任意阶次磁多极子场力线方程的解析表示

本文证明任意阶次磁多极子场力线方程总可以用有限形式解析地表示，并对偶极族和四极族磁多极子场力线的位形给予注记。     

Hydrogen recombination lines near 327 MHz−II: A Galactic plane survey with a 2°×6′ beam

In a previous paper we presented a low-resolution (2°×2°) survey of radio recombination lines (RRLs) at 327 MHz in the longitude rangel=330° to 0° to 89°. In this paper, we present the results of a higher resolution (2°×6′) survey of RRLs from seven 2°-wide fields and two 6°-wide fields in the same longitude range. Observations were made using the Ooty Radio Telescope (ORT). A total of 252 spectra that were obtained are presented. RRLs were detected in almost all the individual positions within the fields withl<35° and at several individual positions within the fields in the longitude rangel=35° to 85°. Detailed analysis of the data towards the field centered at G45.5+0.0, shows that the line emission consists of discrete zones of ionized gas. The angular extent of these zones are likely to be one degree or more corresponding to a linear size of >110 pc at the kinematic distance.     

基于启发式图搜索的遥感影像道路半自动提取

启发式图搜索法用于线状目标识别的原理是：用图结构表示边缘点和边缘段，根据启发函数计算顶点权值，在图的路径上建立相应的代价函数，通过在图中搜索对应的最小代价的通道以找到最优路径。图搜索法是一种全局最优方法，它在受噪声影响较大时效果仍然较好。文中使用了启发式图搜索法（A*算法）实现了道路的半自动跟踪。它的基本思路是：首先利用自适应平滑滤波算子进行道路信息增强，然后对传统的道路数学模型进行了进一步的扩展，突出了对道路几何特性和辐射特性的描述，并依此构建图搜索的代价函数，实现了基于启发式图搜索法A*算法的道路半自动跟踪。经实验证明，该方法进行遥感影像的道路半自动提取效果较好。     

城市交通网络面向对象的时空数据模型研究

原有的城市交通网络数据模型无法对大比例地图中道路的面状特征进行描述。本文引入面向对象的时空数据模型 ,把各种实体作为对象 ,把道路作为面状要素描述。作为面状要素的道路对象直接继承原有道路的非空间特征 ,通过道路中心线对象和交点对象来继承原有线状要素的道路特征 ,包括网络关系和叠加关系等 ,通过车道段对象来增加作为面状要素的道路特征     

Conference Reports

18th International Symposium of Cipa by D. M. Barber, p.505
48th Photogrammetric Week by A. T. Smart, p.506
5th Conference on Optical 3D Measurement Techniques by G. Hunter, p.509     

Book Review

Books reviewed:
S. Openshaw and R. J. Abrahart, Geocomputation
M. Craglia and H. Onsrud, Geographic Information Research: Transatlantic Perspectives
P. J. Halls, Spatial Information and the Environment
J. Sievers and T. Schneider, Second International Symposium on Geographical Names: Geonames 2000
J. C. Leachtenauer and R. G. Driggers, Surveillance and Reconnaissance Imaging Systems: Modelling and Performance Prediction
P. A. Longley, M. F. Goodchild, D. J. Maguire and D. W. Rhind, Geographic Information Systems and Science
Y. Q. Chen and Y. C. Lee, Geographical Data Acquisition
K. Borre, Plane Networks and their Applications.
A. Hirschfield and K. Bowers, Mapping and Analysing Crime Data: Lessons from Research and Practice
O. Koelbl, Proceedings of the Oeepe Workshop on Automation in Digital Photogrammetric Production
RICS Books, Vertical Aerial Photography and Derived Digital Imagery: Client Specification Guidelines
D. E. Reeve and J. R. Petch, Gis Organisations and People: A Socio-Technical Approach     

线路平行线间面积计算的统一简捷模型

本文根据线路平行线间面积计算的统一模型，分别推证了直线，圆曲和缓和曲线段平行线间面积计算的简捷模型，据此归纳出线路平行线间面积计算的统一简捷模型，它在线路土地征及用建材用料计算等方面都有广泛的应用。     

道路曲线数字化数据的联合平差模型

在讨论道路曲线基本单元数字化数据处理模型的基础上，进一步建立了道路曲线的联合平差模型，探讨了以线形为特征的交通运输空间数据的平差处理方法，提出了评价道路曲线数字化的精度指标。这些工作为研究交通空间数据的质量和建立动态分段模型以及道路GIS空间基础数据库是有益的。     

Self-organised clustering for road extraction in classified imagery

The extraction of road networks from digital imagery is a fundamental image analysis operation. Common problems encountered in automated road extraction include high sensitivity to typical scene clutter in high-resolution imagery, and inefficiency to meaningfully exploit multispectral imagery (MSI). With a ground sample distance (GSD) of less than 2 m per pixel, roads can be broadly described as elongated regions. We propose an approach of elongated region-based analysis for 2D road extraction from high-resolution imagery, which is suitable for MSI, and is insensitive to conventional edge definition. A self-organising road map (SORM) algorithm is presented, inspired from a specialised variation of Kohonen's self-organising map (SOM) neural network algorithm. A spectrally classified high-resolution image is assumed to be the input for our analysis. Our approach proceeds by performing spatial cluster analysis as a mid-level processing technique. This allows us to improve tolerance to road clutter in high-resolution images, and to minimise the effect on road extraction of common classification errors. This approach is designed in consideration of the emerging trend towards high-resolution multispectral sensors. Preliminary results demonstrate robust road extraction ability due to the non-local approach, when presented with noisy input.     

从遥感影像提取道路特征的方法综述与展望

从遥感影像中提取道路特征已有许多研究，但仍存在许多问题有待解决。本文探讨了道路特征提取的基本思路，对道路特征提取的基本方法和现状进行了较全面的综述，介绍了具有代表性的特征提取方法，并对各个方法的特点进行了分析，最后对道路特征提取的研究前景进行了展望。