Post Disaster Mapping with Semantic Change Detection in Satellite Imagery

Ananya Gupta, Elisabeth Welburn, Simon Watson, Hujun Yin

CVPRW 2019 pp. 472-474

doi:10.1109/CVPRW.2019.00062 /cvprw/2019/gupta2019cvprw-post/

Abstract

Accurate road maps are important for timely disaster relief efforts and risk management. Current disaster mapping is done manually by volunteers following a disaster and the process is slow and error prone. We propose a framework for identifying accessible roads in post-disaster satellite imagery by detecting changes from pre-disaster imagery, in conjunction with OpenStreetMap data. We validate our results with data from Indonesia 2018 tsunami, obtained from DigitalGlobe.

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Cite

Text

Gupta et al. "Post Disaster Mapping with Semantic Change Detection in Satellite Imagery." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2019. doi:10.1109/CVPRW.2019.00062

Markdown

[Gupta et al. "Post Disaster Mapping with Semantic Change Detection in Satellite Imagery." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2019.](https://mlanthology.org/cvprw/2019/gupta2019cvprw-post/) doi:10.1109/CVPRW.2019.00062

BibTeX

@inproceedings{gupta2019cvprw-post,
  title     = {{Post Disaster Mapping with Semantic Change Detection in Satellite Imagery}},
  author    = {Gupta, Ananya and Welburn, Elisabeth and Watson, Simon and Yin, Hujun},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2019},
  pages     = {472-474},
  doi       = {10.1109/CVPRW.2019.00062},
  url       = {https://mlanthology.org/cvprw/2019/gupta2019cvprw-post/}
}