欧洲众源地理信息手册

地理信息系统

GIS

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"《欧洲众源地理信息手册》是一部关于众包地理信息的英文版专业书籍，由Cristina Capineri, Muki Haklay, Haosheng Huang, Vyron Antoniou, Juhani Kettunen, Frank Ostermann和Ross Purves等人编辑。本书深入探讨了大数据时代下的众源数据、地理信息系统（GIS）以及众包在地理信息领域的应用和挑战。" 《欧洲众源地理信息手册》是研究和理解众包地理信息的重要参考资料，它涵盖了从理论到实践的广泛内容，旨在促进对这一新兴领域的理解和应用。书中的内容可能包括以下几个核心知识点： 1. **众源数据**：书中可能会详细解释众源数据的概念，即通过网络平台收集的由公众贡献的数据，这些数据在地理空间信息领域具有广泛的应用，如地图更新、灾害响应和社区规划。 2. **大数据**：众源数据属于大数据的一个分支，书中可能讨论了如何处理和分析大规模的众源地理信息，包括数据挖掘、清洗、整合和可视化技术。 3. **地理信息系统 (GIS)**：GIS是处理和分析地理信息的关键工具，书中可能介绍了如何利用GIS技术处理众源数据，创建交互式地图，进行空间分析，并解决实际问题。 4. **众包**：众包在地理信息领域的应用是本书的重点，可能会探讨众包的模式、激励机制、参与者的角色、以及如何确保数据质量和可靠性。 5. **数据质量与验证**：由于众源数据的来源多样性和不确定性，书中可能会涉及数据质量评估、错误检测和纠正策略，以及建立信任度模型的方法。 6. **法律与伦理问题**：众包地理信息可能涉及隐私权、知识产权和责任归属等法律问题，书中可能会讨论这些议题，以及如何制定合适的政策和指导原则。 7. **案例研究**：为了加深理解，书中可能包含多个实际案例，如OpenStreetMap等项目，展示众包地理信息如何应用于应急响应、城市规划和社会科学研究。 8. **未来趋势**：作者们可能会展望众包地理信息的未来发展趋势，包括与物联网(IoT)、人工智能(AI)和区块链等新技术的结合，以及在智能城市、可持续发展等领域的新应用。这本书不仅适合地理信息科学的专业人士，也适合对大数据、众包和GIS感兴趣的学者、学生和政策制定者，它提供了对众源地理信息的全面理解和实践指导。

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Introduction 5

(Chapter 7) provides an overview of the semantic issues experienced in VGI

and what potential solutions are emerging from research in geo-semantics and

in the Semantic Web. Antoniou et al. (Chapter 8) present how named features

in Open Street Map behave and change in terms of type, name and location by

analysing the volatility of places and points-of-interest (POIs). Ali (Chapter 9)

presents an approach for rule-guided classication for VGI projects which con-

sists in a learning and a guiding phase. Finally, Bucher et al. (Chapter 10) pre-

sent ndings from the literature and from the experience of the French National

Mapping Agency, IGN, about quality management of geographical data and

focus on the potential of context and tasks modelling to address quality issues

PART III: Data analytics

Part III focuses on data analytics and visualization methods for deriving

knowledge from varying VGI sources such as Twitter, Flickr and OpenStreet-

Map. Purves and Mackaness (Chapter 11) provide an overview of methodolo-

gies used to extract meaning from the analysis of geotagged images based on

research in natural language processing and statistical and exploratory tech-

niques. Gennady and Natalia Andrienko (Chhapter 12) oer an analysis of geo-

graphically referenced posts published in social media, such as Twitter, Flickr

and YouTube and an overview of visual analytics approaches to extracting vari-

ous kinds of information and knowledge. Jiang (Chapter 13) proposes the head/

tail breaks is a powerful tool for visualizing city structures and dynamics, and

uses social media location data to illustrate its eectiveness in visualization.

Lemmens etal. (Chapter 14) present ways to enrich the unstructured nature of

VGI through semantic enrichment and explain how folksonomies and ontolo-

gies play a fundamental role. Karagoz et al. (Chapter 15) focus on detecting

real-world events by following posts in microblogs by employing a process

for toponym recognition and location estimation. Song and Xia (Chapter 16)

concentrate on spatio-temporal variation of sentiment polarity patterns of

georeferenced Tweets, with a view to understanding how opinions evolve on

Twitter over space and time and across communities of users. Stojanocski et al.

(Chapter 17) present a methodology for detecting and identifying social hot-

spots from Twitter stream data and applying sentiment analysis on the data in

New York. Finally, Steiger et al. (Chapter 18) provide a state of the art survey on

social media data analysis and mining from a GIScience perspective.

PART IV: VGI and crowdsourcing in environmental monitoring

Part IV presents several case studies where crowdsourced geographic infor-

mation has been applied especially in the eld of environmental monitoring.

Kettunen et al. (Chapter 19) describe several examples to illustrate the changing

6 European Handbook of Crowdsourced Geographic Information

role of citizens in environmental monitoring in Finland. Jokar Arsanjani and

Fonte (Chapter 20) investigate the completeness, thematic accuracy and t-

ness for use of OpenStreetMap features for land mapping purposes in Europe.

Lupia and Estima (Chapter 21) evaluate the adequacy of the geotagged pho-

tos available at Panoramio for monitoring Land Use/Cover (LULC) in urban

areas, taking Rome (Italy) as the study area. Oltra et al. (Chapter 22) introduce

AtrapaelTigre.com, a citizen science project focusing on the Asian tiger mos-

quito in Spain, and describe lessons they have learned. De Albuquerque et al.

( Chapter23) close the section by reviewing the use of crowdsourced geographic

information for disaster risk management and improving urban resilience and

suggesting future research directions.

PART V: VGI in mobility applications

Part V includes several case studies and research activities of VGI in smart

cities and mobility applications. Zipf et al. (Chapter 24) investigate the use of

OpenStreetMap for routing and navigation for mobility-impaired persons and

describe existing challenges in this aspect. Farkas (Chapter 25) introduces a

crowdsourcing based smart timetable service for public transportation. Lendák

(Chapter 26) reviews existing mobile crowdsourcing projects in smart city,

focusing on environmental monitoring, citizen collaboration, urban mobility,

health/tness and social networking. Finally, Stojanovic et al. (Chapter 27) pre-

sent a framework and some applications to illustrate how mobile crowdsourc-

ing can be used for enabling smart urban mobility.

PART VI: VGI in spatial planning

Part V includes a broad variety of case studies and research activities of VGI in

spatial planning. Huang and Gartner (Chapter 28) illustrate how mobile crowd-

sourcing and social media data can be used to study people’s aective responses

to dierent environments, as well as the potential applications of these aective

data. Massa and Campagna (Chapter 29) introduce Spatext, a tool that allows

integration of VGI and authoritative data, and present a case study to illustrate

its application in urban planning. Basiouka and Potsiou (Chapter 30) inves-

tigate the use of VGI and crowdsourcing in Cadastre design, and propose a

crowdsourcing cadastral model for ocial cadastral surveys. And in the last

chapter, Fan and Zipf (Chapter 31) investigate the generation of 3D city models

by using OpenStreetMap data and introduce the OSM-3D project.

In addition, the book consolidates the references and information from all the

chapters in a rich bibliography and a glossary, thereby providing a state-of-the-

art of research on crowdsourced and volunteered geographic information, as

Introduction 7

well as valuable reference for PhD candidates and senior researchers from many

disciplines who aim to tap into the potential of new geographic data sources.

Concluding Remarks

As this collection demonstrates, research into crowdsourced geographic infor-

mation or VGI (depending on the denition that the researchers prefer), has

made signicant inroads in a relatively short period of 7 or 8 years. Yet the book

opens questions and points to new research directions, in addition to the nd-

ings that each of the researchers demonstrate.

As can be seen from this book, the crowdsourcing techniques and methods

and the VGI phenomenon have motivated a multidisciplinary research commu-

nity to identify both elds of applications and quality criteria depending on the

use of VGI. Besides harvesting tools and storage of these data, many research

attentions have been paid to these information resources, in an age when infor-

mation is one of the most important drivers of development. e participation

component is a fundamental aspect of crowdsourced information and it reveals

both a new way of doing science with a problem-solving approach.

Despite rapid progress in VGI research, this book also shows that there are tech-

nical, social, political and methodological challenges that require further studies

and research. We hope that the book will spark new research questions and devel-

opment—and hopefully foster new research collaborations, and friendships.

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