OpenStreetMap: Challenges and Opportunities in Machine Learning and Remote Sensing

@article{VargasMuoz2021OpenStreetMapCA,
  title={OpenStreetMap: Challenges and Opportunities in Machine Learning and Remote Sensing},
  author={John E. Vargas-Mu{\~n}oz and Shivangi Srivastava and Devis Tuia and Alexandre Xavier Falc{\~a}o},
  journal={IEEE Geoscience and Remote Sensing Magazine},
  year={2021},
  volume={9},
  pages={184-199}
}
OpenStreetMap (OSM) is a community-based, freely available, editable map service created as an alternative to authoritative sources. Given that it is edited mainly by volunteers with different mapping skills, the completeness and quality of its annotations are heterogeneous across different geographical locations. Despite that, OSM has been widely used in several applications in geosciences, Earth observation, and environmental sciences. In this article, we review recent methods based on… 

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