reviewOpen MINDJan 1, 2017Closed access

Deep learning in remote sensing: A comprehensive review and list of resources

ZXZhu, Xiao XiangTDTuia, DevisMLMou, LichaoXGXia, Gui-SongZLZhang, Liangpei

Abstract

Standing at the paradigm shift towards data-intensive science, machine learning techniques are becoming increasingly important. In particular, as a major breakthrough in the field, deep learning has proven as an extremely powerful tool in many fields. Shall we embrace deep learning as the key to all? Or, should we resist a 'black-box' solution? There are controversial opinions in the remote sensing community. In this article, we analyze the challenges of using deep learning for remote sensing data analysis, review the recent advances, and provide resources to make deep learning in remote sensing ridiculously simple to start with. More importantly, we advocate remote sensing scientists to bring their expertise…

Citation impact

2,813
total citations
FWCI
200.16
Percentile
100%
References
203
Citations per year

Authors

7
  • ZX
    Zhu, Xiao XiangCorresponding
  • TD
    Tuia, Devis
  • ML
    Mou, Lichao
  • XG
    Xia, Gui-Song
  • ZL
    Zhang, Liangpei

Topics & keywords

Keywords
  • Deep learning
  • Computer science
  • Data science
  • Field (mathematics)
  • Key (lock)
  • Urbanization
  • Artificial intelligence
  • Black box
UN Sustainable Development Goals
  • Sustainable cities and communities
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