京奉铁路之历史地理研究(1881-1912年)

京奉铁路是近代中国第一条干线铁路,全长840 km,起始于1881年的唐胥铁路建设,经历许多波折,兴建时间长达31年,可以视为近代中国铁路发展的缩影。在中国近代化的过程之中,近代交通的发展受到守旧派的阻力相当巨大,其中铁路建设阻力更大。京奉铁路从清帝国首都北京修筑至陪都盛京,并非一帆风顺,而是在各种错综复杂的因素影响下艰难分段延展。在地理空间的展布上,京奉铁路的路线走向受到多种因素的影响,其中包含政治因素、军事因素、经济因素、地理因素、风俗习惯等。本研究将藉助GIS,对相关区域旧版大比例尺地形图(包含战前日本所制的地形图在内)做定位与套迭,取得旧日铁路路线、城垣、河道、皇家苑囿等地理信息进行分析,探讨影响京奉铁路路线与各种因素的关系。在地图资料之外,本研究将与其他的文字史料相互参照,以分析在唐山—胥各庄段、北京附近、以及奉天附近三个研究区域里,前述各种因素对京奉铁路发展上的影响。     

青藏高原水系特征遥感影像解译方法研究

我国西部地区1∶50000地形图的缺失,制约了该区域经济建设和社会发展,给我国西部大开发战略的实施带来了困难。影像解译是整个测绘工程中的关键环节之一,水系特征又是各类地物中的关键要素。本文通过对不同影像中青藏高原水系特征的解译,结合其它技术手段,综合运用各类信息,在此基础上提出了针对不同水系特征的解译提取方法。结果表明,针对不同水系特征的特点,利用不同的遥感数据源,结合其它技术手段,加上各类信息的运用,能够有效地提取青藏高原的各类水系特征,基本能够满足1∶50000地形图的测绘需求。     

运用自组织映射识别街道网中的网格模式

提出了一种运用自组织映射识别网格模式的方法。首先,计算街道网中网眼的参数,这些参数是质心、面积、矩形度、延展度、是否含有平行边、边数、一阶邻居数和矩形度平均值;然后,将网眼作为自组织映射的向量进行训练,利用U-matrix可视化方法挖掘聚类得出结果。实验结果表明,该方法能有效地从不规则街道网中识别出网格模式。     

基于GML+XSLT和SVG的矢量专题图绘制方法

地理标志语言GML和可缩放矢量图形SVG是2种基于XML的开放性、应用性标记语言;GML和SVG的出现解决了GIS数据的共享和GIS数据的显示的难题。专题地图是GIS中一个重要的功能,它能够直观地对与专题相关的一种或几种数据进行表示,使得数据更有说服力。提出了基于GML、XSLT和SVG实现专题图的方法;绘制了某城市10年的月平均降雨量的专题图。     

河南地图网的设计与实现

河南地图网作为数字河南地图公众服务平台,是互联网宣传河南的重要窗口。文章主要从网站的服务定位、数据组织和功能设计等方面介绍河南地图网的设计与建设,并对河南地图网的现状和发展前景进行分析和总结。     

基于IKONOS卫星立体像对的1∶10000地形图测绘应用

以IKONOS卫星立体像对为数据源,检测了IKONOS卫星影像在不同控制点布设方案的情况下的测图精度,找出了最经济、最有效进行1∶10000地形图测绘的方法;利用IKONOS卫星影像进行1∶10000测图,并分析了卫星像对影像更适合哪种地形测图;将卫星影像测图与航测测图进行效益和效率比较,分析了卫星影像测图的优势。     

2维地图与3维虚拟场景交互技术的应用与实现

通过分析传统2维地图与3维虚拟场景在电力选线设计中的技术作用及特点,阐明了二者交互结合在电力选线中的必要性,并分别从2维地图模块设计与3维虚拟场景模块设计出发,实现了2维地图与3维虚拟场景的交互,最终为电力选线设计提供了便利.     

A spatial decision support system for extracting the core factors and thresholds for landslide susceptibility map

Spatial decision support system (SDSS) is an interactive, computer-based system designed to support a user in achieving a higher effectiveness of decision-making while solving a semi-structured spatial data. Satellite Remote Sensing and Digital Elevation Modeling are providing a systematic, rational framework for advancing scientific knowledge of our SDSS of geophysical phenomena that, often lead to observe the natural hazards or resources. Taking the advantage of these, more specifically, our study focused on using these to collect and measure the landslide data on a vast area located at Shei Pa National Park, Miao Li, Taiwan. Our source data includes (1) Digital Elevation Modeling is also used to investigate the landform, and (2) remote sensing image data are also employed to analyze the vegetation conditions. In addition, the process of generating landslide susceptibility maps involved on how to effectively extract the site-condition dominant attributes and thresholds for displaying the landslide occurrence accurately. Thus, the information from landslide must be categorized and thoroughly evaluated by an Advanced Data Mining Technique — Entropy-based classification method to construct the landslide knowledge rules. The knowledge scope with regards to core factors and thresholds are solved. Then, the susceptibility hazard maps are drawn and verifications are made. On the other hand, the conventional statistical method of Logistic Regression is used for comparison.     

扫描图件管理系统的设计与实现

随着国土资源信息化建设的发展,许多国土业务都以数字化测绘产品为基础,传统硬介质图件由于保存、使用的不便,而逐渐被数字化产品所替代.然而在许多国土部门却依然存在大量历史纸图,这些图件数量大、种类多、精度低、现势性差,但在某些日常业务中还有一定的参考价值,作者针对这种情况,从单位的实际出发,开发设计了扫描图件管理系统,从而有效解决了历史图件的存储、管理和应用等问题.     

Mineral classification from quantitative X-ray maps using neural network: Application to volcanic rocks

We developed a mineral classification technique of electron probe microanalyzer (EPMA) maps in order to reveal the mineral textures and compositions of volcanic rocks. In the case of lithologies such as basalt that include several kinds of minerals, X-ray intensities of several elements derived from EPMA must be considered simultaneously to determine the mineral map. In this research, we used a Kohonen self-organizing map (SOM) to classify minerals in the thin-sections from several X-ray intensity maps. The SOM is a type of artificial neural network that is trained using unsupervised training to produce a two-dimensional representation of multi-dimensional input data. The classified mineral maps of in situ oceanic basalts of the Juan de Fuca Plate allowed us to quantify mineralogical and textural differences among the marginal and central parts of the pillow basalts and the massive flow basalt. One advantage of mineral classification using a SOM is that relatively many minerals can be estimated from limited input elements. By applying our method to altered basalt which contains multiple minerals, we successfully classify eight minerals in thin-section.