Humanitarian response to natural disasters and conflicts can be assisted by satellite image analysis. In a humanitarian context, very specific satellite image analysis tasks must be done accurately and in a timely manner to provide operational support. We present PulseSatellite, a collaborative satellite image analysis tool which leverages neural network models that can be retrained on-the fly and adapted to specific humanitarian contexts and geographies. We present two case studies, in mapping shelters and floods respectively, that illustrate the capabilities of PulseSatellite.
@article{arxiv.2001.10685,
title = {PulseSatellite: A tool using human-AI feedback loops for satellite image analysis in humanitarian contexts},
author = {Tomaz Logar and Joseph Bullock and Edoardo Nemni and Lars Bromley and John A. Quinn and Miguel Luengo-Oroz},
journal= {arXiv preprint arXiv:2001.10685},
year = {2020}
}