基于GIS服务链的遥感影像分布式融合处理

提出了基于Web服务技术、OGC规范和工作流技术,以实现与平台无关的、具备流程编排能力的地理空间处理服务链框架,用于支持复杂的在线空间处理任务.在该框架基础上实现了一个在线遥感影像融合处理示例.该示例展示了利用OGC WCS、WPS,WSDL,UDDI和BPEL4WS等成熟的标准规范来构建GIS服务链,使得客户应用程序...     

The framework of a geospatial semantic web-based spatial decision support system for Digital Earth

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.     

A Service Oriented Geoprocessing System for Real‐Time Road Traffic Monitoring

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.     

Uses of online geoprocessing technology in analyses and case studies: a systematic analysis of literature

Interpreting spatial data to derive information is a core task in the field of Geographic Information Science and Technology. A logical step following the collection of data in online repositories is to provide geoprocessing technology for analysing data online. Online geoprocessing technology can be employed for providing a specified set of tools in a theme-specific platform, documenting a model or workflow and making it widely available, automating recurring tasks or offering simple tools to a large user group. This systematic analysis of literature evaluates how much available online geoprocessing tools are being used for answering questions in specific application contexts. An initial set of articles is derived from a keyword-based search in the database Scopus. This set of articles is manually filtered to identify applications of online geoprocessing tools. The analysis of application-related articles shows that virtually all applications require further development of tools. Experts outside the spatial information science field are still underrepresented regarding the use of this technology. The required adaptation of technology for user tasks is identified as major barrier for the wide use of online geoprocessing. Further research needs to assess user tasks and how online geoprocessing can provide the required functions in a user-oriented manner.     

Geoprocessing in Cloud Computing platforms – a comparative analysis

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.     

Knowledge Based Soil Attribute Mapping In GIS: The Expector Method

EXPECTOR is a method of combining data and 'expert' knowledge within a Geographic Information System to provide information on the occurrence of spatially distributed attributes. It was developed to predict soil property values from spatially variable input data. Although initially developed to provide soil surveyors with a quantitative soil mapping method, it also has applications in land evaluation, land capability assessment, geological mapping and in precision agriculture. It operates on the basis that the state of a particular property, which may be difficult to measure directly, can be inferred from other (more measurable) entities and a knowledge of their inter–relationships. The method has been implemented as a stand–alone 'Knowledge Editing' module for the PC that can be linked to raster GIS packages. This paper describes the basis of the method and illustrates its use with an example describing the production of a surface clay content map for a small catchment in south–western Western Australia.     

Advancements in web‐mapping tools for land use and marine spatial planning

Land use and marine spatial planning processes are increasingly supported by systematic assessment techniques, particularly by multi‐criteria spatial analysis methods. This has been facilitated by the growing release and uptake of web‐mapping tools, which contribute to transparent, consistent, and informed planning processes and decisions. This article reviews the usability, functionality, and applicability of contemporary planning web‐mapping tools to identify the state‐of‐the‐art and future prospects. The review reveals that interfaces are increasingly available and intuitively applicable by non‐specialized users. Basic map navigation and data querying functionality is being expanded to incorporate advanced map‐making and online data geoprocessing capabilities that enable deriving new data and insights. However, the majority of published planning web tools are one‐off solutions, and a disconnect between research and practice is rendering many of these inaccessible or obsolete. Despite the significant progress made in advancing their provision in the last decade, there is a need for developing transferable interfaces that are maintained beyond project end dates, for them to effectively and consistently support planning processes.     

面向城市级服务的地理实体分类方法与建库分析北大核心CSCD

地理实体数据是实景三维结构化和语义化产品,是实景三维建设标准化产品数据。本文在分析自然资源部技术指导文件及各试点城市地理实体建设相关研究和应用的基础上,基于珠海市试验片区实体建库实践经验,提出了面向城市级服务的地理实体分级分类方法,构建了面向应用服务的地理实体数据集。并以院落、建筑物、道路实体等为例,深入分析其数据组织结构,探索了面向国土空间规划和城市精细治理方面的应用研究。     

Real-time fusion of multiple videos and 3D real scenes based on optimal viewpoint selection

3D real scenes are a digital virtual space that represents and portrays the real world in a photorealistic, three-dimensional, and sequential manner. Existing methods for constructing and updating 3D models, such as oblique photography and laser scanning, are difficult to meet the demand of perceiving the real world intuitively, dynamically, and in real time. In recent years, the method of integrating rapidly rising video data and 3D models has become increasingly popular. Compared with existing methods, it enhances the real-time perception of 3D scenes by taking advantage of the real-time character of videos and the intuitive character of 3D models. In this article, we propose a real-time fusion method of multiple videos and 3D real scenes based on optimal viewpoint selection. To begin, 3D reconstruction and video camera calibration were used to prepare the basic data for the fusion of videos and 3D model. Second, a visible-surface detection-based video space restoration method was provided, and the overlapping region between multiple videos was determined. Third, to split the overlapping region into the corresponding camera spaces, a segmentation method based on optimal viewpoint selection was given. Finally, the 2D videos were dynamically fitted to the 3D model using the dynamic texture mapping method, while accomplishing the fusing and rendering of the 3D real scene. After experimental verification, the overall effect of the multiple videos and 3D real scene fusion system implemented using the method proposed in this article is better, while the algorithm is less time-consuming and efficient in rendering.     

海洋信息服务聚合平台应用研究

以当前海洋信息集成国内外的研究现状和存在的问题为背景;以海洋信息集成、业务整合的迫切需求,以及海洋地理信息系统的发展为驱动;以基于Mashup的信息聚合技术和Web服务技术为支持,提出了海洋信息服务聚合平台的体系框架。研究了面向聚合应用的海洋信息服务模式和基于Mashup的海洋信息服务的聚合方法。最后以海洋信息服务聚合平台为基础,以南海基础地理数据为背景数据．研究了基于聚合平俞的分布式海洋观测数据和海洋模型的集成方法。实验表明基于Mashup的海洋信息服务聚合方法可以轻松、快速地重组来自不同地方的数据服务和模型服务,能够满足海洋研究因情景而不断变化的需求。     

面向需求的启发式网络地图自动制图研究

互联网的发展要求提供个性化的网络地图自动制图服务。文中运用Web Servers和专家知识库耦合技术研究面向需求的启发式网络地图自动制图原理和方法,该方法将不同用户的网络地图需求视为对地理空间信息一系列的启发式再识别过程,提取出相应的需求参数建立用户兴趣模型,并运用相关算法实现数据的加载以及对地理实体的符号化表示。实践表明,该系统实例可以改善互联网上面向用户需求的个性化网络地图自动制图服务。     

基于可量测实景影像的空间信息服务

讨论了面向第三代Internet和Web2．0模式下的空间信息服务需求，提出了空间信息服务的数字地球影像体系，并给出了一种可量测实景影像数据获取、组织管理以及与4D产品集成的技术途径。首次提出了可量测实景影像空间信息服务体系，对基于可量测实景影像的空间信息服务的前景进行了展望。     

Semantic typing of linked geoprocessing workflows

In Geographic Information Systems (GIS), geoprocessing workflows allow analysts to organize their methods on spatial data in complex chains. We propose a method for expressing workflows as linked data, and for semi-automatically enriching them with semantics on the level of their operations and datasets. Linked workflows can be easily published on the Web and queried for types of inputs, results, or tools. Thus, GIS analysts can reuse their workflows in a modular way, selecting, adapting, and recommending resources based on compatible semantic types. Our typing approach starts from minimal annotations of workflow operations with classes of GIS tools, and then propagates data types and implicit semantic structures through the workflow using an OWL typing scheme and SPARQL rules by backtracking over GIS operations. The method is implemented in Python and is evaluated on two real-world geoprocessing workflows, generated with Esri's ArcGIS. To illustrate the potential applications of our typing method, we formulate and execute competency questions over these workflows.     

OGC与我国地理信息产业

通过对开放地理信息系统联合会(OGC)的现有规范介绍，探讨了OGC规范与地理空间数据、服务互操作性的关系，以及对我国地理信息产业发展的意义。     

基于RIA地理信息共享平台的运维系统研究

运维系统是保证整个地理系统共享平台正常运行的重要组成部分,具有业务流程复杂,数据交互需求大等特点,由于基于B/S模式的传统Web应用程序在页面交互、数据可视化、传输效率等方面弱点制约其在运维系统中的应用,本文引入RIA技术有效解决上述问题。研究了RIA基本原理及应用可行性,并设计了基于该技术的Web应用程序结构模型。最后通过系统的实例运行,表明基于RIA的运维系统具有良好的性能。     

Ontological Engineering for Interpreting Geospatial Queries

Despite advancements in geographic information system (GIS) technology, the efficient and effective utilization of GIS to solve geospatial problems is a daunting process requiring specialized knowledge and skills. Two of the most important and burdensome tasks in this process are interpretation of geospatial queries and mapping the interpreted results into geospatial data models and geoprocessing operations. With the current state of GIS, there exists a gap between the knowledge user's possess and the knowledge and skills they need to utilize GIS for solving problems. Currently, users resort to training and practice on GIS technology or involving GIS experts. Neither of these options is optimal and there is a need for a new approach that automates geoprocessing tasks using GIS technology. This paper presents an ontological engineering methodology that uses multiple ontologies and the mappings among them to automate certain tasks related to interpretation of geospatial queries and mapping the interpreted results into geospatial data models and geoprocessing operations. The presented methodology includes conceptualization of geospatial queries, knowledge representation for queries, techniques for relating elements in different ontologies, and an algorithm that uses ontologies to map queries to geoprocessing operations.     

在Google Earth平台上的虚拟社区构建

介绍虚拟现实技术及其在GIS中的应用,并采用Google Earth作为平台,利用已有数据资料进行虚拟社区的构建,并借助Google Earth进行发布,初步实现了相关功能,在一定程度上实现了虚拟现实技术与传统地理信息的结合。     

3D change detection at street level using mobile laser scanning point clouds and terrestrial images

Automatic change detection and geo-database updating in the urban environment are difficult tasks. There has been much research on detecting changes with satellite and aerial images, but studies have rarely been performed at the street level, which is complex in its 3D geometry. Contemporary geo-databases include 3D street-level objects, which demand frequent data updating. Terrestrial images provides rich texture information for change detection, but the change detection with terrestrial images from different epochs sometimes faces problems with illumination changes, perspective distortions and unreliable 3D geometry caused by the lack of performance of automatic image matchers, while mobile laser scanning (MLS) data acquired from different epochs provides accurate 3D geometry for change detection, but is very expensive for periodical acquisition. This paper proposes a new method for change detection at street level by using combination of MLS point clouds and terrestrial images: the accurate but expensive MLS data acquired from an early epoch serves as the reference, and terrestrial images or photogrammetric images captured from an image-based mobile mapping system (MMS) at a later epoch are used to detect the geometrical changes between different epochs. The method will automatically mark the possible changes in each view, which provides a cost-efficient method for frequent data updating. The methodology is divided into several steps. In the first step, the point clouds are recorded by the MLS system and processed, with data cleaned and classified by semi-automatic means. In the second step, terrestrial images or mobile mapping images at a later epoch are taken and registered to the point cloud, and then point clouds are projected on each image by a weighted window based z-buffering method for view dependent 2D triangulation. In the next step, stereo pairs of the terrestrial images are rectified and re-projected between each other to check the geometrical consistency between point clouds and stereo images. Finally, an over-segmentation based graph cut optimization is carried out, taking into account the color, depth and class information to compute the changed area in the image space. The proposed method is invariant to light changes, robust to small co-registration errors between images and point clouds, and can be applied straightforwardly to 3D polyhedral models. This method can be used for 3D street data updating, city infrastructure management and damage monitoring in complex urban scenes.