面向不同主题的交通大数据可视分析

大数据时代,交通数据如何更快更准确地实时反映交通状况成为研究热点。使用不同交通数据对不同的研究主题进行可视分析,进而揭示蕴含的交通信息知识,为交通部门提供决策支持。首先,分析了大数据的基本特征,总结了大数据可视分析的研究现状;其次,对交通大数据的基本构成、获取方式及数据类型特点进行详细描述;最后,按照不同的研究主题选择不同的数据源与不同的可视化表达方式,揭示不同研究主题蕴含的交通规律,为交通大数据的自动模型分析提供可靠的可视化知识。     

一种快速有效的大数据区域网平差方法

针对摄影测量影像来源多样化、复杂化、大数据化等趋势,传统区域网平差算法在应对当前复杂多变的数据来源,矩阵排列毫无规律的法方程结构以及大数据量带来的高内存需求和低计算效率等问题上,遇到了前所未有的挑战,为了解决上述难题,本文引入了预条件共轭梯度法以及不精确牛顿解法求解区域网平差过程中的法方程,同时使用一种块状法方程系数矩阵压缩存储格式,构建了全新的区域网平差技术流程。本文方法避免了直接对法方程系数矩阵的求逆,压缩了法方程系数矩阵所需的内存空间,使得本文算法比传统算法所需计算机内存空间大幅减少,平差计算速度明显提升,同时保证了计算精度与传统方法相当。初步试验证明,本文方法对4500张影像、近900万像点数据的平差计算在普通电脑上仅需要约15min,且计算精度达到子像素级。     

谈大数据时代的“云控制”摄影测量

在当今大数据时代,影像数据采集方式的多样化、高效化、便捷化产生的摄影测量影像大数据需要高效、自动与智能的处理。然而,作为传统摄影测量几何定位主要控制数据的外业控制点,其获取的复杂性与低效性仍然是制约摄影测量处理效率的关键因素。针对该问题,本文提出了"云控制"摄影测量的概念,以带有地理空间信息的数据作为几何控制替代外业控制点,通过自动匹配(或配准)获取大量密集的控制信息;并介绍了基于影像、矢量和LiDAR点云的3种"云控制"摄影测量技术;最后对"云控制"摄影测量的应用前景进行了展望并对其问题进行了讨论。     

利用轨迹大数据进行城市道路交叉口识别及结构提取

交叉口是城市交通路网生成、更新的重要组成部分。本文基于车辆时空轨迹大数据,提出了一种城市交叉口自动识别方法。该方法首先通过轨迹跟踪识别轨迹数据中包含的车辆转向点对;然后基于距离和角度的生长聚类方法进行转向点对的空间聚类,并采用基于局部点连通性的聚类方法识别交叉口;最后利用交叉口范围圆和转向点对提取城市各级别路网下的交叉口结构。以武汉市出租车轨迹大数据为例,对武汉市城区内189个交叉口进行了探测。试验结果表明,本文所提方法可以准确地从轨迹大数据中识别出城市交叉口及其结构。     

Characterizing mixed-use buildings based on multi-source big data

To-date few research has successfully integrated big data from multiple sources to characterize urban mixed-use buildings. In this paper, we introduce a probabilistic model to integrate multi-source and geospatial big data (social network data, taxi trajectories, Points of Interest and remote sensing images) to characterize urban mixed-use buildings. The usefulness of our model is demonstrated with a case study of the Tianhe District in megacity Guangzhou, China. The model predicted building functions at 85% accuracy based on ground truth data from field surveys. We further explored the spatial patterns of the identified building functions. Most mixed-use buildings are located along major streets. Our proposed model can identify mixed-use buildings in a city; information is useful for planning evaluation and urban policymaking.     

Big Data Resource Planning for Food Safety: a Preliminary Exploration of the “Environment,Food and Health” Information Chain

Environmental pollution, food safety and health are closely linked. A key challenge in addressing the problem of food safety and protecting public health is building an integrated knowledge base to inform policy and strengthen governance. This requires breaking down the trans-departmental information barrier across the environment, food and health domains to ensure the effective flow of data and the efficient utilization of resources, and facilitate the collaborative governance of food safety. Achieving this will be crucial for the development of health and medical care in China in the era of big data. Currently, the information resources commanded by various departments are incomplete and fragmented. Data resources are also organized in vertical silos and there is a lack of data sharing within and across policy streams. To provide the basis for more effective integrated collection and analysis of data in future, this study summarizes the information resources of various departments whose work relates to interactions between environment, food and health, and presents measures to strengthen top-down design, and establish unified data standards and a big data sharing platform. It also points to the need for increased training of data analysts with interdisciplinary expertise.     

PolarGlobe: A web-wide virtual globe system for visualizing multidimensional,time-varying,big climate data

The increasing research interest in global climate change and the rise of the public awareness have generated a significant demand for new tools to support effective visualization of big climate data in a cyber environment such that anyone from any location with an Internet connection and a web browser can easily view and comprehend the data. In response to the demand, this paper introduces a new web-based platform for visualizing multidimensional, time-varying climate data on a virtual globe. The web-based platform is built upon a virtual globe system Cesium, which is open-source, highly extendable and capable of being easily integrated into a web environment. The emerging WebGL technique is adapted to support interactive rendering of 3D graphics with hardware graphics acceleration. To address the challenges of transmitting and visualizing voluminous, complex climate data over the Internet to support real-time visualization, we develop a stream encoding and transmission strategy based on video-compression techniques. This strategy allows dynamic provision of scientific data in different precisions to balance the needs for scientific analysis and visualization cost. Approaches to represent, encode and decode processed data are also introduced in detail to show the operational workflow. Finally, we conduct several experiments to demonstrate the performance of the proposed strategy under different network conditions. A prototype, PolarGlobe, has been developed to visualize climate data in the Arctic regions from multiple angles.     

土地规划的自然过程基础与大数据时代的方法探索

随着城市化与工业化程度不断加深,产业空间结构不断重组,导致土地供需矛盾日益突出,国土资源无序开发日益严重,因而优化国土资源空间格局,成为生态文明建设的首要任务。同时,科学合理配置土地资源对土地规划提出了更高要求,传统土地规划方法有待改革。在基于尊重自然、顺应自然的开发理念下,总结土地自然过程基础对土地规划的影响,实现“山水路林田生命共同体”的协调规划发展。其次,“大数据”时代的来临,云计算、空间数据整合、云分析等技术对土地规划方法提供新的技术支撑;最后,针对土地规划数据特殊性、移动用户终端的广泛性,提出应创建土地规划云服务平台,使土地规划实现数据集成管理和更新,从而提高土地规划质量。     

地理学研究范式的思考

地理学主要关注陆地表层自然和人文要素的空间分异规律研究,针对这一复杂系统的不同问题应该选择不同的研究方式。本文在思考以往地理学研究方式的基础上,将地理学研究范式概括为：地理经验科学研究范式、地理实证科学研究范式、地理系统科学研究范式和地理大数据研究范式。对不同地理科学问题应选取不同的范式加以研究,对有些复杂科学问题应采用多种研究范式加以解决。     

基于“遥感、大数据、互联网+城乡规划”的“智慧规划”创新模式的探索——以东莞市为例

"遥感、大数据、互联网+"等新技术集成应用,极大地丰富了数据获取来源,为城乡规划提供了新的分析方法。本文以东莞市为例,总结了东莞市城乡规划信息化与新技术应用的发展历程,结合新技术的应用时代背景,揭示了存在的问题,并为探索基于"遥感、大数据、互联网+城乡规划"的"智慧规划"创新模式提出了建议,为加强城市规划建设管理,提升城市品质提供技术基础,同时为中小城市的规划信息化及新技术应用提供借鉴。