土地更新调查成果与二次调查数据衔接问题的探讨

结合广西第二次土地调查工作实际,论述了在调查工作中对原土地更新调查成果的利用,对需补充、完善的调查内容逐一进行了分析和阐述,并对如何处理两次调查数据衔接中存在的问题提出了一些建议和看法。     

伪卫星定位系统中的频率与时间统一

在电磁波定位系统中,时间和频率的统一与稳定性非常重要,会直接影响系统的可用性和精度．通过对一个伪卫星定位系统中时间和频率问题的研究,设计出了一套完整的时频统一方案,并编写了程序实现。该方案可以有效提高系统初始化速度,并提高观测质量。     

多类用户的混合星座导航系统定位性能分析

本文针对地面用户与空间用户在测量环境与观测几何动态性等方面的不同,基于导航卫星可见性与加权精度因子(WDOP)对混合星座导航系统的定位性能进行了分析.给出了不同用户的星座天空视图与可视时长;从理论上讨论了权值选取对WDOP的影响.仿真表明,地面静态用户对不同类型导航卫星的可见性差异很大;而低轨卫星用户的可视时长更短,观...     

盾构下穿既有隧道实时监测及其风险控制研究

阐述了测量机器人实时自动化监测系统的组成、结构及关键技术,利用该系统进行盾构下穿期间既有隧道的实时风险控制。结果表明,盾构下穿过程中所有风险控制值都在预警值之内,控制效果良好,但隧道断面结构存在显著拉伸与压缩变形,为保证隧道结构安全,给出了有益的风险控制建议。测量机器人实时监测系统满足盾构下穿既有隧道风险控制的要求,且具有获取结构变形信息全面、精度高、安装简便、可重复利用等优点。     

Nontectonic signals in reprocessed continuous GPS position time series of CMONOC

The nearly nine-year continuous GPS data collected since 1 March 1999 from the Crustal Motion Observation Network of China(CMONOC) were consistently analyzed.Most of the nonlinear movements in the cumulative position time series pro-duced by CMONOC data center disappeared;and more accurate vertical terms and tectonic signals were extracted.Displacements caused by atmospheric pressure loading,nontidal ocean loading,soil moisture mass loading,and snow cover mass loading using the National Centers for Environmental Prediction(NCEP) Reanalysis I/II models and Estimation of the Circulation and Climate of the Ocean(ECCO) data can explain most of the vertical annual terms at many stations,while only parts can be explained at Lhasa and southern coastal sites,indicating that there are some deformation mechanisms that are still unknown or not modeled accurately.The remarkable differences in vertical position time series for short-baseline sites reveal that GPS stations can be greatly affected by lo-cal factors;and attention should be paid when explaining observed GPS velocity vectors.     

三峡库区水质数据时间序列分析预测研究

阐述了时间序列分析的概念、种类及分析方法,以三峡库区水质各指标的水期时间序列数据为研究对象,采用Holt-Winters时间序列预测模型进行了水质预测的试验研究.     

视景仿真中实体云的建模与渲染技术

在视景仿真中对云的建模和实时渲染是一项十分重要的工作.全面研究了视景仿真中3维实体云的建模与绘制技术,并根据视景仿真对云景仿真的需求,采用分形技术和粒子系统技术实现了一种既能获得良好的视觉效果,又能实时绘制的实体云建模与仿真技术.通过视点相关技术、层次细节技术、动态视点替用等技术大大提高了实体云仿真的实时性,使其在一般的微机平台上可以流畅运行.     

SAS/ETS在变形监测数据处理中的应用

在综合考虑数学模型的预测精度与编程实现的可操作性基础上,提出了利用模块对变形监测数据进行时间序列分析,并概括介绍了该模块的3个主要命令使用方法,解决了时间序列分析在监测数据处理中实现起来非常繁琐的问题。最后通过与环境下动态灰色模型综合比较,证明了时间序列分析在变形监测数据处理中操作简单,模拟精度和预测精度都较高。     

Cartographic Symbol Design Considerations for the Space–Time Cube

The cartographic representation of geographic phenomena in the space–time cube comes with special challenges and opportunities when compared with two-dimensional maps. While the added dimension allows the display of attributes that vary with time, it is difficult to display rapidly varying temporal data given the limited display height. In this study, we adapt 2D cyclic point symbols to construct 3D surfaces designed along a helical path for the space–time cube. We demonstrate how these complex?3D helical surfaces can display detailed data, including data reported daily over 100 years and data reported in four-hour intervals over a year. To create the point symbols, each value is plotted along the curve of a helix, with each turn of the helix representing one year or week, respectively. The model is modified by varying the radii from the time axis to all points using the attribute value, in these cases maximum daily temperature and four-hourly ridership, and then creating a triangulated surface from the resulting points. Using techniques common to terrain representation, we apply hue and saturation to the surface based on attribute values, and lightness based on relief shading. Multiple surfaces can be displayed in a space–time cube with a consistent time interval facing the viewer, and the surfaces or viewer perspective can be rotated to display synchronized variations. We see this method as one example of how cartographic design can refine or enhance operations in the space–time cube.     

Re-examining urban region and inferring regional function based on spatial–temporal interaction

Urban system is shaped by the interactions between different regions and regions planned by the government, then reshaped by human activities and residents’ needs. Understanding the changes of regional structure and dynamics of city function based on the residents’ movement demand are important to evaluate and adjust the planning and management of urban services and internal structures. This paper constructed a probabilistic factor model on the basis of probabilistic latent semantic analysis and tensor decomposition, for purpose of understanding the higher order interactive population mobility and its impact on urban structure changes. First, a four-dimensional tensor of time (T)?×?week (W)?×?origin (O)?×?destination (D) was constructed to identify the day-to-day activities in three time modes and weekly regularity of weekday/weekend pattern. Then we reclassified the urban regions based on the space clustering formed by the space factor matrix and core tensor. Finally, we further analysed the space–time interaction on different time scales to deduce the actual function and connection strength of each region. Our research shows that the application of individual-based spatial–temporal data in human mobility and space–time interaction study can help to analyse urban spatial structure and understand the actual regional function from a new perspective.