大数据时代地理信息获取与服务方式的嬗变

地理信息是国家基础信息资源,其获取方式与服务方式与相关学科技术的发展水平相适应。研究地理信息获取和服务方式的发展变化过程和互联网大数据时代地理信息获取和服务的新方式,为地理信息发展和服务提供有益的参考。大数据时代,用户使用地理信息的行为会成为地理信息服务依赖的重要数据,可以从中分析获取大至人类群体活动规律、小至用户行为习惯偏好等信息。此外,在这个阶段,大众不仅是地理信息服务的使用者,同时也是地理信息的采集者、提供者。     

A weighted multi-attribute method for matching user-generated Points of Interest

To a large degree, the attraction of Big Data lies in the variety of its heterogeneous multi-thematic and multi-dimensional data sources and not merely its volume. To fully exploit this variety, however, requires conflation. This is a two-step process. First, one has to establish identity relations between information entities across different data sources; and second, attribute values have to be merged according to certain procedures that avoid logical contradictions. The first step, also called matching, can be thought of as a weighted combination of common attributes according to some similarity measures. In this work, we propose such a matching based on multiple attributes of Points of Interest (POI) from the Location-based Social Network Foursquare and the local directory service Yelp. While both contain overlapping attributes that can be used for matching, they have specific strengths and weaknesses that make their conflation desirable. For instance, Foursquare offers information about user check-ins to places, while Yelp specializes in user-contributed reviews. We present a weighted multi-attribute matching strategy, evaluate its performance, and discuss application areas that benefit from a successful matching. Finally, we also outline how the established POI matches can be stored as Linked Data on the Semantic Web. Our strategy can automatically match 97% of randomly selected Yelp POI to their corresponding Foursquare entities.     

Data democracy – increased supply of geospatial information and expanded participatory processes in the production of data

The global landscape in the supply, co-creation and use of geospatial data is changing very rapidly with new satellites, sensors and mobile devices reconfiguring the traditional lines of demand and supply and the number of actors involved. In this paper we chart some of these technology-led developments and then focus on the opportunities they have created for the increased participation of the public in generating and contributing information for a wide range of uses, scientific and non. Not all this information is open or geospatial, but sufficiently large portions of it are to make it one of the most significant phenomena of the last decade. In fact, we argue that while satellite and sensors have exponentially increased the volumes of geospatial information available, the participation of the public is transformative because it expands the range of participants and stakeholders in society using and producing geospatial information, with opportunities for more direct participation in science, politics and social action.     

A New Algorithm for Continuous Area Cartogram Construction with Triangulation of Regions and Restriction on Bearing Changes of Edges

Collective intelligence is the idea that under the right circumstances collections of individuals are smarter than even the smartest individuals in the group, that is a group has an “intelligence” that is independent of the intelligence of its members. The ideology of collective intelligence undergirds much of the enthusiasm about the use of “volunteered” or crowd-sourced geographic information. Literature from a variety of fields makes clear that not all groups possess collective intelligence, this article identifies four pre-conditions for the emergence of collective intelligence and then examines the extent to which collectively generated mapping systems satisfy these conditions. However, the “intelligence” collectively generated maps is hard to assess because there are two difficult to reconcile perspectives on map quality – the credibility perspective and the accuracy perspective. Much of the current literature on user-generated maps focuses on assessing the quality of individual contributions. However, because user-generated maps are complex social systems and because the quality of a contribution is difficult to assess this strategy may not yield an “intelligent” end product. The existing literature on collective intelligence suggests that the structure of groups is more important than the intelligence of group members. Applying this idea to user-generated maps suggests that systems should be designed to foster conditions known to produce collective intelligence rather than privileging particular contributions/contributors. The article concludes with some design recommendations and by considering the implications of collectively generated maps for both expert knowledge and traditional state sponsored mapping programs.     

Geo-reCAPTCHA: Crowdsourcing large amounts of geographic information from earth observation data

The reCAPTCHA concept provides a large amount of valuable information for various applications. First, it provides security, e.g., for a form on a website, by means of a test that only a human could solve. Second, the effort of the user for this test is used to generate additional information, e.g., digitization of books or identification of house numbers. In this work, we present a concept for adapting the reCAPTCHA idea to create user-generated geographic information from earth observation data, and the requirements during the conception and implementation are depicted in detail. Furthermore, the essential parts of a Geo-reCAPTCHA system are described, and afterwards transferred, to a prototype implementation. An empirical user study is conducted to investigate the Geo-reCAPTCHA approach, assessing time and quality of the resulting geographic information. Our results show that a Geo-reCAPTCHA can be solved by the users of our study on building digitization in a short amount of time (19.2 s on average) with an overall average accuracy of the digitizations of 82.2%. In conclusion, Geo-reCAPTCHA has the potential to be a reasonable alternative to the typical reCAPTCHA, and to become a new data-rich channel of crowdsourced geographic information.     

Satellite image analysis using crowdsourcing data for collaborative mapping: current and opportunities

ABSTRACT

Researchers are continually finding new applications of satellite images because of the growing number of high-resolution images with wide spatial coverage. However, the cost of these images is sometimes high, and their temporal resolution is relatively coarse. Crowdsourcing is an increasingly common source of data that takes advantage of local stakeholder knowledge and that provides a higher frequency of data. The complementarity of these two data sources suggests there is great potential for mutually beneficial integration. Unfortunately, there are still important gaps in crowdsourced satellite image analysis by means of crowdsourcing in areas such as land cover classification and emergency management. In this paper, we summarize recent efforts, and discuss the challenges and prospects of satellite image analysis for geospatial applications using crowdsourcing. Crowdsourcing can be used to improve satellite image analysis and satellite images can be used to organize crowdsourced efforts for collaborative mapping.     

Finding meaningful participation in volunteer geographic information and citizen science: a case comparison in environmental application

ABSTRACT

Volunteer geographic information (VGI) and citizen science (CS) have been used as a way to promote a form of democratization of knowledge. Crowdsourcing facilitates the massive collection of data through nonexpert volunteers. This study compares 57 VGI and CS projects through a cross-case comparison method to explore the level of involvement of participants, based on three main analytic dimensions (project rationale, actor interaction, and data flow) and 12 sub-variables. The primary goal of this research is to analyze the purpose and the role of technology in VGI and CS projects, using three matrices to explore emerging trade-offs. Finally, we synthesized the workflow of VGI and CS project and compared based on project purposes. At the end of this study, five main purposes were found among the selected projects, uncovering that data collection is the most common purpose. A general workflow can be conceptualized, but detail implementation will involve various trade-offs, especially between local involvement and large-area expert-oriented protocol implementations. By exploring diverse relationships among selected variables of analysis in VGI and CS projects, this study pretends to build a foundation for larger, global meta-analysis that can bring some transparency in the epistemic interactions between experts and nonexperts.     

Assessing quality of volunteer crowdsourcing contributions: lessons from the Cropland Capture game

Volunteered geographic information (VGI) is the assembly of spatial information based on public input. While VGI has proliferated in recent years, assessing the quality of volunteer-contributed data has proven challenging, leading some to question the efficiency of such programs. In this paper, we compare several quality metrics for individual volunteers’ contributions. The data were the product of the ‘Cropland Capture’ game, in which several thousand volunteers assessed 165,000 images for the presence of cropland over the course of 6 months. We compared agreement between volunteer ratings and an image's majority classification with volunteer self-agreement on repeated images and expert evaluations. We also examined the impact of experience and learning on performance. Volunteer self-agreement was nearly always higher than agreement with majority classifications, and much greater than agreement with expert validations although these metrics were all positively correlated. Volunteer quality showed a broad trend toward improvement with experience, but the highest accuracies were achieved by a handful of moderately active contributors, not the most active volunteers. Our results emphasize the importance of a universal set of expert-validated tasks as a gold standard for evaluating VGI quality.     

将高精度地理信息获取作为基础测绘重要战略任务的思考

高精度地理信息具有提供更高空间定位精度和更强空间关系表达能力的优势."十四五"期间,高精度地理信息获取作为基础测绘重要战略任务,其相关成果将为经济社会发展和自然资源综合管理提供更好的空间参考依据.本文从高精度地理信息的获取进展出发,分析了高精度地理信息产品的需求形势和对基础测绘服务能力的提升作用,以及高精度地理信息获取...     

Monitoring the built-up environment of Shanghai on the street-block level using SAR and volunteered geographic information

ABSTRACT

In this geo-statistical analysis of change detection, we illustrate the evolution of the built-up environment in Shanghai at the street-block level. Based on two TerraSAR-X image stacks with 36 and 15 images, covering the city centre of Shanghai for the time period from 2008 to 2015, a set of coherence images was created using a small baseline approach. The road network from Open Street Map, a volunteered geographic information product, serves as the input dataset to create street-blocks. A street-block is surrounded by roads and resembles a ground parcel, a real estate property – a cadastral unit. The coherence information is aggregated to these street-blocks for each observation and the variation is analysed over time. An analysis of spatial autocorrelation reveals clusters of similar behaviours. The result is a detailed map of Shanghai highlighting areas of change. We argue that the aggregation and grouping of synthetic aperture radar coherence image information to real-world entities (street-blocks) is comprehensible and relevant to the urban planning process. Therefore, this research is a contribution to the community of urban planners, designers, and government agencies who want to monitor the development of the urban landscape.     

我国地理信息标准化政策研究

基于对发达国家标准化相关政策现状和特点分析,对国际组织和先进国家地理信息标准化现状、特点和趋势分析,以及对我国地理信息标准化政策现状与存在问题的分析,立足于认真执行国家发布的标准化相关法律法规和指导方针,提出我国地理信息标准化的基本政策是:强化地理信息标准研制与实施力度,促进地理信息资源共建共享,并据此提出了若干具体的政策建议。     

志愿者地理信息数据质量研究现状与趋势

针对志愿者地理信息的质量评价问题,对当前的研究现状和存在问题进行了较为全面的综述。有关志愿者地理信息数据质量分析与评估的研究也是该领域的研究热点,国内外学者从不同的角度进行了研究,依据是否使用参考数据分为基于参考数据的方法和基于数据分析的方法。总结了基于参考数据方法的基本流程,论述了两种评价方法中具有代表性的研究成果,分析了这些方法的特点和不足,最后指出了现有研究中存在的问题和进一步需要研究的方向。     

Improvement of a location-aware recommender system using volunteered geographic information

Abstract

Recommender systems (RS), as supportive tools, filter information from a massive amount of data based on the determined preferences. Most of the RS require information about the context of users such as their locations. In such cases, location-aware recommender systems (LARS) can be employed to suggest more personalized items to the users. The most current research projects on LARS focus on the development of algorithms, evaluation methods and applications. However, the role of up-to-date spatial databases in LARS is not a well-researched area. The up-to-date spatial information would potentially improve the accuracy of items which are recommended by LARS. Volunteered geographic information (VGI) could be a low-cost source of up-to-date spatial information for LARS. This article proposes an approach to enrich spatial databases of LARS by VGI. Since not all records of VGI are fitted for use in LARS, a mechanism is developed to identify useful information. Some VGI data sets refer to existing spatial data in the database while other VGI data sets are shared for the first time. Therefore, the proposed method assessed the quality of VGI with reference source (for VGI which is existed in the database) and VGI without reference source (for VGI which is shared for the first time). To demonstrate the feasibility of the proposed approach, a mobile application has been developed to recommend suitable restaurants to the users based on their geospatial locations. The evaluation of the method indicates that VGI can potentially enhance the functionality of the LARS in predicting the users’ interests.     

浅论自发地理信息的数据管理

自发地理信息（volunteered geographic information,VGI）由大众志愿者自发标报,导致其可信度具有诸多不确定性,但目前的研究工作很少考虑用户信誉对于VGI质量的影响,因此提出基于用户信誉的VGI可信度计算模型。首先提出了VGI的用户信誉模型,模型综合考虑了用户的初始信誉和评价信誉两方面,在此基础上综合地理要素的编辑过程和贡献者的信誉等因素发展了地理对象的可信度计算模型。最后采用OpenStreetMap的真实历史数据中的线对象进行实验,实验结果表明,线要素的质量和可信度值呈正相关关系。本文从可信度的角度来评价自发地理信息,为VGI的质量评价和筛选提供了新的视角。     

Digital Earth from vision to practice: making sense of citizen-generated content

Abstract

The vision of Digital Earth (DE) put recently forward under the auspices of the International Society for DE extends the paradigm of spatial data infrastructures by advocating an interactive and dynamic framework based on near-to-real time information from sensors and citizens. This paper contributes to developing that vision and reports the results of a two-year research project exploring the extent to which it is possible to extract information useful for policy and science from the large volumes of messages and photos being posted daily through social networks. Given the noted concerns about the quality of such data in relation to that provided by authoritative sources, the research has developed a semi-automatic workflow to assess the fitness for purpose of data extracted from Twitter and Flickr, and compared them to that coming from official sources, using forest fires as a case study. The findings indicate that we were able to detect accurately six of eight major fires in France in the summer of 2011, with another four detected by the social networks but not reported by our official source, the European Forest Fire Information Service. These findings and the lessons learned in handling the very large volumes of unstructured data in multiple languages discussed in this study provide useful insights into the value of social network data for policy and science, and contribute to advancing the vision of DE.     

论地图数据库合并技术

本文探讨了地图数据库合并技术的研究范畴、研究内容、一般数据处理流程以及与其他已有技术的关 系等一些基本问题,并给出了一个简单应用实例。这些问题的研究丰富和完善了地图数据库合并技术的基本理论 体系,对建立地图数据库合并的主要技术框架有着重要的意义。     

兼顾志愿者地理信息的国家应急测绘公众服务平台设计

随着互联网技术的进步和新一代网络信息传播模式的深入发展,志愿者地理信息的研究和应用日益广泛,但由于其规范性和均一性方面的缺陷,在应急公共服务领域,志愿者信息的有效利用依旧是亟需突破的难题。本文将重点介绍国家应急测绘公众服务平台设计思路和总体架构,并结合志愿者地理信息特点,探讨该类信息在国家应急测绘公众服务平台建设中的处理流程和应用模式,力求在应急信息资源共享和服务平台共建方面进行新的尝试,为我国突发事件应急体系建设提供有益实践。     

Crowdsourcing The National Map

Using crowdsourcing techniques, the US Geological Survey’s (USGS) Volunteered Geographic Information (VGI) project known as “The National Map Corps (TNMCorps)” encourages citizen scientists to collect and edit data about man-made structures in an effort to provide accurate and authoritative map data for the USGS National Geospatial Program’s web-based The National Map. VGI is not new to the USGS, but past efforts have been hampered by available technologies. Building on lessons learned, TNMCorps volunteers are successfully editing 10 different structure types in all 50 states as well as Puerto Rico and the US Virgin Islands.     

Change of geographic information service model in mobile context

IntroductionGreat progress of scientific and technologicalcivilization dramatically i mproves the interactivemethods between people and world. At the sameti me various intelligent mobile terminals spreadInternet over anywhere in human’s life . Mobilecomputing and mobility of computational toolswill reform traditional geographic informationservice model ,combine seamlessly people ,real-ity and digital world through networks each oth-er ,achieve interoperability without li mitation ofti me and …     

电子政务中地理信息服务现状及未来发展

地理信息服务主要包括地理信息资源建设和技术支持,本文阐述了地理信息及其相关技术在电子政务中的作用以及它们之间的关系,对当前电子政务建设中地理信息资源建设和应用服务的现状与存在的主要问题进行了探讨,并提出了促进电子政务中地理信息应用与服务的具体建议。