Visualizing spatiotemporal trajectories of mobile social media users using space–time cube

The implementation of social network applications on mobile platforms has significantly elevated the activity of mobile social networking. Mobile social networking offers a channel for recording an individual’s spatiotemporal behaviors when location-detecting capabilities of devices are enabled. It also facilitates the study of time geography on an individual level, which has previously suffered from a scarcity of georeferenced movement data. In this paper, we report on the use of georeferenced tweets to display and analyze the spatiotemporal patterns of daily user trajectories. For georeferenced tweets having both location information in longitude and latitude values and recorded creation time, we apply a space–time cube approach for visualization. Compared to the traditional methodologies for time geography studies such as the travel diary-based approach, the analytics using social media data present challenges broadly associated with those of Big Data, including the characteristics of high velocity, large volume, and heterogeneity. For this study, a batch processing system has been developed for extracting spatiotemporal information from each tweet and then creating trajectories of each individual mobile Twitter user. Using social media data in time geographic research has the benefits of study area flexibility, continuous observation and non-involvement with contributors. For example, during every 30-minute cycle, we collected tweets created by about 50,000 Twitter users living in a geographic region covering New York City to Washington, DC. Each tweet can indicate the exact location of its creator when the tweet was posted. Thus, the linked tweets show a Twitter users’ movement trajectory in space and time. This study explores using data intensive computing for processing Twitter data to generate spatiotemporal information that can recreate the space–time trajectories of their creators.     

加速迭代硬阈值ISAR稀疏成像

加速迭代硬阈值(AIHT)作为一种压缩感知(CS)算法,具有计算复杂度低、内存占用小的特点,在较小数目的观测下,经过有限次迭代便能获得较好的重建效果。因此,本文将该算法应用到逆合成孔径雷达(ISAR)稀疏成像,对该方法的具体特征和适用性进行了详细分析。仿真结果表明,在相同信噪比和回波脉冲数条件下,基于AIHT的ISAR成像方法,相比于稀疏贝叶斯算法(SBL),在重建时间上缩短了至少2个量级;相比于迭代加权最小二乘法(IRLS)和平滑l0范数算法,在重建质量上提高了约3倍。经实测数据处理结果验证,在1/4原始脉冲数条件下,该方法仍具有良好的聚焦性能和压低旁瓣效果。     

工程建设项目的多测整合对策研究

以广州市开展联合测绘的改革成效为基础,进一步探索研究工程建设项目审批服务全链条中的测绘服务事项,重点关注优化测绘服务流程、统一测绘技术标准规范、强化对测绘成果的共享互认以及完善测绘行业管理制度等内容,通过优化测绘服务体系为审批制度改革"加速",为优化营商环境"助力",为全国各地全面推出"多测合一"改革提供可复制推广的经...     

输电线路测量辅助处理软件编制

采用VB 6.0并结合架空输电线路测量内业数据整理的特点,编制了输电线路测量辅助处理软件对测量数据进行编辑处理,生成各种成果表和归档资料,同时提供与架空送电线路软件的数据接口。该软件实现了架空输电线路内业数据处理自动化的,已在架空输电线路工程中得到广泛应用。     

基于高效配准算法的CBERS数据规模化生产系统

中巴地球资源卫星影像具有广泛的应用价值,且数据量巨大,本文讨论构建一套完整的CBERS CCD产品生产系统,实现了对其几何精纠正产品、正射纠正产品和镶嵌产品的自动化和批量化生产。论文重点探讨了系统的核心——高效准确的影像自动配准功能,在此基础上实现了对CBERS数据的正射纠正、几何精纠正及产品镶嵌等功能。本文详细介绍了系统所采用的策略、生产流程及核心算法。该系统已在实际生产中得到应用,满足相关精度指标,完全适合中低分辨率遥感影像规模化生产。     

地理国情普查影像解译自动化方案研究

随着空天地一体化对地观测传感网的逐步完善,积累了大量的空间遥感影像。地理国情普查项目进一步地推动了遥感技术的发展和遥感影像的使用,使遥感影像更好地服务于经济社会的发展和生态文明的建设。传统的依靠人工的地物信息提取方式不能满足需求,本文尝试影像解译自动化方案替代完全依靠人工采集的方式,提高遥感信息提取的效率。     

建筑群负荷引起的大地水准面起伏及对高程的影响

The paper studies the ground vertical deformation and the geoid undulation caused by loading of neighboring buildings, based on the loading tides theory. The influence on elevation is also considered. The results show that the ground vertical deformation and the geoid undulation both reach millimeter magnitude. Therefore, it is obvious that the building loading significantly affects the precise engineering surveying, and it must be seriously considered in application.      

基于GPU的数字影像的正射纠正技术的研究

本文简述了CUDA编程模型高性能并行计算的特性,在实现了基于GPU的数字影像正射纠正的基础上,阐述了基于GPU的加速技术在数字影像处理方面的应用情景.     

网格计算在校园网中的应用研究

网格计算可以合理而有效地将资源高效地组织起来,相对于机群计算环境,它具有范围更广、功能更强大、组织和管理更复杂的特点。目前高校中各种计算资源丰富,但是由于地域的分散,很难做到存储、计算资源的共享。本文对校园网现状和网格技术进行研究,提出校园网格的概念及实现的功能。