Crowdsourcing Geospatial Data for Earth and Human Observations: A Review

Author:

Huang Xiao1ORCID,Wang Siqin2,Yang Di3,Hu Tao4,Chen Meixu5,Zhang Mengxi6,Zhang Guiming7,Biljecki Filip8,Lu Tianjun9,Zou Lei10,Wu Connor Y. H.11,Park Yoo Min12,Li Xiao13,Liu Yunzhe14,Fan Hongchao15,Mitchell Jessica16,Li Zhenlong17,Hohl Alexander18

Affiliation:

1. Department of Environmental Sciences, Emory University, Atlanta, GA, USA.

2. Spatial Sciences Institute, University of Southern California, Los Angeles, CA, USA.

3. Wyoming Geographic Information Science Center, University of Wyoming, Laramie, WY, USA.

4. Department of Geography, Oklahoma State University, Stillwater, OK, USA.

5. Department of Geography and Planning, University of Liverpool, Liverpool, UK.

6. Carilion School of Medicine,Virginia Tech, Blacksburg, VA, USA.

7. Department of Geography & the Environment, University of Denver, Denver, CO, USA.

8. Department of Architecture, National University of Singapore, Singapore, Singapore.

9. Department of Epidemiology and Environmental Health, College of Public Health, University of Kentucky, Lexington, KY, USA.

10. Department of Geography, Texas A&M University, College Station, TX, USA.

11. Department of Management Science and Information Systems, Oklahoma State University, Stillwater, OK, USA.

12. Department of Geography, University of Connecticut, Storrs, CT, USA.

13. Transport Studies Unit, University of Oxford, Oxford, UK.

14. The MRC Centre for Environment and Health, Imperial College London, London, UK.

15. Department of Civil and Environmental Engineering, Norwegian University of Science and Technology, Trondheim, Norway.

16. Spatial Analysis Lab, University of Montana, Missoula, MT, USA.

17. Geoinformation and Big Data Research Laboratory, Department of Geography, The Pennsylvania State University, University Park, PA, USA.

18. Department of Geography, The University of Utah, Salt Lake City, UT, USA.

Abstract

The transformation from authoritative to user-generated data landscapes has garnered considerable attention, notably with the proliferation of crowdsourced geospatial data. Facilitated by advancements in digital technology and high-speed communication, this paradigm shift has democratized data collection, obliterating traditional barriers between data producers and users. While previous literature has compartmentalized this subject into distinct platforms and application domains, this review offers a holistic examination of crowdsourced geospatial data. Employing a narrative review approach due to the interdisciplinary nature of the topic, we investigate both human and Earth observations through crowdsourced initiatives. This review categorizes the diverse applications of these data and rigorously examines specific platforms and paradigms pertinent to data collection. Furthermore, it addresses salient challenges, encompassing data quality, inherent biases, and ethical dimensions. We contend that this thorough analysis will serve as an invaluable scholarly resource, encapsulating the current state-of-the-art in crowdsourced geospatial data, and offering strategic directions for future interdisciplinary research and applications across various sectors.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

General Engineering

Reference279 articles.

1. What is web 2.0: Design patterns and business models for the next generation of software;O'reilly T;Commun Strateg,2007

2. Big data: The management revolution;McAfee A;Harv Bus Rev,2012

3. Crowdsourcing geospatial data;Heipke C;ISPRS J Photogramm Remote Sens,2010

4. Li G Zheng Y Fan J Wang J Cheng R. Crowdsourced data management: Overview and challenges. Paper presented at: Proceedings of the 2017 ACM international conference on Management of Data; 2017 May 14–19; Illinois Chicago USA.

5. Turner A. Introduction to neogeography. Sebastopol (CA): O’Reilly Media Publisher; 2006. p. 54.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Crowdsourced geospatial data is reshaping urban sciences;International Journal of Applied Earth Observation and Geoinformation;2024-02

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3