A geospatial search engine for discovering multi-format geospatial data across the web

The volume of publically available geospatial data on the web is rapidly increasing due to advances in server-based technologies and the ease at which data can now be created. However, challenges remain with connecting individuals searching for geospatial data with servers and websites where such data exist. The objective of this paper is to present a publically available Geospatial Search Engine (GSE) that utilizes a web crawler built on top of the Google search engine in order to search the web for geospatial data. The crawler seeding mechanism combines search terms entered by users with predefined keywords that identify geospatial data services. A procedure runs daily to update map server layers and metadata, and to eliminate servers that go offline. The GSE supports Web Map Services, ArcGIS services, and websites that have geospatial data for download. We applied the GSE to search for all available geospatial services under these formats and provide search results including the spatial distribution of all obtained services. While enhancements to our GSE and to web crawler technology in general lie ahead, our work represents an important step toward realizing the potential of a publically accessible tool for discovering the global availability of geospatial data.     

Geospatial web services pave new ways for server-based on-demand access and processing of Big Earth Data

ABSTRACT

Big Earth Data has experienced a considerable increase in volume in recent years due to improved sensing technologies and improvement of numerical-weather prediction models. The traditional geospatial data analysis workflow hinders the use of large volumes of geospatial data due to limited disc space and computing capacity. Geospatial web service technologies bring new opportunities to access large volumes of Big Earth Data via the Internet and to process them at server-side. Four practical examples are presented from the marine, climate, planetary and earth observation science communities to show how the standard interface Web Coverage Service and its processing extension can be integrated into the traditional geospatial data workflow. Web service technologies offer a time- and cost-effective way to access multi-dimensional data in a user-tailored format and allow for rapid application development or time-series extraction. Data transport is minimised and enhanced processing capabilities are offered. More research is required to investigate web service implementations in an operational mode and large data centres have to become more progressive towards the adoption of geo-data standard interfaces. At the same time, data users have to become aware of the advantages of web services and be trained how to benefit from them most.     

基于多协议的地理信息服务集成

设计了多协议地理信息服务集成框架,探讨解决了其中的关键问题,实现了从不同地理信息服务获取的影像数据、矢量数据和DEM数据的无缝集成。     

The Roles of Web Feature and Web Map Services in Real-time Geospatial Data Sharing for Time-critical Applications

Many time-critical applications such as emergency response, location-based services, and real time traffic management need instant access to diverse data to make quick decisions and take instantaneous actions. However, two issues block time-critical applications to quickly acquire and integrate spatial data over the web: (1) the heterogeneity of existing GIS systems, and (2) the file-level data sharing systems over the web. This research examines current open standards, protocols, and technologies capable of solving the two issues for real-time spatial data sharing over the web. Focusing on investigating the role of Web Feature Services (WFS) and Web Map Services (WMS), this research has developed a solution for real-time geospatial data sharing at the feature level over the web. A prototype has been implemented to query, extract, create, delete, update, and map geographic features stored in web-accessible OGC (Open Geospatial Consortium) simple feature datastores for transportation emergency applications. The prototype results show that the OGC WFS and WMS play important roles in real-time geospatial data sharing and exchange from heterogeneous sources at the feature level for time-critical applications. The WFS and WMS eliminate time-consuming data translation and facilitate reuse of existing geospatial data over the web. Several issues related to the solution are also discussed in the paper.     

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.     

Putting meaning into NETMAR – the open service network for marine environmental data

The open service network for marine environmental data (NETMAR) project uses semantic web technologies in its pilot system which aims to allow users to search, download and integrate satellite, in situ and model data from open ocean and coastal areas. The semantic web is an extension of the fundamental ideas of the World Wide Web, building a web of data through annotation of metadata and data with hyperlinked resources. Within the framework of the NETMAR project, an interconnected semantic web resource was developed to aid in data and web service discovery and to validate Open Geospatial Consortium Web Processing Service orchestration. A second semantic resource was developed to support interoperability of coastal web atlases across jurisdictional boundaries. This paper outlines the approach taken to producing the resource registry used within the NETMAR project and demonstrates the use of these semantic resources to support user interactions with systems. Such interconnected semantic resources allow the increased ability to share and disseminate data through the facilitation of interoperability between data providers. The formal representation of geospatial knowledge to advance geospatial interoperability is a growing research area. Tools and methods such as those outlined in this paper have the potential to support these efforts.     

Building the World Wide Hypermap (WWH) with a RESTful architecture

The hypermap concept was introduced in 1992 as a way to hyperlink geospatial features to text, multimedia or other geospatial features. Since then, the concept has been used in several applications, although it has been found to have some limitations. On the other hand, Spatial Data Infrastructures (SDIs) adopt diverse and heterogeneous service oriented architectures (SOAs). They are developed by different standard bodies and are generally disconnected from mass market web solutions. This work expands the hypermap concept to overcome its limitations and harmonise it with geospatial resource oriented architecture (ROA), connecting it to the semantic web and generalising it to the World Wide Hypermap (WWH) as a tool for building a single ‘Digital Earth’. Global identifiers, dynamic links, link purposes and resource management capabilities are introduced as a solution that orchestrates data, metadata and data access services in a homogeneous way. This is achieved by providing a set of rules using the current Internet paradigm formalised in the REpresentational State Transfer (REST) architecture and combining it with existing Open Geospatial Consortium (OGC) and International Organization for Standardization (ISO) standards. A reference implementation is also presented and the strategies needed to implement the WWH, which mainly consist in a set of additions to current Geographic Information System (GIS) products and a RESTful server that mediates between the Internet and the local GIS applications.     

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.     

基于Web Service和Mashup的城市地理信息共享

提出了一个基于Web Service的城市地理空间数据服务技术框架,并讨论采用Mashup技术,实现数据共享和应用开发。案例研究验证了城市地理数据服务框架的可行性,表明Web Service和Mashup技术在数字城市中具有巨大的应用潜力。     

An automated and optimized approach for online spatial biodiversity model: a case study of OGC web processing service

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.     

基于云计算的三维地理空间信息服务的表达

当前云计算的发展已能支持高性能的地理空间服务,比如在数字城市和电子商务等行业。Apache基金支持下的开源软件框架Hadoop,可以用来构建一个云环境的集群用来存储和处理高性能的地理空间数据。开放地理空间联盟(OGC)的Web三维服务(W3DS)就是这样一个很好的三维的地理空间数据服务标准。在标准的云计算环境下将是一个更好的应用示范。基于此,本文研究了OGC的W3DS服务在云计算环境下的实验结果。实验采用Apache的Hadoop框架作为三维地理空间信息服务实验展示的基础。实验结果对展示高性能的三维地理空间信息提供了有价值的参考。     

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。     

Asynchronous Geospatial Processing: An Event‐Driven Push‐Based Architecture for the OGC Web Processing Service

Geospatial processing tasks like solar potential analyses or floodplain investigations within flood scenarios are often complex and deal with large amounts of data. If such analysis operations are performed in distributed web‐based systems, technical capabilities are mostly not sufficient. Major shortcomings comprise the potentially long execution times and the vast amount of messaging overhead that arise from common poll‐based approaches. To overcome these issues, an approach for an event‐driven architecture for web‐based geospatial processing is proposed within this article. First, this article presents a thorough qualitative discussion of different available technologies for push‐based notifications. The aim of this discussion is to find the most suitable push‐based messaging technologies for application with OGC Web Processing Services (WPS). Based on this, an event‐driven architecture for asynchronous geospatial processing with the WPS is presented, building on the Web Socket Protocol as the transport protocol and the OGC Event Service as the message‐oriented middleware. The proposed architecture allows pushing notifications to clients once a task has completed. This paradigm enables the efficient execution of web‐based geospatial processing tasks as well as the integration of geographical analyses into event‐driven real‐time workflows.     

A Rule-Based Strategy for the Semantic Annotation of Geodata

The ability to represent geospatial semantics is of great importance when building geospatial applications for the Web. This ability will enhance discovery, retrieval and translation of geographic information as well as the reuse of geographic information in different contexts. The problem of generating semantic annotations has been recognized as one of the most serious obstacles for realizing the Geospatial Semantic Web vision. We present a rule‐based strategy for the semantic annotation of geodata that combines Semantic Web and Geospatial Web Services technology. In our approach, rules are employed to partially automate the annotation process. Rules define conditions for identifying geospatial concepts. Based on these rules, spatial analysis procedures are implemented that allow for inferring whether or not a feature in a dataset represents an instance of a geospatial concept. This automated evaluation of features in the dataset generates valuable information for the creation and refinement of semantic annotations on the concept level. The approach is illustrated by a case study on annotating data sources containing representations of lowlands. The presented strategy lays the foundations for the specification of a semantic annotation tool for geospatial web services that supports data providers in annotating their sources according to multiple domain views.     

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。     

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.     

空间服务语义模式的地理信息服务发现

如何从大规模地理信息服务集合中快速且准确地发现目标服务是地理信息服务应用中的一个关键问题。当前基于关键字的服务发现方式缺乏语义支持,搜索效率低。本文在WSMO/WSML框架下,提出了一种基于空间服务语义模式的服务发现方法,将地理信息从语法模式转换为语义模式,明确表达空间数据中隐含的知识,有效克服数据源之间的语义异构。该方法能够显著提高地理信息服务发现的查全率和查准率。     

Terra Populus’ architecture for integrated big geospatial services

Big geospatial data is an emerging sub‐area of geographic information science, big data, and cyberinfrastructure. Big geospatial data poses two unique challenges. First, raster and vector data structures and analyses have developed on largely separate paths for the last 20 years. This is creating an impediment to geospatial researchers seeking to utilize big data platforms that do not promote heterogeneous data types. Second, big spatial data repositories have yet to be integrated with big data computation platforms in ways that allow researchers to spatio‐temporally analyze big geospatial datasets. IPUMS‐Terra, a National Science Foundation cyberInfrastructure project, addresses these challenges by providing a unified framework of integrated geospatial services which access, analyze, and transform big heterogeneous spatio‐temporal data. As IPUMS‐Terra's data volume grows, we seek to integrate geospatial platforms that will scale geospatial analyses and address current bottlenecks within our system. However, our work shows that there are still unresolved challenges for big geospatial analysis. The most pertinent is that there is a lack of a unified framework for conducting scalable integrated vector and raster data analysis. We conducted a comparative analysis between PostgreSQL with PostGIS and SciDB and concluded that SciDB is the superior platform for scalable raster zonal analyses.     

面向NSDI遥感影象数据库共享的元数据库和数据交换中心技术探讨

数据发现是数据共享的前提,本文根据NSDI空间数据共享的要求,针对多源遥感影像数据网络发现所面对的技术问题,结合国际国内最新的影像、栅格等地理数据交换标准,为了将原有的遥感影像数据库加入NSDI影像库,进行了具有普遍适用性的遥感影像元数据库内容设计、分级结构模型设计,并基于目前数据交换技术的发展状况,论述了将传统的、孤立的、多源的海量遥感影像数据库加入NSDI遥感影像库,实现快速数据检索的便捷途径和系统体系框架。