Building the distributed geographic SQL workflow in the Grid environment

Over recent years, massive geospatial information has been produced at a prodigious rate, and is usually geographically distributed across the Internet. Grid computing, as a recent development in the landscape of distributed computing, is deemed as a good solution for distributed geospatial data management and manipulation. Thus, the Grid computing technology can be applied to integrate various distributed resources into a ‘super-computer’ that enables efficient distributed geospatial query processing. In order to realize this vision, an effective mechanism for building the distributed geospatial query workflow in the Grid environment needs to be elaborately designed. The workflow-building technology aims to automatically transform the global geospatial query into an equivalent distributed query process in the Grid. In response to this goal, detailed steps and algorithms for building the distributed geospatial query workflow in the Grid environment are discussed in this article. Moreover, we develop corresponding software tools that enable Grid-based geospatial queries to be run against multiple data resources. Experimental results demonstrate that the proposed methodology is feasible and correct.     

计算模式驱动下GIS体系结构的发展分析

计算模式是信息时代特有的解决问题的方法范式,它综合反映了信息科学的理论、软件与硬件等因素在解决实际问题中相互作用的形式,是与相应阶段主流信息技术相对应的信息系统体系结构的规律模式或构筑范式。该文分析了计算模式驱动下GIS的体系结构从单机模式、局域网模式、广域网模式(WebGIS)到网格模式(GridGIS)的发展过程,指出单机、局域网和广域网模式本质上都具有集中封闭的性质,不同程度地存在着理论、技术、物理、功能和逻辑思维等五大边缘,是典型的空间信息孤岛。网格计算模式是一种彻底的分布式计算模式,GIS的网格模式直接打破了传统模式的技术、物理、功能和逻辑思维限制,并面向理论边缘的解决,具有开放、均质、扁平的结构性质,升格为空间信息网格基础设施。     

网格GIS及其在数字油田中的应用探讨

数字油田是解决当前油田智能化管理问题的最好途径。该文分析了当前油田建设中所面临的问题,结合油田在勘探开发中的实际需要,特别就当前数字油田建设中所面临的共性问题,在分析现有油田技术及发展需求的基础上,指出了基于中间件的分布式网格GIS技术是解决当前数字油田领域中所存在的问题的最佳方式,并讨论了其实现过程。     

Near real-time geoprocessing on the grid: A scalable approach to road traffic monitoring

The geospatial sensor web is set to revolutionise real-time geospatial applications by making up-to-date spatially and temporally referenced data relating to real-world phenomena ubiquitously available. The uptake of sensor web technologies is largely being driven by the recent introduction of the OpenGIS Sensor Web Enablement framework, a standardisation initiative that defines a set of web service interfaces and encodings to task and query geospatial sensors in near real time. However, live geospatial sensors are capable of producing vast quantities of data over a short time period, which presents a large, fluctuating and ongoing processing requirement that is difficult to adequately provide with the necessary computational resources. Grid computing appears to offer a promising solution to this problem but its usage thus far has primarily been restricted to processing static as opposed to real-time data sets. A new approach is presented in this work whereby geospatial data streams are processed on grid computing resources. This is achieved by submitting ongoing processing jobs to the grid that continually poll sensor data repositories using relevant OpenGIS standards. To evaluate this approach a road-traffic monitoring application was developed to process streams of GPS observations from a fleet of vehicles. Specifically, a Bayesian map-matching algorithm is performed that matches each GPS observation to a link on the road network. The results show that over 90% of observations were matched correctly and that the adopted approach is capable of achieving timely results for a linear time geoprocessing operation performed every 60 seconds. However, testing in a production grid environment highlighted some scalability and efficiency problems. Open Geospatial Consortium (OGC) data services were found to present an IO bottleneck and the adopted job submission method was found to be inefficient. Consequently, a number of recommendations are made regarding the grid job-scheduling mechanism, shortcomings in the OGC Web Processing Service specification and IO bottlenecks in OGC data services.     

格网技术对GIS发展的影响

格网技术作为新一代的Web技术,必将深刻影响GIS的发展。格网计算为数据密集型空间分析提供了资源支持。数据格网为海量空间数据分布式存储、管理、传输、分析提供了一体化的解决方法。格网技术为VRGIS实时场景渲染和海量场景数据存储以及GIS互操作问题的解决提供了一种新思路。格网中的智能体组件动态组装应用软件将对GIS应用开发方式产生重大影响。通过建立空间信息格网可以实现中国GIS产业的跨越式发展。     

Using adaptively coupled models and high-performance computing for enabling the computability of dust storm forecasting

Forecasting dust storms for large geographical areas with high resolution poses great challenges for scientific and computational research. Limitations of computing power and the scalability of parallel systems preclude an immediate solution to such challenges. This article reports our research on using adaptively coupled models to resolve the computational challenges and enable the computability of dust storm forecasting by dividing the large geographical domain into multiple subdomains based on spatiotemporal distributions of the dust storm. A dust storm model (Eta-8bin) performs a quick forecasting with low resolution (22 km) to identify potential hotspots with high dust concentration. A finer model, non-hydrostatic mesoscale model (NMM-dust) performs high-resolution (3 km) forecasting over the much smaller hotspots in parallel to reduce computational requirements and computing time. We also adopted spatiotemporal principles among computing resources and subdomains to optimize parallel systems and improve the performance of high-resolution NMM-dust model. This research enabled the computability of high-resolution, large-area dust storm forecasting using the adaptively coupled execution of the two models Eta-8bin and NMM-dust.     

基于P2P的空间数据操作分布技术研究

分布在不同节点的空间数据库通过P2P协作共同完成复杂的空间应用任务。提出一种基于P2P的空间数据操作分布的引擎设计:引擎根据空间应用任务的解析,在P2P网络中动态地选择最佳的执行引擎,通过P2P的消息和通信机制进行协作,共同完成复杂的空间计算和空间查询任务。P2P的执行机制避免了集中式执行引擎带来的网络拥塞和单点失效问题,提高了空间数据资源和计算资源协作的可靠性和可用性。     

基于网格计算的城市地理学研究方法探讨

综合分析了城市地理学研究的几种基本方法,并重点探讨了G IS技术在城市地理学研究的重要应用。指出多源数据的获取、数据共享、模型方法的互操是目前城市地理学研究面临的重要问题,建议将网格计算这一新的分布式计算技术应用到城市地理学的研究中,并给出一个基本的城市地理学网格计算体系结构,讨论了实现这个计算体系的几个关键问题,认为采用W eb Service标准建立城市地理学研究的网格计算体系是目前可行的方法。     

基于企业服务总线的网格GIS集成研究

在面向服务的分布计算架构中,企业服务总线(ESB)提供了服务间智能化集成、管理、中介和交互功能。在利用网格架构的面向服务体系结构中,总结如何利用ESB灵活、开放的集成异构多源的GIS平台和数据源。整体架构基于OGSA,服务集成采用ESB,网格门户和实际GIS平台通过ESB连接,形成基于总线消息驱动的智能化服务集成网格系统。该系统将在Internet平台上广泛互联现有的GIS资源,实现GIS"单系统映射"。通过细粒度服务搭建和配置,生成GIS实例,直接而简单地满足具体的业务需求。     

全球离散格网的建模方法及基本问题

全球离散格网(Discrete Global Grid,DGG)模型是数字地球及空间信息格网的基础,不同的建模方法不但影响空间数据的存储和管理效率,而且影响全球GIS的操作功能。该文介绍了DGG的评价标准,将DGG的建模方法归纳为3种类型:经纬度格网模型、自适应格网模型和正多面体格网模型,重点分析了不同类型球面离散格网模型的几何结构、单元特征和应用模式。最后,提出了DGG在Global GIS中亟待解决的基本问题,包括编码、精度、应用、误差、整合和定位问题。     

A high-performance cellular automata model for urban simulation based on vectorization and parallel computing technology

Cellular automata (CA) models can simulate complex urban systems through simple rules and have become important tools for studying the spatio-temporal evolution of urban land use. However, the multiple and large-volume data layers, massive geospatial processing and complicated algorithms for automatic calibration in the urban CA models require a high level of computational capability. Unfortunately, the limited performance of sequential computation on a single computing unit (i.e. a central processing unit (CPU) or a graphics processing unit (GPU)) and the high cost of parallel design and programming make it difficult to establish a high-performance urban CA model. As a result of its powerful computational ability and scalability, the vectorization paradigm is becoming increasingly important and has received wide attention with regard to this kind of computational problem. This paper presents a high-performance CA model using vectorization and parallel computing technology for the computation-intensive and data-intensive geospatial processing in urban simulation. To transfer the original algorithm to a vectorized algorithm, we define the neighborhood set of the cell space and improve the operation paradigm of neighborhood computation, transition probability calculation, and cell state transition. The experiments undertaken in this study demonstrate that the vectorized algorithm can greatly reduce the computation time, especially in the environment of a vector programming language, and it is possible to parallelize the algorithm as the data volume increases. The execution time for the simulation of 5-m resolution and 3 × 3 neighborhood decreased from 38,220.43 s to 803.36 s with the vectorized algorithm and was further shortened to 476.54 s by dividing the domain into four computing units. The experiments also indicated that the computational efficiency of the vectorized algorithm is closely related to the neighborhood size and configuration, as well as the shape of the research domain. We can conclude that the combination of vectorization and parallel computing technology can provide scalable solutions to significantly improve the applicability of urban CA.     

A Manifesto on Mobile Computing in Geographic Education*

Abstract

Mobile, location-aware computing technology is widely available. In this article we sketch out a manifesto on mobile computing in geographic education (MoGeo) for consideration and debate within the geographic community. At the core of our argument is the idea that emerging mobile computing technologies will allow teachers to bring the classroom and pedagogic materials into the field, and that the resulting in situ educational experience will enhance learning by contextualizing the complex and abstract concepts that we teach. We provide a set of key principles that can guide the development of field experiences for students using these new technologies.     

A Manifesto on Mobile Computing in Geographic Education*

Mobile, location‐aware computing technology is widely available. In this article we sketch out a manifesto on mobile computing in geographic education (MoGeo) for consideration and debate within the geographic community. At the core of our argument is the idea that emerging mobile computing technologies will allow teachers to bring the classroom and pedagogic materials into the field, and that the resulting in situ educational experience will enhance learning by contextualizing the complex and abstract concepts that we teach. We provide a set of key principles that can guide the development of field experiences for students using these new technologies.     

Porting of a wildfire risk and fire spread application into a cloud computing environment

Effective wildfire management is an essential part of forest firefighting strategies to minimize damage to land resources and loss of human lives. Wildfire management tools often require a large number of computing resources at a specific time. Such computing resources are not affordable to local fire agencies because of the extreme upfront costs on hardware and software. The emerging cloud computing technology can be a cost- and result-effective alternative. The purpose of this paper is to present the development and the implementation of a state-of-the-art application running in cloud computing, composed of a wildfire risk and a wildfire spread simulation service. The two above applications are delivered within a web-based interactive platform to the fire management agencies as Software as a Service (SaaS). The wildfire risk service calculates and provides daily to the end-user maps of the hourly forecasted fire risk for the next 112 hours in high spatiotemporal resolution, based on forecasted meteorological data. In addition, actual fire risk is calculated hourly, based on meteorological conditions provided by remote automatic weather stations. Regarding the wildfire behavior simulation service, end users can simulate the fire spread by simply providing the ignition point and the projected duration of the fire, based on the HFire algorithm. The efficiency of the proposed solution is based on the flexibility to scale up or down the number of computing nodes needed for the requested processing. In this context, end users will be charged only for their consumed processing time and only during the actual wildfire confrontation period. The system utilizes both commercial and open source cloud resources. The current prototype is applied in the study area of Lesvos Island, Greece, but its flexibility enables expansion in different geographical areas.     

人口密度空间化的一种方法

人口密度空间化是地理学中一个重要的研究课题,但是传统方法直接生成的人口密度分布图具有不同区域间突变的缺点。该文中基于面积权重内插法与邻域平均法原理,以MapInfo为软件平台,在缺乏地形图、RS图片等资料的情况下,提出人口密度空间化的一种方法——网格单元面积权重内插法,并以丰县为研究区域进行例证。结果表明：该方法有效缓和了传统方法直接生成的人口密度图中的突变线,制作的人口密度Grid专题地图能够很好地反映人口密度的平均性,生成的人口密度三维可视化地图符合人口密度的空间分布特点。     

A parallel computing approach to viewshed analysis of large terrain data using graphics processing units

Viewshed analysis, often supported by geographic information system, is widely used in many application domains. However, as terrain data continue to become increasingly large and available at high resolutions, data-intensive viewshed analysis poses significant computational challenges. General-purpose computation on graphics processing units (GPUs) provides a promising means to address such challenges. This article describes a parallel computing approach to data-intensive viewshed analysis of large terrain data using GPUs. Our approach exploits the high-bandwidth memory of GPUs and the parallelism of massive spatial data to enable memory-intensive and computation-intensive tasks while central processing units are used to achieve efficient input/output (I/O) management. Furthermore, a two-level spatial domain decomposition strategy has been developed to mitigate a performance bottleneck caused by data transfer in the memory hierarchy of GPU-based architecture. Computational experiments were designed to evaluate computational performance of the approach. The experiments demonstrate significant performance improvement over a well-known sequential computing method, and an enhanced ability of analyzing sizable datasets that the sequential computing method cannot handle.     

An algorithm for polygon overlay using cooperative parallel processing

Abstract

With the increasing importance of parallel computing, attention must be given to utilising these resources efficiently. This article describes an algorithm to use cooperating parallel processors to solve the problem of vector polygon overlay, one of the most computationally-intensive problems in the GIS arena. The basic algorithm, which is described here using natural language, is not specific to a particular parallel architecture but has elements that are best suited to particular configurations, namely distributed-memory Multiple Instruction stream Multiple Data stream (MIMD) architectures. The intention is to provide an algorithm which utilises the potential of such architectures by distributing the computational load over several cooperating processors.     

Mapping Systems and GIS: A Case Study using the Ghana National Grid

The problem of incompatible projections and conversion between mapping systems is of general concern to those involved in the collection of natural resources data. The Ghana National Grid (GNG) is an example of a mapping system that is not defined in image processing and GIS software and for which the transformation parameters are not readily available in the literature. Consequently, integrating GNG topographic map data within a GIS with data derived from other sources can be problematic. In this paper a practical solution for deriving the required transformation parameters to convert from the World Geodetic System of 1984 (WGS84) to the GNG system is demonstrated. The method uses a single geodetic control point, available 1:50 000 topographic maps and a SPOT satellite panchromatic image geo-referenced to GNG. The resultant parameters are applied to road survey data in Universal Transverse Mercator (UTM) format for overlay with the SPOT image. Despite the approximations made in applying the method, when compared against official estimates of the datum transformation parameters, this relatively simple procedure resulted in estimates that appear acceptable in regard to combining data sets at a nominal scale of 1:50000.     

Agent-based modeling within a cyberinfrastructure environment: a service-oriented computing approach

Agent-based models (ABM) allow for the bottom-up simulation of dynamics in complex adaptive spatial systems through the explicit representation of pattern–process interactions. This bottom-up simulation, however, has been identified as both data- and computing-intensive. While cyberinfrastrucutre provides such support for intensive computation, the appropriate management and use of cyberinfrastructure (CI)-enabled computing resources for ABM raise a challenging and intriguing issue. To gain insight into this issue, in this article we present a service-oriented simulation framework that supports spatially explicit agent-based modeling within a CI environment. This framework is designed at three levels: intermodel, intrasimulation, and individual. Functionalities at these levels are encapsulated into services, each of which is an assembly of new or existing services. Services at the intermodel and intrasimulation levels are suitable for generic ABM; individual-level services are designed specifically for modeling intelligent agents. The service-oriented simulation framework enables the integration of domain-specific functionalities for ABM and allows access to high-performance and distributed computing resources to perform simulation tasks that are often computationally intensive. We used a case study to investigate the utility of the framework in enabling agent-based modeling within a CI environment. We conducted experiments using supercomputing resources on the TeraGrid – a key element of the US CI. It is indicated that the service-oriented framework facilitates the leverage of CI-enabled resources for computationally intensive agent-based modeling.     

地球系统空间格网及其应用模式

全球变化与地球系统科学研究涉及跨圈层、跨投影带的中-大-超大尺度问题,对全球地学信息系统(GGIS)、全球空间格网(GSG)及数字地球提出了新挑战。在剖析GSG研究现状的基础上,指出需从地球系统整体上设计一个多领域普适的全球三维空间格网———地球系统空间格网(ESSG),以支撑全球变化及地球系统科学研究。结合领域特点,提出了构建ESSG的8项基本要求,并基于球体退化八叉树格网(SDOG)设计并实现了一种满足该要求的SDOG-ESSG模型;介绍了SDOG-ESSG模型在地球系统空间数据集成、三维建模、多尺度表达、对象变化表达、数据检索与云服务、过程模拟及空间环境安全规划与可视化决策等方面的7种典型应用模式。