数字地球网格计算雏议

数字地球将为人类提供关于我们地球的海量自然和人文数据与信息 ,是我们生活的行星的一个多分辨率 ,四维虚拟表达。网格计算被认为是解决数字地球问题的最好方法。数字地球问题的解决必须通过异构的计算资源 ,信息系统 ,设备 ,人之间的相互协作 ,而这些都是地理位置或组织结构分散的。本文介绍我们在生成用于解决数字地球问题的核心中间件的研究工作以及结果。因为网格计算本身是一门比较新的领域 ,网格计算与数字地球的有机结合将为数字地球提供一个全新的计算工具     

Service-oriented infrastructure for flood mapping using optical and SAR satellite data

In this paper, we present the service-oriented infrastructure within the Wide Area Grid project that was carried out within the Working Group on Information Systems and Services of the Committee on Earth Observation Satellites. The developed infrastructure integrates services and computational resources of several regional and national Grid systems: Ukrainian Academician Grid (with satellite data processing Grid segment, UASpaceGrid) and Grid system at the Center on Earth Observation and Digital Earth of Chinese Academy of Sciences. The study focuses on integrating geo-information services on flood mapping provided by Ukrainian and Chinese entities to benefit from information acquired from multiple sources. We also describe services for workflow automation and management in Grid environment and provide an example of workflow automation for generating flood maps from optical and synthetic-aperture radar satellite imagery. We also discuss issues of enabling trust for the infrastructure using certificates and reputation-based model. Applications of utilizing the developed infrastructure for operational flood mapping in Ukraine and China are given as well.     

Redefining the possibility of digital Earth and geosciences with spatial cloud computing

Abstract

Global challenges (such as economy and natural hazards) and technology advancements have triggered international leaders and organizations to rethink geosciences and Digital Earth in the new decade. The next generation visions pose grand challenges for infrastructure, especially computing infrastructure. The gradual establishment of cloud computing as a primary infrastructure provides new capabilities to meet the challenges. This paper reviews research conducted using cloud computing to address geoscience and Digital Earth needs within the context of an integrated Earth system. We also introduce the five papers selected through a rigorous review process as exemplar research in using cloud capabilities to address the challenges. The literature and research demonstrate that spatial cloud computing provides unprecedented new capabilities to enable Digital Earth and geosciences in the twenty-first century in several aspects: (1) virtually unlimited computing power for addressing big data storage, sharing, processing, and knowledge discovering challenges, (2) elastic, flexible, and easy-to-use computing infrastructure to facilitate the building of the next generation geospatial cyberinfrastructure, CyberGIS, CloudGIS, and Digital Earth, (3) seamless integration environment that enables mashing up observation, data, models, problems, and citizens, (4) research opportunities triggered by global challenges that may lead to breakthroughs in relevant fields including infrastructure building, GIScience, computer science, and geosciences, and (5) collaboration supported by cloud computing and across science domains, agencies, countries to collectively address global challenges from policy, management, system engineering, acquisition, and operation aspects.     

A high-level architecture for a Geomatics Informatization Technology System: the Chinese case

Abstract

China will, as a component of ‘Digital Earth,’ establish a Geomatics Informatization Technology System (GITS) which is characterized by real-time acquisition, automatic processing, networking service, and socialized application with fundamental geographical information. The basic composition of GITS is proposed. GITS covers four layers and six platforms. The four layers are data acquisition, processing, management, and application and services. The six platforms are informatic geodetic datum, high-precision geo-spatial data acquisition, automatic geo-spatial data processing, grid-based geo-spatial information management, comprehensive geo-spatial information sharing and service, and geo-spatial information integration and application. The informatic geodetic datum platform provides a carrier for all the four layers and a base for the other five platforms. The high-precision geo-spatial data acquisition platform belongs to the acquisition layer. The automatic geo-spatial data processing platform belongs to the processing layer. The grid-based geo-spatial information management platform belongs to the management layer and is a bridge connecting geo-spatial data acquisition and spatial information sharing service and integrated applications. The comprehensive geo-spatial information sharing and service platform belongs to the application and service layer. Finally, this paper presents thoughts for constructing GITS.     

GeoCube： 面向大规模分析的多源对地观测时空立方体

随着对地立体观测体系的建立,遥感大数据不断累积。传统基于文件、景/幅式的影像组织方式,时空基准不够统一,集中式存储不利于大规模并行分析。对地观测大数据分析仍缺乏一套统一的数据模型与基础设施理论。近年来,数据立方体的研究为对地观测领域大数据分析基础设施提供了前景。基于统一的分析就绪型多维数据模型和集成对地观测数据分析功能,可构建一个基于数据立方的对地观测大数据分析基础设施。因此,本文提出了一个面向大规模分析的多源对地观测时空立方体,相较于现有的数据立方体方法,强调多源数据的统一组织、基于云计算的立方体处理模式以及基于人工智能优化的立方体计算。研究有助于构建时空大数据分析的新框架,同时建立与商业智能领域的数据立方体关联,为时空大数据建立统一的时空组织模型,支持大范围、长时序的快速大规模对地观测数据分析。本文在性能上与开源数据立方做了对比,结果证明提出的多源对地观测时空立方体在处理性能上具有明显优势。     

Progress and challenges in the architecture and service pattern of Earth Observation Sensor Web for Digital Earth

The Earth Observation (EO) Web is the data acquisition and processing network for digital Earth. The EO Web including Data Web and Sensor Web has become one of the most important aspects of the Digital Earth 2020. This paper summarised the history of the development and status quo of the major types of EO data web service systems, including architecture, service pattern and standards. The concepts, development and implementation of the EO Sensor Web were reviewed. Furthermore, we analysed the requirements on the architecture of the next-generation EO Sensor Web system, namely Spaceborne-Airborne-Ground integrated Intelligent EO Sensor Web system, and highlighted the virtualization, intelligent, pervasive and active development tendency of such system.     

A scalable cyberinfrastructure and cloud computing platform for forest aboveground biomass estimation based on the Google Earth Engine

ABSTRACT

Earth observation (EO) data, such as high-resolution satellite imagery or LiDAR, has become one primary source for forests Aboveground Biomass (AGB) mapping and estimation. However, managing and analyzing the large amount of globally or locally available EO data remains a great challenge. The Google Earth Engine (GEE), which leverages cloud-computing services to provide powerful capabilities on the management and rapid analysis of various types of EO data, has appeared as an inestimable tool to address this challenge. In this paper, we present a scalable cyberinfrastructure for on-the-fly AGB estimation, statistics, and visualization over a large spatial extent. This cyberinfrastructure integrates state-of-the-art cloud computing applications, including GEE, Fusion Tables, and the Google Cloud Platform (GCP), to establish a scalable, highly extendable, and high-performance analysis environment. Two experiments were designed to demonstrate its superiority in performance over the traditional desktop environment and its scalability in processing complex workflows. In addition, a web portal was developed to integrate the cyberinfrastructure with some visualization tools (e.g. Google Maps, Highcharts) to provide a Graphical User Interfaces (GUI) and online visualization for both general public and geospatial researchers.     

网格在地理信息系统中的应用

当前GIS技术的发展遇到了一些技术瓶颈,如各种异构数据难以兼容、共享导致无法充分表达和利用空间数据,特别是当数字地球概念提出以后,现有的计算机技术无法完成对整个地球空间信息这么庞大的海量数据的处理。WebGIS随着Internet技术的成熟而出现,它试图解决一部分空间数据共享问题,但是由于网络基础体系结构的限制,WebGIS不可能突破上述的技术瓶颈。直到网格的出现,才为从本质上解决空间数据利用及共享问题提供了契机,网格技术也成为解决数字地球问题的最佳途径。     

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.     

Distributed geospatial information processing: sharing distributed geospatial resources to support Digital Earth

Abstract

This paper introduces a new concept, distributed geospatial information processing (DGIP), which refers to the process of geospatial information residing on computers geographically dispersed and connected through computer networks, and the contribution of DGIP to Digital Earth (DE). The DGIP plays a critical role in integrating the widely distributed geospatial resources to support the DE envisioned to utilise a wide variety of information. This paper addresses this role from three different aspects: 1) sharing Earth data, information, and services through geospatial interoperability supported by standardisation of contents and interfaces; 2) sharing computing and software resources through a GeoCyberinfrastructure supported by DGIP middleware; and 3) sharing knowledge within and across domains through ontology and semantic searches. Observing the long-term process for the research and development of an operational DE, we discuss and expect some practical contributions of the DGIP to the DE.     

Enabling Digital Earth simulation models using cloud computing or grid computing – two approaches supporting high-performance GIS simulation frameworks

Abstract

Geospatial simulation models can help us understand the dynamic aspects of Digital Earth. To implement high-performance simulation models for complex geospatial problems, grid computing and cloud computing are two promising computational frameworks. This research compares the benefits and drawbacks of both in Web-based frameworks by testing a parallel Geographic Information System (GIS) simulation model (Schelling's residential segregation model). The parallel GIS simulation model was tested on XSEDE (a representative grid computing platform) and Amazon EC2 (a representative cloud computing platform). The test results demonstrate that cloud computing platforms can provide almost the same parallel computing capability as high-end grid computing frameworks. However, cloud computing resources are more accessible to individual scientists, easier to request and set up, and have more scalable software architecture for on-demand and dedicated Web services. These advantages may attract more geospatial scientists to utilize cloud computing for the development of Digital Earth simulation models in the future.     

SIG中的元数据共享服务体系研究与实践

元数据是数字地球建设的关键技术之一，是建设信息化城市和实施空间信息网格基础设施的重要内容。本文基于Web服务对象及其标准，建立了分布、异构的网格环境下的元数据服务管理模型，包括基于Web服务的空间元数据共享服务体系、空间元数据服务与发布流程及其实现。最后，探讨了如何使用目前JAVA技术中比较流行的JDBC和懒加载技术开发空间元数据服务管理模型。     

Free and open source software for geospatial applications (FOSS4G) to support Future Earth

ABSTRACT

The development, integration, and distribution of the information and spatial data infrastructure (i.e. Digital Earth; DE) necessary to support the vision and goals of Future Earth (FE) will occur in a distributed fashion, in very diverse technological, institutional, socio-cultural, and economic contexts around the world. This complex context and ambitious goals require bringing to bear not only the best minds, but also the best science and technologies available. Free and Open Source Software for Geospatial Applications (FOSS4G) offers mature, capable and reliable software to contribute to the creation of this infrastructure. In this paper we point to a selected set of some of the most mature and reliable FOSS4G solutions that can be used to develop the functionality required as part of DE and FE. We provide examples of large-scale, sophisticated, mission-critical applications of each software to illustrate their power and capabilities in systems where they perform roles or functionality similar to the ones they could perform as part of DE and FE. We provide information and resources to assist the readers in carrying out their own assessments to select the best FOSS4G solutions for their particular contexts and system development needs.     

Building geospatial infrastructure

ABSTRACT

Many visions for geospatial technology have been advanced over the past half century. Initially researchers saw the handling of geospatial data as the major problem to be overcome. The vision of geographic information systems arose as an early international consensus. Later visions included spatial data infrastructure, Digital Earth, and a nervous system for the planet. With accelerating advances in information technology, a new vision is needed that reflects today’s focus on open and multimodal access, sharing, engagement, the Web, Big Data, artificial intelligence, and data science. We elaborate on the concept of geospatial infrastructure, and argue that it is essential if geospatial technology is to contribute to the solution of problems facing humanity.     

空间信息网格中远程空间连接查询的优化

随着空间信息网格的建设,网格平台上管理的空间信息资源越来越丰富,这促进了空间信息网格中空间数据分布式查询的应用需求,而在分布式空间查询中,空间连接查询操作往往成为性能的瓶颈.根据空间信息的特点,通过利用网格计算资源来优化空间连接查询的执行.首先基于网格服务构建网格平台分布式空间数据查询软件结构,通过设计远程空间连接执行服务利用网格平台中的计算资源;根据空间信息的特点.采用基于Kd-Tree空间分区并行连接的方法提高远程空间数据连接操作执行效率,并给出了远程空间连接执行的查询代价模型;然后根据连接代价模型设计了远程空间连接查询执行计划优化生成算法;最后总结了本文工作并探讨了下一步研究方向.     

An open-source web service for creating quadrilateral grids based on the rHEALPix Discrete Global Grid System

ABSTRACT

The foundation of modern Digital Earth frameworks is the Discrete Global Grid System (DGGS). To standardize the DGGS model, the Open Geospatial Consortium (OGC) recently created the DGGS Abstract Specification, which also aims to increase usability and interoperability between DGGSs. To support these demands and aid future research, open implementations are necessary. However, several OGC conformant DGGSs are not available for researchers to use. This has motivated us to develop an open-source web service that allows users to create quadrilateral grids based on the rHEALPix DGGS. In this paper, we describe the implementation of the web service, including issues and limitations, and demonstrate how discrete global grids and regional grids can be created. Lastly, we present examples that show how vector data sets can be modeled and integrated at different levels of resolution – a key benefit of the DGGS model.     

Adopting cloud computing to optimize spatial web portals for better performance to support Digital Earth and other global geospatial initiatives

A spatial web portal (SWP) provides a web-based gateway to discover, access, manage, and integrate worldwide geospatial resources through the Internet and has the access characteristics of regional to global interest and spiking. Although various technologies have been adopted to improve SWP performance, enabling high-speed resource access for global users to better support Digital Earth remains challenging because of the computing and communication intensities in the SWP operation and the dynamic distribution of end users. This paper proposes a cloud-enabled framework for high-speed SWP access by leveraging elastic resource pooling, dynamic workload balancing, and global deployment. Experimental results demonstrate that the new SWP framework outperforms the traditional computing infrastructure and better supports users of a global system such as Digital Earth. Reported methodologies and framework can be adopted to support operational geospatial systems, such as monitoring national geographic state and spanning across regional and global geographic extent.     

基于网络GIS技术的时空典藏整合环境构建

时空信息是所有内涵数据都具备的基本特性,通过时空信息处理技术建构时空坐标体系,让所有数字典藏的内容得以整合,通过网络开放式交换机制,让原本储存在不同机构的信息,既可以分散储存,又可以彼此引用套合,促成信息统整。本文探讨了利用互联网地理信息系统建构数字典藏计划的时空内涵基础架构,其最主要目的在于扩充原有地理信息系统内涵,发展成时间及空间信息处理技术,建构起时空内涵基础架构,以精确的时空参考系统为基础,建立所有典藏内涵的时间与地理空间标记(geographic footprint),做为信息检索和信息整合的主要依据,并以空间可视化(Spatial Visualization)方式提供更生动、易读的、精准的事件原貌。     

Semantic and syntactic interoperability in online processing of big Earth observation data

ABSTRACT

The challenge of enabling syntactic and semantic interoperability for comprehensive and reproducible online processing of big Earth observation (EO) data is still unsolved. Supporting both types of interoperability is one of the requirements to efficiently extract valuable information from the large amount of available multi-temporal gridded data sets. The proposed system wraps world models, (semantic interoperability) into OGC Web Processing Services (syntactic interoperability) for semantic online analyses. World models describe spatio-temporal entities and their relationships in a formal way. The proposed system serves as enabler for (1) technical interoperability using a standardised interface to be used by all types of clients and (2) allowing experts from different domains to develop complex analyses together as collaborative effort. Users are connecting the world models online to the data, which are maintained in a centralised storage as 3D spatio-temporal data cubes. It allows also non-experts to extract valuable information from EO data because data management, low-level interactions or specific software issues can be ignored. We discuss the concept of the proposed system, provide a technical implementation example and describe three use cases for extracting changes from EO images and demonstrate the usability also for non-EO, gridded, multi-temporal data sets (CORINE land cover).     

西南资源环境空间信息网格研究

在空间信息科学领域,人们提出了空间信息网格(SIG)的概念,为空间数据的信息获取、共享、访问、分析和处理提供技术支持,以实现网格环境下的空间资源共享与协同。本文着重于网格技术与移动代理技术在地理信息共享领域的应用研究,结合空间信息网格技术,探讨了区域资源环境信息共享技术。在此基础上,本文设计了基于网格的地理信息共享与服务体系框架,并初步实现了基于该框架的西南地区资源环境信息共享与服务平台的原型系统。在原型系统中实现了网格环境下的WMS服务、WFS服务、服务资源注册服务、服务状态监测服务以及安全方面的访问控制服务。