Estimating traffic speed and speeding using passively collected big mobility data and a distributed computing framework

With the increasing availability of location-aware devices, passively collected big GPS trajectory data offer new opportunities for analyzing human mobility. Processing big GPS trajectory data, especially extracting information from billions of trajectory points and assigning information to corresponding road segments in road networks, is a challenging but necessary task for researchers to take full advantage of big data. In this research, we propose an Apache Spark and Sedona-based computing framework that is capable of estimating traffic speeds for statewide road networks from GPS trajectory data. Taking advantage of spatial resilient distributed datasets supported by Sedona, the framework provides high computing efficiency while using affordable computing resources for map matching and waypoint gap filling. Using a mobility dataset of 126 million trajectory points collected in California, and a road network inclusive of all road types, we computed hourly speed estimates for approximately 600,000 segments across the state. Comparing speed estimates for freeway segments with speed limits, our speed estimates showed that speeding on freeways occurred mostly during the nighttime, while analysis of travel on residential roads showed that speeds were relatively stable over the 24-h period.     

基于PDA的嵌入式GIS结构体系

介绍了基于PDA的嵌入式GIS是在移动计算、嵌入式技术、移动互联、移动定位等技术的基础上发展起来的,讨论了基于PDA的嵌入式GIS的两种结构体系:离线体系和在线体系,并结合开发实例介绍了两种结构体系的基于PDA的嵌入式GIS的实现.     

基于云计算的位置服务平台建设研究

云计算作为一种革命性的计算模型住很多行业都成为重要的技术趋势。将云计算应用于空间地理信息领域所形成的空间云计算也逐渐成为整个空间地理信息行业的主流技术。位置服务利用当今高速发展的互联网和多样化的移动终端向用户提供基于位置的信息和娱乐服务。空间信息数据是位置服务平台的重要维成部分。本文首先介绍云计算相关概念,根据对目前位置服务平台存在的问题的剖析提出了基于云计算的位置服务平台建设的思路和平台架构,最后分析了该平台的特点和所形成的产业链。     

基于云计算的三维地理空间信息服务的表达

当前云计算的发展已能支持高性能的地理空间服务,比如在数字城市和电子商务等行业。Apache基金支持下的开源软件框架Hadoop,可以用来构建一个云环境的集群用来存储和处理高性能的地理空间数据。开放地理空间联盟(OGC)的Web三维服务(W3DS)就是这样一个很好的三维的地理空间数据服务标准。在标准的云计算环境下将是一个更好的应用示范。基于此,本文研究了OGC的W3DS服务在云计算环境下的实验结果。实验采用Apache的Hadoop框架作为三维地理空间信息服务实验展示的基础。实验结果对展示高性能的三维地理空间信息提供了有价值的参考。     

云计算在GIS系统模型中的应用

云计算是基于网络的计算模型,通过构建云计算基础设施来为上层的云端应用提供支撑环境。将GIS与云计算相结合,能够为GIS的信息存储、处理及其应用提供新的发展前景。结合云计算与GIS,提出了基于云计算的GIS系统模型。以云计算的数据存储和透明化用户服务为基础,构建以GIS基础服务设施为服务支撑平台和以GIS基础信息数据与GIS应用程序为应用支撑平台。从而使GIS能够在通过云计算进行底层数据和服务的网络化资源分配,同时为用户提供稳定高效可靠的GIS服务。     

A comprehensive optimization strategy for real-time spatial feature sharing and visual analytics in cyberinfrastructure

For geospatial cyberinfrastructure-enabled web services, the ability of rapidly transmitting and sharing spatial data over the Internet plays a critical role to meet the demands of real-time change detection, response and decision-making. Especially for vector datasets which serve as irreplaceable and concrete material in data-driven geospatial applications, their rich geometry and property information facilitates the development of interactive, efficient and intelligent data analysis and visualization applications. However, the big-data issues of vector datasets have hindered their wide adoption in web services. In this research, we propose a comprehensive optimization strategy to enhance the performance of vector data transmitting and processing. This strategy combines: (1) pre- and on-the-fly generalization, which automatically determines proper simplification level through the introduction of appropriate distance tolerance speed up simplification efficiency; (2) a progressive attribute transmission method to reduce data size and, therefore, the service response time; (3) compressed data transmission and dynamic adoption of a compression method to maximize the service efficiency under different computing and network environments. A cyberinfrastructure web portal was developed for implementing the proposed technologies. After applying our optimization strategies, substantial performance enhancement is achieved. We expect this work to facilitate real-time spatial feature sharing, visual analytics and decision-making.     

A geospatial hybrid cloud platform based on multi-sourced computing and model resources for geosciences

Cloud computing has been considered as the next-generation computing platform with the potential to address the data and computing challenges in geosciences. However, only a limited number of geoscientists have been adapting this platform for their scientific research mainly due to two barriers: 1) selecting an appropriate cloud platform for a specific application could be challenging, as various cloud services are available and 2) existing general cloud platforms are not designed to support geoscience applications, algorithms and models. To tackle such barriers, this research aims to design a hybrid cloud computing (HCC) platform that can utilize and integrate the computing resources across different organizations to build a unified geospatial cloud computing platform. This platform can manage different types of underlying cloud infrastructure (e.g., private or public clouds), and enables geoscientists to test and leverage the cloud capabilities through a web interface. Additionally, the platform also provides different geospatial cloud services, such as workflow as a service, on the top of common cloud services (e.g., infrastructure as a service) provided by general cloud platforms. Therefore, geoscientists can easily create a model workflow by recruiting the needed models for a geospatial application or task on the fly. A HCC prototype is developed and dust storm simulation is used to demonstrate the capability and feasibility of such platform in facilitating geosciences by leveraging across-organization computing and model resources.     

基于Mobile Agent技术的空间信息移动服务

首先详细地分析空间信息移动服务的研究现状、技术路线和局限等问题,在此基础上概括空间信息移动服务的涵义与特征,然后提出一种基于Mobile Agent技术的空间信息移动服务模型.该模型集成移动代理(Mobile Agent)、WAP、XML、SVG、SOAP和J2EE/J2ME等技术,可以实现空间信息的移动计算、空间数据与服务功能的完全分离等,并且该模型还具备易构建性、自主性、移动性、协作性、安全性、智能性、并行计算和同异步处理等特性和良好的可扩展特征.针对此模型框架给出应用案例的算法描述及其结果,最后总结基于此模型的空间信息移动服务的一些优点,同时也指出向普适计算模式的空间信息服务发展的必然趋势.     

The Potential of the Maximum Cross-Correlation Technique to Estimate Surface Currents From Thermal AVHRR Global Area Coverage Data

Having already shown its potential of deriving the vector fields representing the ocean-surface advection from sequential 1.1-km-resolution local area coverage (LAC) Advanced Very High Resolution Radiometer (AVHRR) images, the maximum cross-correlation (MCC) technique here is applied to four 4.4-km-resolution global area coverage (GAC) AVHRR images. The resulting three vector fields are compared to the vector fields obtained from the LAC imagery corresponding to the same satellite passages. To quantify the reduction in accuracy inevitable when applying the method to the lower resolution imagery, the LAC vector fields were assumed to be error free. The deviation of the GAC vectors from the LAC vectors is expressed as percentage errors of the signal variance of meridional u and zonal v velocity components, and they are 16%/30%, respectively, for the best case and 62%/117% and 92%/111% for the other two cases. These results indicate that, in its present state, the GAC data do not allow the MCC technique to extract reliable current-vector information from it     

IKONOS卫星影像立体测图中有理函数模型的研究

有理函数模型是成像几何模型的一种简单、通用的表达,已经成为构筑真实传感器模型的一个计算方法.本文对IKONOS卫星影像立体测图作了介绍.详细介绍了IKONOS图像的有理函数模型的理论、算法、各种特性以及如何对其进行优化.     

Technical progress of China's national remote sensing mapping:from mapping western China to national dynamic mapping

Remote sensing mapping is an important research direction in the development of geographic surveying and mapping.In order to successfully implement the project of Mapping Western China(MWC),a technical mapping system has been established.In this project,many problems have been solved through technological innovation,such as block adjustment with scarce control points,large-scale aerial/satellite image mapping,and intelligent interpretation of multi-source images.Several softwares were developed,e.g.PixelGrid for aerial/satellite image mapping in a large area,FeatureStation for the integration of multi-source data in the complex terrain areas,and an airborne multi-band and multi-polarization interferometric data acquisition system for SAR mapping.For the first time,full coverage of 1∶50,000 topographic data of China's land territory has been produced,which means the geospatial framework of digital China is basically completed.With the implementation of other key national plans and projects(i.e.national geographic conditions monitoring and national remote sensing map-ping),the focus has changed from MWC to national dynamic mapping.Accordingly,a dynamic mapping system is established.The data acquisition capability has developed from a single source to multiple sources and multiple modalities.The mapping capability has developed into dynamic mapping,and the capability for database update shows the characteristics of colla-boration.The national geographic condition monitoring creates a multi-scale index system for statistical analysis for various needs.A multi-level and multi-dimensional technical system for statistical computing and decision-making service is developed for the transformation from dynamic monitoring to information service.In this paper,we give a brief introduction about the recent development of remote sensing mapping in China with respect to data acquisition,map production,and information service.The purpose of this paper is to motivate the establishment of theory and method for remote sensing mapping,technical and equipment in the smart mapping era,to improve the capability of perceiving,analyzing,mining,and applying geographic data,and to promote the intelligent development of geographic survey-ing and mapping.     

“吉信地理信息云服务平台”服务模式研究

云计算是近几年来计算机领域里十分热门的一个词汇,随着技术的发展和市场的扩张,GIS开始与其他IT应用深度融合,并且逐渐进入IT应用的主流。在云计算的时代,GIS也面临着新的机会与变革。本文从云计算的概念和服务模式出发,介绍了吉信地理信息云服务平台的服务模式。     

Big Data and cloud computing: innovation opportunities and challenges

ABSTRACT

Big Data has emerged in the past few years as a new paradigm providing abundant data and opportunities to improve and/or enable research and decision-support applications with unprecedented value for digital earth applications including business, sciences and engineering. At the same time, Big Data presents challenges for digital earth to store, transport, process, mine and serve the data. Cloud computing provides fundamental support to address the challenges with shared computing resources including computing, storage, networking and analytical software; the application of these resources has fostered impressive Big Data advancements. This paper surveys the two frontiers – Big Data and cloud computing – and reviews the advantages and consequences of utilizing cloud computing to tackling Big Data in the digital earth and relevant science domains. From the aspects of a general introduction, sources, challenges, technology status and research opportunities, the following observations are offered: (i) cloud computing and Big Data enable science discoveries and application developments; (ii) cloud computing provides major solutions for Big Data; (iii) Big Data, spatiotemporal thinking and various application domains drive the advancement of cloud computing and relevant technologies with new requirements; (iv) intrinsic spatiotemporal principles of Big Data and geospatial sciences provide the source for finding technical and theoretical solutions to optimize cloud computing and processing Big Data; (v) open availability of Big Data and processing capability pose social challenges of geospatial significance and (vi) a weave of innovations is transforming Big Data into geospatial research, engineering and business values. This review introduces future innovations and a research agenda for cloud computing supporting the transformation of the volume, velocity, variety and veracity into values of Big Data for local to global digital earth science and applications.     

基于云平台的遥感信息公共服务研究

云平台作为云计算服务的基础架构,在计算机网络的基础上提供各种计算资源的统一管理和动态分配。文章提出的基于云平台的遥感信息公共服务,就是借助云平台先进的基础架构和管理方式,构建快速有效的遥感信息公共服务,推进遥感信息的应用和遥感信息事业的进步。文章在引进云平台技术的基础上,分析遥感信息公共服务平台的架构和关键技术,并对服务平台的应用前景和进一步研究进行展望。     

多级应急响应地理信息服务平台的应用技术

提出一个支持多级分布、服务级联的信息服务综合架构和集成机制,并应用于应急响应地理信息服务平台的设计,探讨了应急响应地理数据虚拟化、分布式异构环境下应急响应地理信息数据/功能服务技术、多级应急地理信息目录服务构建技术等,为构建有效的多级应急响应地理信息服务平台提供技术支撑。     

Change of projection following readjustment

Abstract

The readjustment of a major geodetic control network results in a new set of spheroidal coordinates for the network stations. Those new coordinates followed by an appropriate control densification serve as input for computing new plane coordinates. There are many surveying and mapping products which are based on the existing 'old' plane coordinates system. This paper deals with considerations and procedures aiming at the introduction of a new projection defined in such a way as to minimise the detrimental consequences of readjustment through the use of a synthetic point of origin for the new projection.     

从规则格网DEM自动提取汇水区域及其子区域的方法

从DEM自动提取的汇水区域及其子区域信息对进一步的水文分析有着重要的辅助作用.在经过洼地处理的DEM及得到水流方向矩阵的基础上,本文提出并实现了一种汇水区域及其子区域的提取算法.该算法首先提取整个DEM区域内每条河流的汇水区域,然后按照不同的要求划分子区域.经过试验,与现有的方法相比,该算法在提取效率和结果准确性方面都有明显提高.     

自适应空间信息移动服务

空间信息移动服务系统是空间信息系统继由传统PC计算环境向有线Web分布式计算环境扩展后，向移动计算环境的新发展。文中在分析移动计算环境概念和特点的基础上，讨论了空间信息移动服务的若干特点及关键技术，研究了自适应空间信息移动服务方案。     

格网GDP空间分布更新模型研究

在地理信息系统中,引入格网化的GDP能够反映某一阶段内经济数据的空间分布状况,可为区域发展提供及时的科学数据和决策依据。本文阐述了建立格网GDP更新模型的必要性和可行性。在分析格网GDP更新的关键基础上,以简单比例模型和环境要素面积模型为蓝本,提出了一种按行政单元多边形不同区域分别进行处理的更新模型,并给出了实现更新的基本框架。经过验证,这种分区域处理的格网GDP更新模型在运算精度、运算复杂度、可操作性之间具有良好的平衡,可作为规则格网GDP更新的一般模型。     

基于ArcGIS的云GIS平台设计方案研究

当前云计算技术发展迅速,已不断融入GIS应用的开发建设中,通过构建云GIS平台来提供地理信息服务逐渐成为各级政府部门的共识。本文介绍了云GIS平台的建设内容,重点提出了基于ArcGIS建设云GIS平台的设计方案。