Please use this identifier to cite or link to this item: https://doi.org/10.34133/remotesensing.0105
Title: Crowdsourcing Geospatial Data for Earth and Human Observations: A Review
Authors: Huang, Xiao
Wang, Siqin
Yang, Di
Hu, Tao
Chen, Meixu
Zhang, Mengxi
Zhang, Guiming
Biljecki, Filip 
Lu, Tianjun
Zou, Lei
Wu, Connor YH
Park, Yoo Min
Li, Xiao
Liu, Yunzhe
Fan, Hongchao
Mitchell, Jessica
Li, Zhenlong
Hohl, Alexander
Issue Date: Jan-2024
Publisher: American Association for the Advancement of Science (AAAS)
Citation: Huang, Xiao, Wang, Siqin, Yang, Di, Hu, Tao, Chen, Meixu, Zhang, Mengxi, Zhang, Guiming, Biljecki, Filip, Lu, Tianjun, Zou, Lei, Wu, Connor YH, Park, Yoo Min, Li, Xiao, Liu, Yunzhe, Fan, Hongchao, Mitchell, Jessica, Li, Zhenlong, Hohl, Alexander (2024-01). Crowdsourcing Geospatial Data for Earth and Human Observations: A Review. Journal of Remote Sensing 4. ScholarBank@NUS Repository. https://doi.org/10.34133/remotesensing.0105
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.
Source Title: Journal of Remote Sensing
URI: https://scholarbank.nus.edu.sg/handle/10635/246823
ISSN: 2694-1589
DOI: 10.34133/remotesensing.0105
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