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research article

Geoinformation Harvesting From Social Media Data: A community remote sensing approach

Zhu, Xiao Xiang
•
Wang, Yuanyuan
•
Kochupillai, Mrinalini
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December 1, 2022
Ieee Geoscience And Remote Sensing Magazine

As unconventional sources of geoinformation, massive imagery and text messages from open platforms and social media form a temporally quasi-seamless, spatially multiperspective stream, but with unknown and diverse quality. Due to its complementarity to remote sensing (RS) data, geoinformation from these sources offers promising perspectives, but harvesting is not trivial due to its data characteristics. In this article, we address key aspects in the field, including data availability, analysis-ready data preparation and data management, geoinformation extraction from social media text messages and images, and the fusion of social media and RS data. We then showcase some exemplary geographic applications. In addition, we present the first extensive discussion of ethical considerations of social media data in the context of geoinformation harvesting and geographic applications. With this effort, we wish to stimulate curiosity and lay the groundwork for researchers who intend to explore social media data for geoapplications. We encourage the community to join forces by sharing their code and data.

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Type
research article
DOI
10.1109/MGRS.2022.3219584
Web of Science ID

WOS:000937199800009

Author(s)
Zhu, Xiao Xiang
Wang, Yuanyuan
Kochupillai, Mrinalini
Werner, Martin
Haeberle, Matthias
Hoffmann, Eike Jens
Taubenboeck, Hannes
Tuia, Devis  
Levering, Alex
Jacobs, Nathan
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Date Issued

2022-12-01

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

Published in
Ieee Geoscience And Remote Sensing Magazine
Volume

10

Issue

4

Start page

150

End page

180

Subjects

Geochemistry & Geophysics

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Remote Sensing

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Imaging Science & Photographic Technology

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ethics

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codes

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social networking (online)

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streaming media

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data mining

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remote sensing

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cultural ecosystem services

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land-use classification

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damage assessment

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big data

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data-collection

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urban areas

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information

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twitter

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cover

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images

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
ECEO  
Available on Infoscience
March 27, 2023
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/196533
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