GB/T 18316-2008的使用探讨

从抽样检验的基本原理出发,结合对空间数据产品特点的理解,针对空间数据产品的抽样检验,从抽样方案、检验内容、质量评价等方面对现行的抽样检验标准GB/T 18316-2008进行了分析。探讨了该标准存在的缺陷对客观、科学、公正评价空间数据产品质量的影响以及解决方法,对GB/T18316-2008的修订有一定借鉴意义。     

中药资源地理国情监测工具集设计与实现

目前第四次全国中药资源普查试点工作采集了大量的成果数据,并且成果数据与地理空间位置之间存在天然的联系。本文以中药资源数据的空间属性作为出发点,在中药资源普查成果数据和已有地理国情监测数据的基础上,建立了基础地理数据库、专题地理数据库和中药资源数据库,设计并实现了能够进行中药资源专题分析计算的地理工具集。最后,基于B/S架构完成了中药资源地理国情监测技术平台的构建,验证了地理工具集设计思路的正确性。     

三维地图式可视化大数据

数据可视化技术利用计算机图形图像学以及数据挖掘技术,以交互方式将数据中的隐藏信息展示给用户,为用户决策提供参考。近年来,随着PC计算能力与互联网技术的快速发展,传统的数据可视化技术已无法满足人们日益增长的信息处理需求。目前,数据可视化在可视化过程中存在显示结果精确度低、表达方式单一、不能突出数字信息内含的规律性等问题。本文针对上述问题提出了基于三维地图的可视化大数据解决方案,该方案通过制作专题地图可视化数据,对数据的规律性进行了研究,从而方便用户理解数据的深层次信息,发现隐藏的特征、模式、趋势等信息。     

基于地面三维激光扫描数据的快速建模

三维激光扫描技术具有速度快、精度高、自动化程度高并且不与物体直接接触等诸多优点,现已应用于古建筑保护、数字城市、工业生产、地形测绘等不同领域。本文利用地面三维激光扫描仪对校内樱花园手形建筑物进行扫描,获取该目标物的点云数据,并对获取的点云数据进行拼接、去噪处理。同时,利用点云数据处理软件Geomagic对目标物进行快速的三维模型重建并达到了预期的效果。     

基于SuperMap的空间大数据可视化技术研究与应用

人类正从IT时代走向DT时代,诸多的技术手段使大数据处理技术能够从大规模数据中分析出相关模式或趋势,让我们对海量数据的价值挖掘充满了期待.当可视化呈现让大数据的潜力达到最大时,以往未被观察到的现象或趋势很容易被发现,用户能够快速地获得更多信息,发现他们所需要的价值.因此,如何最大化地呈现大数据中隐含的价值变得尤为关键.本文将重点研究空间大数据的可视化方法,充分发挥数据可视化的作用,帮助用户挖掘隐藏在空间大数据中的价值.     

面向统计应用的数据可视化系统设计

当今社会正处于一个信息爆炸的时代,随着企业信息化技术的发展,除了政府机构、媒体(传统媒体)、企业等提供越来越多的数据以外,新兴的社会化媒体、物联网技术等的应用普遍化、介入人类生活的深入化也是数据量急剧增长的主要原因.这些数据大多以表格的形式存放在数据库内,既枯燥又难于理解.如何才能将这些数据有效地展示出来,帮助用户理解数据,发现潜在的规律,是亟待解决的问题.数据可视化能够将抽象的数据表示成为可见的图形或图像,显示数据之间的关联、比较、走势关系,有效揭示出数据的变化趋势,从而为理解那些大量复杂的抽象数据信息,为企业决策支持提供帮助.本文把大数据时代作为背景,把统计数据作为一个整体研究对象,将可视化技术和可视化表现作为方法手段,对各自进行分类和研究探讨,从而全面地认识数据可视化.     

Exploring maps by sounds: using parameter mapping sonification to make digital elevation models audible

This study empirically investigates the potential of auditory displays for spatial data exploration, as an additional means to broaden the accessibility and dissemination of geographic information for a diverse body of users. In a mixed factorial experiment, three parameter mapping sonification methods are empirically evaluated to interactively explore discrete and continuous digital elevation models by auditory means. Contrasting prior sonification research, this study’s unique empirical evidence suggests that participants can indeed successfully interpret sonified displays containing continuous spatial data. Specifically, the auditory variable pitch leads to significantly better response accuracy, compared to the sound variable duration. Background and training has a weak effect on data interpretation performance with the auditory display. The more immersive the experienced soundscape, the better participants can interpret the sonified terrain. These encouraging empirical results indeed suggest that interactive auditory displays might offer additional means to disseminate spatial information, and to increase the accessibility to spatial data, beyond the currently dominant visual paradigm.     

Generating urban road intersection models from low-frequency GPS trajectory data

Detailed real-time road data are an important prerequisite for navigation and intelligent transportation systems. As accident-prone areas, road intersections play a critical role in route guidance and traffic management. Ubiquitous trajectory data have led to a recent surge in road map reconstruction. However, it is still challenging to automatically generate detailed structural models for road intersections, especially from low-frequency trajectory data. We propose a novel three-step approach to extract the structural and semantic information of road intersections from low-frequency trajectories. The spatial coverage of road intersections is first detected based on hotspot analysis and triangulation-based point clustering. Next, an improved hierarchical trajectory clustering algorithm is designed to adaptively extract the turning modes and traffic rules of road intersections. Finally, structural models are generated via K-segment fitting and common subsequence merging. Experimental results demonstrate that the proposed method can efficiently handle low-frequency, unstable trajectory data and accurately extract the structural and semantic features of road intersections. Therefore, the proposed method provides a promising solution for enriching and updating routable road data.     

Ten Years of Science Based on the Canadian Precipitation Analysis: A CaPA System Overview and Literature Review†

Near real-time quantitative precipitation estimates are required for many applications including weather forecasting, flood forecasting, crop management, forest fire prevention, hydropower production, and dam safety. Since April 2011, such a product has been available from Environment and Climate Change Canada for a domain covering all North America. This product, known as the Regional Deterministic Precipitation Analysis, is generated using the Canadian Precipitation Analysis (CaPA) system. Although it was designed for near real-time use, an archive of pre-operational and operational products going back to 2002 is now available and has been used in numerous studies. This paper presents a review of the various scientific publications that have reported either using or evaluating CaPA products. We find that the product is used with success both for scientific studies and operational applications and compares well with other precipitation datasets. We summarize the strengths and weaknesses of the system as reported in the literature. We also provide users with information on how the system works, how it has changed over time, and how the archived and near real-time analyses can be accessed and used. We finally briefly report on recent and upcoming improvements to the product based, in part, on the results of this literature review.     

A Prototype Regional GSI-based EnKF-Variational Hybrid Data Assimilation System for the Rapid Refresh Forecasting System:Dual-Resolution Implementation and Testing Results

A dual-resolution(DR) version of a regional ensemble Kalman filter(EnKF)-3D ensemble variational(3DEnVar) coupled hybrid data assimilation system is implemented as a prototype for the operational Rapid Refresh forecasting system. The DR 3DEnVar system combines a high-resolution(HR) deterministic background forecast with lower-resolution(LR) EnKF ensemble perturbations used for flow-dependent background error covariance to produce a HR analysis. The computational cost is substantially reduced by running the ensemble forecasts and EnKF analyses at LR. The DR 3DEnVar system is tested with 3-h cycles over a 9-day period using a 40/13-km grid spacing combination. The HR forecasts from the DR hybrid analyses are compared with forecasts launched from HR Gridpoint Statistical Interpolation(GSI) 3D variational(3DVar)analyses, and single LR hybrid analyses interpolated to the HR grid. With the DR 3DEnVar system, a 90% weight for the ensemble covariance yields the lowest forecast errors and the DR hybrid system clearly outperforms the HR GSI 3DVar.Humidity and wind forecasts are also better than those launched from interpolated LR hybrid analyses, but the temperature forecasts are slightly worse. The humidity forecasts are improved most. For precipitation forecasts, the DR 3DEnVar always outperforms HR GSI 3DVar. It also outperforms the LR 3DEnVar, except for the initial forecast period and lower thresholds.