GENTOOLS在国家1∶50000数据库更新工程中的应用研究

1∶50000地形数据库更新是一项复杂的地形数据库制作工程。传统的缩编技术工艺与相应的工具难以适应新的生产需要,适应于数字环境下的缩编生产工具的需求则变得非常迫切。GENTOOLS很好地解决了1∶50000数据库更新工程中的诸多难题,采用半自动和手动相结合的方法,大大提高了缩编效率,同时也为地形图缩编提供了一种新的选择。     

利用Quickbird卫星遥感影像进行1∶10000比例尺基本地理信息数据更新的探讨

作者探索利用已有的控制点成果及1∶10000地形图矢量数据、高分辨率Quickbird卫星遥感影像,针对国内各省近年更新过的1∶10000数字正射影像数据、1∶10000地形图数据进行再次更新的方法进行了探索。     

基于增强型GPS的自适应UKF实时星间相对定位方法

高精度的星间实时相对定位是卫星编队飞行的一项关键技术。本文以双星编队为例,提出一种基于GPS双频P码、双频载波相位以及星间距离观测信息的自适应UKF、实时相对定位方法。仿真结果表明:相比传统的EKF方法,该算法能有效地提高滤波稳定性及相对定位精度,而且,星间测距信息的引入能大大减少整周模糊度判定所需的历元数。     

用于地震调查的航空红外遥感实时传输系统研究

该系统提供了航空红外遥感资料的袢时采集和传输，为及时开展地震野外调查工作提供了一个有力的手段。该系统由红外传感器系统、机载站图像和数据实时处理系统、机载站通信系统、转发站通信系统、地面站接收系统、地面站图像和数据实时处理系统组成。     

现代通讯技术在自动化测量系统中的应用

介绍了基于现代通讯技术ADSL及GPRS的两种远程监控方式在自动化测量系统工程中的应用。获得的结论对于相关技术及专业的应用研究具有一定的借鉴作用。     

地震数据IP传输及存储技术应用

介绍一种IP传输方案。该方案通过地震数据IP传输及存储单元(ITU)、IP流多串口服务器完成，能实现单个台站与多个台网中心的Internet传输、单个台站与多个台网中心的专线传输、地震台网中心之间的Internet连接、远程数据下载及参数设置等多种传输方式，该传输方案具备实时性、可压缩性、多路服务、安全性、数据在线保存、传输费用低、操作简单等特点。     

水库流域入库洪水预报误差分析

由于受水库枢纽工程的影响，使得反推计算的入库流量本身就存在较大的误差，从而增加了入库洪水预报模型研制的难度，影响了这时预报精度的考核。通过对全国诸多水电厂水库流域实时洪水预报的实践，对其入库洪水预报中存在的误差原因及解决方法进行了科学的分析和阐述，以指导实时预报。     

Dynamic performance of twin curved cable‐stayed bridges

The dynamic behaviour of two curved cable‐stayed bridges, recently constructed in northern Italy, has been investigated by full‐scale testing and theoretical models. Two different excitation techniques were employed in the dynamic tests: traffic‐induced ambient vibrations and free vibrations. Since the modal behaviour identified from the two types of test are very well correlated and a greater number of normal modes was detected during ambient vibration tests, the validity of the ambient vibration survey is assessed in view of future monitoring. For both bridges, 11 vibration modes were identified in the frequency range of 0ndash;10Hz, being a one‐to‐one correspondence between the observed modes of the two bridges. Successively, the information obtained from the field tests was used to validate and improve 3D finite elements so that the dynamic performance of the two systems were assessed and compared based on both the experimental results and the updated theoretical models. Copyright © 2003 John Wiley & Sons, Ltd.     

Automatic Road Change Detection and GIS Updating from High Spatial Remotely-Sensed Imagery

This paper presents a tramework for road network change detectlon In order to upctate the Canadian National Topographic DataBase (NTDB). The methodology has been developed on the basis of road extraction from IRS-pan images (with a 5.8 m spatial resolution) by using a wavelet approach. The feature matching and conflation techniques are used to road change detection and updating. Elementary experiments have showed that the proposed framework could be used for developing an operational road database updating system.     

The data‐driven approach as an operational real‐time flood forecasting model

Accurate water level forecasts are essential for flood warning. This study adopts a data‐driven approach based on the adaptive network–based fuzzy inference system (ANFIS) to forecast the daily water levels of the Lower Mekong River at Pakse, Lao People's Democratic Republic. ANFIS is a hybrid system combining fuzzy inference system and artificial neural networks. Five ANFIS models were developed to provide water level forecasts from 1 to 5 days ahead, respectively. The results show that although ANFIS forecasts of water levels up to three lead days satisfied the benchmark, four‐ and five‐lead‐day forecasts were only slightly better in performance compared with the currently adopted operational model. This limitation is imposed by the auto‐ and cross‐correlations of the water level time series. Output updating procedures based on the autoregressive (AR) and recursive AR (RAR) models were used to enhance ANFIS model outputs. The RAR model performed better than the AR model. In addition, a partial recursive procedure that reduced the number of recursive steps when applying the AR or the RAR model for multi‐step‐ahead error prediction was superior to the fully recursive procedure. The RAR‐based partial recursive updating procedure significantly improved three‐, four‐ and five‐lead‐day forecasts. Our study further shows that for long lead times, ANFIS model errors are dominated by lag time errors. Although the ANFIS model with the RAR‐based partial recursive updating procedure provided the best results, this method was able to reduce the lag time errors significantly for the falling limbs only. Improvements for the rising limbs were modest. Copyright © 2011 John Wiley & Sons, Ltd.