共查询到20条相似文献，搜索用时 31 毫秒
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Today, many real‐time geospatial applications (e.g. navigation and location‐based services) involve data‐ and/or compute‐intensive geoprocessing tasks where performance is of great importance. Cloud computing, a promising platform with a large pool of storage and computing resources, could be a practical solution for hosting vast amounts of data and for real‐time processing. In this article, we explored the feasibility of using Google App Engine (GAE), the cloud computing technology by Google, for a module in navigation services, called Integrated GNSS (iGNSS) QoS prediction. The objective of this module is to predict quality of iGNSS positioning solutions for prospective routes in advance. iGNSS QoS prediction involves the real‐time computation of large Triangulated Irregular Networks (TINs) generated from LiDAR data. We experimented with the Google App Engine (GAE) and stored a large TIN for two geoprocessing operations (proximity and bounding box) required for iGNSS QoS prediction. The experimental results revealed that while cloud computing can potentially be used for development and deployment of data‐ and/or compute‐intensive geospatial applications, current cloud platforms require improvements and special tools for handling real‐time geoprocessing, such as iGNSS QoS prediction, efficiently. The article also provides a set of general guidelines for future development of real‐time geoprocessing in clouds. 相似文献
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ABSTRACTLight detection and ranging (LiDAR) data are essential for scientific discoveries such as Earth and ecological sciences, environmental applications, and responding to natural disasters. While collecting LiDAR data over large areas is quite possible the subsequent processing steps typically involve large computational demands. Efficiently storing, managing, and processing LiDAR data are the prerequisite steps for enabling these LiDAR-based applications. However, handling LiDAR data poses grand geoprocessing challenges due to data and computational intensity. To tackle such challenges, we developed a general-purpose scalable framework coupled with a sophisticated data decomposition and parallelization strategy to efficiently handle ‘big’ LiDAR data collections. The contributions of this research were (1) a tile-based spatial index to manage big LiDAR data in the scalable and fault-tolerable Hadoop distributed file system, (2) two spatial decomposition techniques to enable efficient parallelization of different types of LiDAR processing tasks, and (3) by coupling existing LiDAR processing tools with Hadoop, a variety of LiDAR data processing tasks can be conducted in parallel in a highly scalable distributed computing environment using an online geoprocessing application. A proof-of-concept prototype is presented here to demonstrate the feasibility, performance, and scalability of the proposed framework. 相似文献
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《International Journal of Digital Earth》2013,6(2):111-134
Abstract While significant progress has been made to implement the Digital Earth vision, current implementation only makes it easy to integrate and share spatial data from distributed sources and has limited capabilities to integrate data and models for simulating social and physical processes. To achieve effectiveness of decision-making using Digital Earth for understanding the Earth and its systems, new infrastructures that provide capabilities of computational simulation are needed. This paper proposed a framework of geospatial semantic web-based interoperable spatial decision support systems (SDSSs) to expand capabilities of the currently implemented infrastructure of Digital Earth. Main technologies applied in the framework such as heterogeneous ontology integration, ontology-based catalog service, and web service composition were introduced. We proposed a partition-refinement algorithm for ontology matching and integration, and an algorithm for web service discovery and composition. The proposed interoperable SDSS enables decision-makers to reuse and integrate geospatial data and geoprocessing resources from heterogeneous sources across the Internet. Based on the proposed framework, a prototype to assist in protective boundary delimitation for Lunan Stone Forest conservation was implemented to demonstrate how ontology-based web services and the services-oriented architecture can contribute to the development of interoperable SDSSs in support of Digital Earth for decision-making. 相似文献
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《International Journal of Digital Earth》2013,6(4):404-425
Abstract The emergence of Cloud Computing technologies brings a new information infrastructure to users. Providing geoprocessing functions in Cloud Computing platforms can bring scalable, on-demand, and cost–effective geoprocessing services to geospatial users. This paper provides a comparative analysis of geoprocessing in Cloud Computing platforms – Microsoft Windows Azure and Google App Engine. The analysis compares differences in the data storage, architecture model, and development environment based on the experience to develop geoprocessing services in the two Cloud Computing platforms; emphasizes the importance of virtualization; recommends applications of hybrid geoprocessing Clouds, and suggests an interoperable solution on geoprocessing Cloud services. The comparison allows one to selectively utilize Cloud Computing platforms or hybrid Cloud pattern, once it is understood that the current development of geoprocessing Cloud services is restricted to specific Cloud Computing platforms with certain kinds of technologies. The performance evaluation is also performed over geoprocessing services deployed in public Cloud platforms. The tested services are developed using geoprocessing algorithms from different vendors, GeoSurf and Java Topology Suite. The evaluation results provide a valuable reference on providing elastic and cost-effective geoprocessing Cloud services. 相似文献
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In a service‐oriented environment, Web geoprocessing services can provide geoprocessing functions for a variety of applications including Sensor Web. Connecting Sensor Web and geoprocessing services together shows great potentail to support live geoprocessing using real‐time data inputs. This article proposes a task ontology driven approach to live geoprocessing. The task in the ontology contains five aspects: task type, task priority, task constraints, task model, and task process. The use of the task ontology in driving live geoprocessing includes the following steps: (1) Task model generation, which generates a concrete process model to fulfill user demands; (2) Process model instantiation, which transforms the process model into an executable workflow; (3) Workflow execution: the workflow engine executes the workflow to generate value‐added data products using Sensor Web data as inputs. The approach not only helps create semantically correct connections between Sensor Web and Web geoprocessing services, but also provides sharable problem solving knowledge using process models. A prototype system, which leverages Web 2.0, Sensor Web, Semantic Web, and geoprocessing services, is developed to demonstrate the applicability of the approach. 相似文献
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none 《The Cartographic journal》2013,50(2):153-156
AbstractThere is currently a high demand for spatial data usage within web applications. From a technical viewpoint, web services and geoportals aim to fulfil user requirements; however, the current cartographic methods do not satisfy the needs of the end users. The problem is more challenging when the final map contains data from various sources that have various cartographic characteristics; therefore, the vital information might be located under the base map layer. In this paper, we propose the concept of layer priorities as foreground, middle ground or background, and we propose the two following methods to enhance the symbolisation: polygon overlay and colour saturation methods. The results from two case studies show that these methods can satisfy the requirements of the end users. 相似文献
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C. Stasch B. Pross B. Gräler C. Malewski C. Förster S. Jirka 《International Journal of Digital Earth》2018,11(1):64-78
ABSTRACTNovel sensor technologies are rapidly emerging. They enable a monitoring and modelling of our environment in a level of detail that was not possible a few years ago. However, while the raw data produced by these sensors are useful to get a first overview, it usually needs to be post-processed and integrated with other data or models in different applications. In this paper, we present an approach for integrating several geoprocessing components in the TaMIS water dam monitoring system developed with the Wupperverband, a regional waterbody authority in Germany. The approach relies upon the OGC Web Processing Service and is tightly coupled with Sensor Observation Service instances running at the Wupperverband. Besides implementing the standardized XML-based interface, lightweight REST APIs have been developed to ease the integration with thin Web clients and other Web-based components. Using this standards-based approach, new processing facilities can be easily integrated and coupled with different observation data sources. 相似文献
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An online spatial biodiversity model (SBM) for optimized and automated spatial modelling and analysis of geospatial data is proposed, which is based on web processing service (WPS) and web service orchestration (WSO) in parallel computing environment. The developed model integrates distributed geospatial data in geoscientific processing workflow to compute the algorithms of spatial landscape indices over the web using free and open source software. A case study for Uttarakhand state of India demonstrates the model outputs such as spatial biodiversity disturbance index (SBDI) and spatial biological richness index (SBRI). In order to optimize and automate, an interactive web interface is developed using participatory GIS approaches for implementing fuzzy AHP. In addition, sensitivity analysis and geosimulation experiments are also performed under distributed GIS environment. Results suggest that parallel algorithms in SBM execute faster than sequential algorithms and validation of SBRI with biological diversity shows significant correlation by indicating high R2 values. 相似文献
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Requirements for Next Generation Spatial Data Infrastructures-Standardized Web Based Geoprocessing and Web Service Orchestration 总被引：2，自引：0，他引：2
Spatial Data Infrastructures (SDI) have been widely accepted to exchange geospatial data among organizations. Today SDIs main focus lies on the provision of geospatial data in the form of distributed spatial web services, the retrieval through catalogues, and visualization in the form of Web Map Services (WMS). The hypothesis presented in this paper takes SDI's one step further by providing a method to process geodata in an Open Geospatial Consortium (OGC) compliant way into information. Two case studies present the potential of standardized geoprocessing services. In addition, this paper addresses the problem of service chaining by providing a system architecture to implement complex geoprocessing models and workflows based on web services using Web Service Orchestration (WSO). The proposed methods utilize spatial standards provided by OGC, the International Organization for Standardization (ISO) and ‘mainstream IT’ standards provided by the World Wide Web Consortium (W3C) and the Organization for the Advancement of Structured Information Standards (OASIS) to establish a generic web service architecture for providing common geoprocessing capabilities (e.g. spatial algorithms, map algebra, etc.) for usage in SDIs. 相似文献
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地理数据共享与互操作技术 总被引：4，自引：0，他引：4
从地理数据共享的需求出发,概述了实现数据共享的途径．重点阐述了由OOC(开放式地理信息系统协会)儡导地理数据处理互操作技术(Oeoprocessing Interoperability)OGIS(开放式地理数据互操作规范)及其内容。 相似文献
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The emergence of the Sensor Web has paved the way for a new set of innovative software applications that exploit the enhanced availability of real‐time information. This article describes one such application built from Sensor Web components that aggregates GPS track data from a fleet of vehicles to provide an overview of road traffic congestion at the city scale. The application embodies a Service Oriented Architecture; web service components are used to archive and pre‐process incoming sensor observations, to encapsulate a horizontally partitioned spatial database that performs geoprocessing, and to disseminate results to client applications. Our results confirm that floating car data can provide an accurate depiction of current road traffic conditions. The presented solution uses Open Geospatial Consortium web services where possible and serves to highlight the difficulties inherent in achieving horizontal database scalability in sensor based geoprocessing systems. 相似文献
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传统的空间信息处理建模工具,如ArcGIS ModelBuilder,聚焦于地理空间信息处理算子的组合建模。“模型网”的提出对已有的空间信息处理建模工具提出了新的挑战,一方面,现有的空间信息处理建模工具需要能够支持网络环境,支持空间信息服务的即插即用;另一方面,服务需要与复杂地学模型耦合,支持基于时间步长的地学模型运行。针对组件与服务并存的现状以及异构模型和算法兼容性差等问题,提出了组件与服务耦合的地学模型集成方法;并从“模型即服务”和模型集成需求出发,提出了基于WebSocket协议发布地学模型的新方法,实现了基于时间步长的地学模型在线共享。采用科学工作流技术实现了遵循国际开放地理空间信息联盟（Open Geospatial Consortium,OGC）标准的空间信息服务、基于WebSocket协议的地学模型服务、遵循OpenMI开放建模接口规范的模型组件集成,具有逻辑一致、物理分隔、执行可控等特点。利用该方法将传统的空间信息处理建模工具拓展为地学模型集成工具,并应用于具体案例中,验证了方法的可行性。 相似文献
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GeoPW: Laying Blocks for the Geospatial Processing Web 总被引：2，自引：0，他引：2
Peng Yue Jianya Gong Liping Di Jie Yuan Lizhi Sun Ziheng Sun Qian Wang 《Transactions in GIS》2010,14(6):755-772
Recent advances in Web‐related technologies have significantly promoted the wide sharing and integrated analysis of distributed geospatial data. Geospatial applications often involve diverse sources of data and complex geoprocessing functions. Existing Web‐based GIS focuses more on access to distributed geospatial data. In scientific problem solving, the ability to carry out geospatial analysis is essential to geoscientific discovery. This article presents the design and implementation of GeoPW, a set of services providing geoprocessing functions over the Web. The concept of the Geospatial Processing Web is discussed to address the geoprocessing demands in the emerging information infrastructure, and the role of GeoPW in establishing the Geospatial Processing Web is identified. The services in GeoPW are implemented by developing middleware that wraps legacy GIS analysis components to provide a large number of geoprocessing utilities over the Web. These services are open and accessible to the public, and they support integrated geoprocessing on the Web. 相似文献
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GE Renyan 《地球空间信息科学学报》2013,16(1):29-32
ABSTRACT With the help of CCD images, the realization of high precision positioning and measurement has become the basic standard for machine vision and real time photogrammetry systems. However, deformation and other sorts of degradation occurring during transmission are major limiting factors of the precision attainable with most current CCD cameras and frame grabbers. So a precise radiometric and geometric transmission of images from CCD sensor to memory is a fundamental aspect of CCD camera calibration. The geometric calibration system, which uses some image processing algorithms of the CCD camera based on the researched and developed system is discussed. The reliability and validity are also discussed. The experimental results for the calibration of the CCD array will be taken as an important quality index for CCD evaluation. 相似文献
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天地一体化数字影像地理空间信息的获取与更新 总被引：2，自引：0，他引：2
数字地理空间信息在经济社会发展、应急救援服务及国防军事中的作用越来越重要。网格(Grid)技术正成为继Internet和Web之后的第三代网络技术，地球空间信息网格体系的发展是对测绘科技发展的又一次机遇，航空／航天数字栅格图像数据能为现代网格地图，或无级无缝在线服务的电子地图提供丰富的动态的数据源。进入21世纪以来，多种方式的天地一体化对地观测技术体系不断发展，能全天时、快速、高精度地获取地理空间的数字影像数据。同时，为了适应不同领域和目标应用的需要，建立或更新GIS数据库的数据，图像数据处理与分析理论和方法的研究也成果斐然。 相似文献