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

• Published in: IEEE geoscience and remote sensing magazine Vol. 10; no. 4; pp. 150 - 180
• Main Authors: Zhu, Xiao Xiang, Wang, Yuanyuan, Kochupillai, Mrinalini, Werner, Martin, Haberle, Matthias, Hoffmann, Eike Jens, Taubenbock, Hannes, Tuia, Devis, Levering, Alex, Jacobs, Nathan, Kruspe, Anna, Abdulahhad, Karam
• Format: Journal Article
• Language: English
• Published: IEEE 01.12.2022
• Subjects: Codes; Data mining; Ethics; Remote sensing; Social networking (online); Streaming media
• ISSN: 2473-2397; 2168-6831
• DOI: 10.1109/MGRS.2022.3219584

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.