2C码的主要作用,比较了GPS现代化后L2载波信噪比的变化特点,阐述了伪距观测值的噪声水平。