从等值线图形获取DAT和GRD格式的数据文件

在盆地模拟研究工作中，需要处理大量的地质数据和地质图件，一方面，随时需要把各种数据变为可视的图形；另一方面，还时常需要从图形中得到研究中所必需的数据，例如，由构造图得到研究区域的深度数据文件。本文介绍一种从等值线图形获取DAT格式和网格化GRD格式的数据文件的方法。     

铁路缓和曲线的等间隔放样方法

介绍了铁路缓和曲线设置的目的、作用、基本原则和重要意义，阐述了等间隔放样缓和曲线的基本原理，给出了等间隔放样缓和曲线放样要素采集的基本方法，叙述了缓和曲线等间隔放样的工作过程。     

基于SuperMap的图形处理技术

本文首先阐述了SuperMap DeskPro的基本功能，然后对利用SuperMap DeskPro进行常规图形处理的技巧进行了详细介绍，具体包括地图配准、地图拼接、数据集重新整合、对象标注、文本数据集到属性字段的转换和地图格网生成。通过这些技巧的运用，可以有效提高数据的处理能力。     

利用SPOT和ETM+影像进行县级土地利用调查--以河北省万全县为例

本文以SPOT和ETM 影像作为主要信息源，经过对图像进行几何纠正、配准、增强和融合等一系列处理后，在ARCVIEW GIS基础上，成功完成了对河北省万全县土地资源利用情况的调查分析。同时还对应用遥感技术成功获取土地资源利用信息的方法和技术进行了探讨。     

AutoCAD与其他常用软件的数据转换

本文就AutoCAD与生产应用中常用的ARCGIS、ARC／INFO、MicroStation、3DS等软件系统之间的数据转换作一些浅谈。     

土地利用动态管理系统研发中的若干问题研究

土地利用管理是土地管理的核心内容之一。土地利用动态变化加剧了土地管理的压力，建设具有辅助决策功能的土地利用动态信息系统是大势所趋。本文在阐述建设此系统的重要意义基础上，讨论了系统研发中几个关键问题，即“动态”管理的实现、空间数据和属性数据集成管理和决策的初步实现等。本文提出的解决方法，对于类似土地信息系统的建设具有普遍的指导意义。     

Data archives of seismic fault-induced damage

The study of earthquake engineering requires an understanding of various processes by which structures are seriously damaged. For this, archiving available data in a systematic way will be quite necessary. Taskforces of both Japan Society of Civil Engineers (JSCE) and Japan Geotechnical Society (JGS), with a mission of establishing remedial measures for fault-inflicted damage to civil infrastructures, have been investigating previous examples of fault-related damages. Some of their important activities were further expanded as a subject of EqTAP project (Development of Earthquake and Tsunami Disaster Mitigation Technologies and Their Integration for the Asia-Pacific Region). This paper introduces some examples from the JSCE/JGS/EqTAP Data Archives, which can give some hints for rational remedial or design measures for civil-infrastructures whose constructions across faults were/are unavoidable.     

The International Laser Ranging Service and its support for IGGOS

The International Laser Ranging Service (ILRS) was established in September 1998 as a service within the IAG to support programs in geodetic, geophysical, and lunar research activities and to provide data products to the International Earth Rotation Service (IERS) in support of its prime objectives. Now in operation for 5 years, the ILRS develops: (1) the standards and specifications necessary for product consistency and (2) the priorities and tracking strategies required to maximize network efficiency. The service collects, merges, analyzes, archives and distributes satellite and lunar laser ranging data to satisfy a variety of scientific, engineering, and operational needs and encourages the application of new technologies to enhance the quality, quantity, and cost effectiveness of its data products. The ILRS works with: (1) the global network to improve station performance; (2) new satellite missions in the design and building of retroreflector targets to maximize data quality and quantity and (3) science programs to optimize scientific data yield. The ILRS Central Bureau maintains a comprehensive web site as the primary vehicle for the distribution of information within the ILRS community. The site, which can be accessed at: http://ilrs.gsfc.nasa.gov is also available at mirrored sites at the Communications Research Laboratory (CRL) in Tokyo and the European Data Center (EDC) in Munich.During the last 2 years, the ILRS has addressed very important challenges: (1) data from the field stations are now submitted hourly and made available immediately through the data centers for access by the user community; (2) tracking on low satellites has been significantly improved through the sub-daily issue of predictions, drag functions, and the real-time exchange of time biases; (3) analysis products are now submitted in SINEX format for compatibility with the other space geodesy techniques; (4) the Analysis Working Group is heavily engaged in Pilot Projects as it works toward an ILRS “standard” global solution and (5) SLR has significantly increased its participation in the International Terrestrial Reference Frame (ITRF) activity, which is important to the success of IGGOS.     

Data assimilation (4D-VAR) to forecast flood in shallow-waters with sediment erosion

In this paper, the four-dimensional variational data assimilation technique (4D-VAR) is presented as a tool to forecast floods. Our study is limited to purely hydrological flows and supposes that the weather, here a big rain, has been already forecasted by meteorological services. The technique consists in minimizing, in the sense of Lagrange, the cost function: a measure of the difference between calculated data and available observations, here the water level. This is done under constraints that are the equations of the physical model. In our case, we modified the shallow-water equations to include a simplified sediment transport model. The steepest descent algorithm is then used to find the minimum. This is made possible because we can compute analytically the gradient of the cost function by using the adjoint equations of the model. As an application of the 4D-VAR technique, the overflowing of the Chicoutimi River at the Chute-Garneau dam, during the 1996 flood, is investigated. It is found that the 4D-VAR method reduces the error in the water height forecast even when the erosion model is not activated. In terms of Lyapunov exponents, we estimate the predictability horizon of such an event to be about half-an-hour after a big rain. However, this limit of predictability can be increased by using more observations or by using a finer computational grid.     

Model identification for hydrological forecasting under uncertainty

Methods for the identification of models for hydrological forecasting have to consider the specific nature of these models and the uncertainties present in the modeling process. Current approaches fail to fully incorporate these two aspects. In this paper we review the nature of hydrological models and the consequences of this nature for the task of model identification. We then continue to discuss the history (“The need for more POWER‘’), the current state (“Learning from other fields”) and the future (“Towards a general framework”) of model identification. The discussion closes with a list of desirable features for an identification framework under uncertainty and open research questions in need of answers before such a framework can be implemented.