An integrated geospatial information service system for disaster management in China

The Chinese Government and citizens face enormous challenges of disaster management as widespread devastation, economic damages, and loss of human lives caused by increasing natural disasters. Disaster management requires a complicated iterative process that includes disaster monitoring, early detection, forecasting, loss assessment, and efficient analysis of disaster reduction. Each task typically involves the use of technologists and multiple geospatial information resources, including sensors, data sources, models, geo-tools, software packages, and computing resources. However, most existing disaster management systems operate in a typical passive data-centric mode, where resources cannot be fully utilized. This impediment is partially being addressed by the increasingly complex application requirements and the growing availability of diverse resources. In this paper, we summarize and analyze the practical problems experienced by the National Disaster Reduction Application System of China. To address the issues of data-centric, centralized, isolated solutions, we propose a novel Focusing Service Mechanism, which is capable of scheduling and allocating for optimum utilization of multiple resources, to dynamically generate collaborative and on-demand disaster information services. We also demonstrate the design and implementation of the Integrated Disaster Information Service System (IDISS). Through the service strategies of Virtualizing, Wrapping, and Integrating, disaster-related resources are constructed into services in the IDISS. These services are dynamically aggregated into focusing service chains, for diverse disaster management tasks. Actual applications illustrate that the proposed service system can significantly improve the capability of disaster management in China.     

兼容VGI与众包的灾害信息管理系统研究

针对地理信息采集VGI和众包传播模式在灾害救援中发挥的巨大作用,设计并实现了兼容VGI与众包的灾害信息管理系统VDMS,实例验证了该系统的有效性。结果表明:VDMS系统可以将VGI众包采集流程集成到灾害信息管理中,提高了灾害信息采集效率。设计了一种灾害信息管理系统VDMS,实现了灾害发生时海量数据的高效管理与有效利用。     

Crowdsourcing geospatial data

In this paper we review recent developments of crowdsourcing geospatial data. While traditional mapping is nearly exclusively coordinated and often also carried out by large organisations, crowdsourcing geospatial data refers to generating a map using informal social networks and web 2.0 technology. Key differences are the fact that users lacking formal training in map making create the geospatial data themselves rather than relying on professional services; that potentially very large user groups collaborate voluntarily and often without financial compensation with the result that at a very low monetary cost open datasets become available and that mapping and change detection occur in real time. This situation is similar to that found in the Open Source software environment.We shortly explain the basic technology needed for crowdsourcing geospatial data, discuss the underlying concepts including quality issues and give some examples for this novel way of generating geospatial data. We also point at applications where alternatives do not exist such as life traffic information systems. Finally we explore the future of crowdsourcing geospatial data and give some concluding remarks.     

Automatic search of geospatial features for disaster and emergency management

Although the fast development of OGC (Open Geospatial Consortium) WFS (Web Feature Service) technologies has undoubtedly improved the sharing and synchronization of feature-level geospatial information across diverse resources, literature shows that there are still apparent limitations in the current implementation of OGC WFSs. Currently, the implementation of OGC WFSs only emphasizes syntactic data interoperability via standard interfaces and cannot resolve semantic heterogeneity problems in geospatial data sharing. To help emergency responders and disaster managers find new ways of efficiently searching for needed geospatial information at the feature level, this paper aims to propose a framework for automatic search of geospatial features using Geospatial Semantic Web technologies and natural language interfaces. We focus on two major tasks: (1) intelligent geospatial feature retrieval using Geospatial Semantic Web technologies; (2) a natural language interface to a geospatial knowledge base and web feature services over the Semantic Web. Based on the proposed framework we implemented a prototype. Results show that it is practical to directly discover desirable geospatial features from multiple semantically heterogeneous sources using Geospatial Semantic Web technologies and natural language interfaces.     

A parallel approach for improving Geo-SPARQL query performance

Geospatial Semantic Web promises better retrieval geospatial information for Digital Earth systems by explicitly representing the semantics of data through ontologies. It also promotes sharing and reuse of geospatial data by encoding it in Semantic Web languages, such as RDF, to form geospatial knowledge base. For many applications, rapid retrieval of spatial data from the knowledge base is critical. However, spatial data retrieval using the standard Semantic Web query language – Geo-SPARQL – can be very inefficient because the data in the knowledge base are no longer indexed to support efficient spatial queries. While recent research has been devoted to improving query performance on general knowledge base, it is still challenging to support efficient query of the spatial data with complex topological relationships. This research introduces a query strategy to improve the query performance of geospatial knowledge base by creating spatial indexing on-the-fly to prune the search space for spatial queries and by parallelizing the spatial join computations within the queries. We focus on improving the performance of Geo-SPARQL queries on knowledge bases encoded in RDF. Our initial experiments show that the proposed strategy can greatly reduce the runtime costs of Geo-SPARQL query through on-the-fly spatial indexing and parallel execution.     

基于全球剖分网格的地理空间信息保障服务技术研究

随着空间和对地观测技术的飞速发展,建立一个适应全球的多源、多尺度、多时相跨平台统一数据组织的网格框架具有非常重要的意义。当前地理空间数据的生产、维护分散在不同单位,且采用的数据网格标准各异,造成了部门或系统之间、不同历史阶段之间标准不统一。本文针对高分专项地理空间信息保障库对数据资源全局展示、关联检索和模版应用等综合服务展示需求,基于GeoSOT网格与编码理论体系,提出了"地理空间信息全球统一网格化编码管理"的数据剖分组织解决思路,并进行了系统分析、研究与设计。通过试验证明,基于GeoSOT虚拟一张图的数据组织管理方法能够显著提高地理空间信息保障服务系统的整体应用效能。     

GeoScope: Full 3D geospatial information system case study

Aiming at the integrative management and comprehensive applications of large-scale 3D geospatial information covering the full 3D space of a city,this paper briefly introduces the design and implementation of a full 3D GIS platform:GeoScope,which provides a professional solution for the massive full three-dimensional geospatial data integration,management,analysis,visualization,and applications.GeoScope is characterized by:(1) extendible software architecture based on the hierarchical message bus,facilitates multimodal integrative applications of 2D GIS and 3D GIS;(2) unified 3D city models,support multiscale semantic representation of outdoor & indoor and aboveground & underground 3D objects;(3) high-efficient 3D geospatial database engine,supports integrated management of massive 3D geospatial data for real-time applications;and (4) high-performance visualization engine exploiting the massively parallel computation architecture of modern GPUs,supports real-time realistic rendering of large-scale complicated 3D geospatial environments.The successful pilot application of GeoScope is also illustrated with the 3D city models of 8494 km2 of the whole Wuhan City,the largest city in middle China.     

Improving geospatial query performance of an interoperable geographic situation‐awareness system for disaster response

Disaster response operations require fast and coordinated actions based on real‐time disaster situation information. Although crowdsourced geospatial data applications have been demonstrated to be valuable tools for gathering real‐time disaster situation information, they only provide limited utility for disaster response coordination because of the lack of semantic compatibility and interoperability. To help overcome the semantic incompatibility and heterogeneity problems, we use Geospatial Semantic Web (GSW) technologies. We then combine GSW technologies with Web Feature Service requests to access multiple servers. However, a GSW‐based geographic information system often has poor performance due to the complex geometric computations required. The objective of this research is to explore how to use optimization techniques to improve the performance of an interoperable geographic situation‐awareness system (IGSAS) based on GSW technologies for disaster response. We conducted experiments to evaluate various client‐side optimization techniques for improving the performance of an IGSAS prototype for flood disaster response in New Haven, Connecticut. Our experimental results show that the developed prototype can greatly reduce the runtime costs of geospatial semantic queries through on‐the‐fly spatial indexing, tile‐based rendering, efficient algorithms for spatial join, and caching, especially for those spatial‐join geospatial queries that involve a large number of spatial features and heavy geometric computation.     

Spatial cloud computing: how can the geospatial sciences use and help shape cloud computing?

Abstract

The geospatial sciences face grand information technology (IT) challenges in the twenty-first century: data intensity, computing intensity, concurrent access intensity and spatiotemporal intensity. These challenges require the readiness of a computing infrastructure that can: (1) better support discovery, access and utilization of data and data processing so as to relieve scientists and engineers of IT tasks and focus on scientific discoveries; (2) provide real-time IT resources to enable real-time applications, such as emergency response; (3) deal with access spikes; and (4) provide more reliable and scalable service for massive numbers of concurrent users to advance public knowledge. The emergence of cloud computing provides a potential solution with an elastic, on-demand computing platform to integrate – observation systems, parameter extracting algorithms, phenomena simulations, analytical visualization and decision support, and to provide social impact and user feedback – the essential elements of the geospatial sciences. We discuss the utilization of cloud computing to support the intensities of geospatial sciences by reporting from our investigations on how cloud computing could enable the geospatial sciences and how spatiotemporal principles, the kernel of the geospatial sciences, could be utilized to ensure the benefits of cloud computing. Four research examples are presented to analyze how to: (1) search, access and utilize geospatial data; (2) configure computing infrastructure to enable the computability of intensive simulation models; (3) disseminate and utilize research results for massive numbers of concurrent users; and (4) adopt spatiotemporal principles to support spatiotemporal intensive applications. The paper concludes with a discussion of opportunities and challenges for spatial cloud computing (SCC).     

Developing Web-based Mapping Applications Through Distributed Object Technology

Emerging web-based mapping technologies use the World Wide Web (WWW) and Internet protocols to provide the ability to distribute, access, and visualize geospatial information over the Internet. Many web-based mapping applications have been developed to deliver geospatial information within and across organizations and even to the public at large. A major technological challenge is to achieve interoperability amongst web-based mapping applications so that mapping and geoprocessing resources distributed over the Internet can be shared and integrated. This paper presents an approach to the development of web-based mapping applications using distributed object technology in order to enable interoperability. Distributed object technology combines object technology, which utilizes reusable software components (called objects) that model real-world entities to build software systems, and distributed computing, which allows computing resources to be distributed and accessed over computer networks. The paper introduces a distributed object technology, the Common Object Request Broker Architecture (CORBA); proposes an architecture for web-based mapping using CORBA; and presents a prototype implementation.     

An evaluation of integrating multisourced sensors for disaster management

Disaster management and in particular disaster response phase are highly time-sensitive and dynamic processes, demanding that real-time information reaches disaster responders prior making critical decisions. During the last decade, disaster management has been widely enabled through utilizing spatial data sourcing and related technologies in the whole process of collection, access, and usage of disaster information. Currently, there are unique challenges that cannot be met without incorporating in situ sensing as an emerging technology for sourcing and managing disaster information. These include (1) high temporal and spatial resolution of information, (2) broad range of disaster data, and (3) automated operations. Incorporating in situ sensing into the disaster management process can potentially address such challenges by providing data that support all of these requirements. Following an examination of current concepts and methods for integrating multisourced sensors, a framework of the requirements for integrating in situ sensors for disaster management, is suggested. Based on this framework and its components, an evaluation of the methods is developed and applied. The results highlight that information integration of multisourced sensors is a major challenge and has not yet adequately addressed for sensor data enablement of disaster management.     

A new geospatial overlay method for the analysis and visualization of spatial change patterns using object-oriented data modeling concepts

Traditional geographic information system (GIS)-overlay routines usually build on relatively simple data models. Topology is – if at all – calculated on the fly for very specific tasks only. If, for example, a change comparison is conducted between two or more polygon layers, the result leads mostly to a complete and also very complex from–to class intersection. A lot of additional processing steps need to be performed to arrive at aggregated and meaningful results. To overcome this problem a new, automated geospatial overlay method in a topologically enabled (multi-scale) framework is presented. The implementation works with polygon and raster layers and uses a multi-scale vector/raster data model developed in the object-based image analysis software eCognition (Trimble Geospatial Imaging, Munich, Germany). Advantages are the use of the software inherent topological relationships in an object-by-object comparison, addressing some of the basic concepts of object-oriented data modeling such as classification, generalization, and aggregation. Results can easily be aggregated to a change-detection layer; change dependencies and the definition of different change classes are interactively possible through the use of a class hierarchy and its inheritance (parent–child class relationships). Implementation is exemplarily shown for a change comparison of CORINE Land Cover data sets. The result is a flexible and transferable solution which is – if parameterized once – fully automated.     

Fundamental aspects of access control for geospatial data

Abstract

In recent years, geographical information systems have been employed in a wide variety of application domains, and as a result many research efforts are being devoted to those upcoming problems. Geospatial data security, especially access control, has attracted increased research interests within the academic community. The tendency towards sharing and interoperability of geospatial data and applications makes it common to acquire and integrate geospatial data from multiple organisations to accomplish a complex task. Meanwhile, many organisations have the requirement for securing access to possessed sensitive or proprietary geospatial data. In this heterogeneous and distributed environment, consistent access control functionality is crucial to promote controlled accessibility. As an extension of general access control mechanisms in the IT domain, the mechanism for geospatial data access control has its own requirements and characteristics of granularity and geospatial logic. In this paper, we address several fundamental aspects concerning the design and implementation of an access control system for geospatial data, including the classification, requirements, authorisation models, storage structures and management approaches for authorisation rules, matching and decision-making algorithms between authorisation rules and access requests, and its policy enforcement mechanisms. This paper also presents a system framework for realising access control functionality for geospatial data, and explain access control procedures in detail.     

结合空间位置和语义匹配的多源房屋灾害数据融合

自然灾害综合风险普查工作中,房屋灾害信息数据来源众多,为调查底库快速建库带来很大挑战。本文针对多源房屋数据难以快速提取融合的问题,基于地理空间位置的信息匹配和基于地理空间语义的信息匹配等技术,通过空间数据提取、房屋建筑增补绘、属性信息匹配、属性信息选择,实现了房屋建筑多源信息快速自动融合,为自然灾害普查工作提供了可靠翔实的房屋建筑数据底板。实践证明,该技术成果数据准确可靠,可有效提升自然灾害风险普查工作效率,大量降低人工成本。     

基于多软件联合的地理市情监测报告制作研究

目前地理信息软件ArcGIS是测绘行业进行地理国情监测数据制作的首选,在实际应用中,ArcGIS具有很好的地理空间数据编辑优势,但在地图出版印制方面存在色彩和样式单一等不足,Illustrator软件具有强大的图形编辑处理功能和印前系统,但排版不如InDesign,本文以编制天津市地理市情监测报告为例,结合ArcGIS,Illus-trator,InDesign,AutoCAD,MicrosoftOfficeExcel等软件优势,说明一条从地理信息软件至印刷品之路,对同类专题地图册的制作具有一定的参考价值。     

玉树地震灾情SAR遥感监测与信息服务系统

在玉树地震中,中国首套自主知识产权的机载多波段多极化干涉SAR测图系统,发挥全天时主动遥感的优势,成功服务于抗震救灾中。依据玉树地震灾情综合地理信息监测与评估工作,着重探讨SAR遥感影像用于地震灾情监测与评估中的处理方法和技术路线,研究制定了地震灾区灾情综合地理信息监测指标,通过快速几何处理、快速变化信息提取、快速目标判读和灾害空间危险性评估,实现了玉树地震震区灾情综合地理信息的解译、制图和统计评估。在此基础上,开发了玉树地震灾情综合地理信息服务系统,实现了灾情监测信息的综合管理、可视化查询和统计分析。     

对地观测与抗震救灾

2008年5月12汶川地震灾害发生后,全国相关涉灾部门充分利用空间信息技术为汶川地震救灾提供科学有效的决策支持,在灾害应急响应中发挥了巨大的作用。本文主要从对地观测以及地震救灾的空间信息技术支持两个方面,分析了空间信息技术在救灾中的作用。为今后空间信息如何更好地服务于自然灾害救助,提出了中国空间信息技术发展的思路与建议。     

A Web GIS Application for Dams and Drought in India

Dams and diversion are built in India for meeting needs of water and energy. Due to variability of monsoon in space and time, precipitation falls short or exceeds causing in extreme cases drought and floods respectively. Water resource planners and engineers need information on dams and diversion. Drought information is needed in disaster management. For dissemination of these spatial data, Web GIS technology can be utilized, which is amalgamation of several information technologies. For Web GIS application, a high end, powerful and open source software, namely Mapserver is available. The software is CGI technology based. An application on dams and drought information for India is conceptualized using Mapserver. It is planned to write the application by modifying available tutorial. This will require writing DHTML pages, writing logic, using available libraries etc. Separate DHTML pages will be written for dam and drought applications. For dam application pages will be written for storage, hydropower and all dams. The drought application will provide maps of rainfall over districts for different SPI and time scales.     

基于Spark的分布式空间数据存储结构设计与实现

Apache Spark分布式计算框架可用于空间大数据的管理与计算,为实现云GIS提供基础平台。针对Apache Spark的数据组织与计算模型,结合Apache HBase分布式数据库,从分布式GIS内核的理念出发,设计并实现了分布式空间数据存储结构与对象接口,并基于某国产GIS平台软件内核进行了实现。针对点、线、面数据的存储与查询,与传统空间数据库系统PostGIS进行了一系列对比实验,验证了提出的分布式空间数据存储架构的可行性与高效性。     

Geospatial preparedness: Empirical study of the joint effort to provide geospatial support to disaster response

In a disaster aftermath in places lacking geospatial preparedness, the United Nations Office for the Coordination of Humanitarian Affairs creates a framework for cooperation with the Coordinated Data Scramble initiative, where Information Management Officers (IMOs) from different organizations work together in supporting the coordination of humanitarian aid. The perspective of these IMOs has been considered to identify the factors influencing the use of GIS in this context. The results show the requirement for a geodata management strategy, including geodata gathering, maintenance, and decision‐making processes based on those geodata. Geodata should be reliable and up‐to‐date. It requires consistent and useful metadata and the possibility of contacting the geodata source. Security and political issues limit information sharing. In this context, OpenStreetMap is often used as a source of information. Therefore, improving OpenStreetMap improves geospatial preparedness. Nevertheless, the use of this open platform highlights issues related to information privacy.