Journal of Remote Sensing (Jan 2024)

Crowdsourcing Geospatial Data for Earth and Human Observations: A Review

  • Xiao Huang,
  • Siqin Wang,
  • Di Yang,
  • Tao Hu,
  • Meixu Chen,
  • Mengxi Zhang,
  • Guiming Zhang,
  • Filip Biljecki,
  • Tianjun Lu,
  • Lei Zou,
  • Connor Y. H. Wu,
  • Yoo Min Park,
  • Xiao Li,
  • Yunzhe Liu,
  • Hongchao Fan,
  • Jessica Mitchell,
  • Zhenlong Li,
  • Alexander Hohl

DOI
https://doi.org/10.34133/remotesensing.0105
Journal volume & issue
Vol. 4

Abstract

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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.