# PulseSatellite: A tool using human-AI feedback loops for satellite image analysis in humanitarian contexts

arXiv: https://arxiv.org/abs/2001.10685 · HTML: https://mlsanity.com/paper/2001.10685/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Jan 2020.

## Built on by (most cited first, 4 of 4)

- [Improving Human-AI Collaboration With Descriptions of AI Behavior](https://mlsanity.com/paper/2301.06937/) (2023)
- [Characterizing Human Explanation Strategies to Inform the Design of Explainable AI for Building Damage Assessment](https://mlsanity.com/paper/2111.02626/) (2021)
- [Multi-AI Complex Systems in Humanitarian Response](https://mlsanity.com/paper/2208.11282/) (2022)
- [An Automated Tip-and-Cue Framework for Optimized Satellite Tasking and Visual Intelligence](https://mlsanity.com/paper/2512.09670/) (2025)

## Abstract (arXiv)

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.