# Event detection from novel data sources: Leveraging satellite imagery alongside GPS traces

arXiv: https://arxiv.org/abs/2401.10890 · HTML: https://mlsanity.com/paper/2401.10890/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 50 references that are in the map.
- First posted on arXiv 19 Jan 2024.

## Builds on (most cited first, 3 of 3)

- [Natural Disasters Detection in Social Media and Satellite imagery: a survey](https://mlsanity.com/paper/1901.04277/) (2019)
- [Trends in the Diffusion of Misinformation on Social Media](https://mlsanity.com/paper/1809.05901/) (2018)
- [Using convolutional networks and satellite imagery to identify patterns in urban environments at a large scale](https://mlsanity.com/paper/1704.02965/) (2017)

## Abstract (arXiv)

Rapid identification and response to breaking events, particularly those that pose a threat to human life such as natural disasters or conflicts, is of paramount importance. The prevalence of mobile devices and the ubiquity of network connectivity has generated a massive amount of temporally- and spatially-stamped data. Numerous studies have used mobile data to derive individual human mobility patterns for various applications. Similarly, the increasing number of orbital satellites has made it easier to gather high-resolution images capturing a snapshot of a geographical area in sub-daily temporal frequency. We propose a novel data fusion methodology integrating satellite imagery with privacy-enhanced mobile data to augment the event inference task, whether in real-time or historical. In the absence of boots on the ground, mobile data is able to give an approximation of human mobility, proximity to one another, and the built environment. On the other hand, satellite imagery can provide visual information on physical changes to the built and natural environment. The expected use cases for our methodology include small-scale disaster detection (i.e., tornadoes, wildfires, and floods) in rural regions, search and rescue operation augmentation for lost hikers in remote wilderness areas, and identification of active conflict areas and population displacement in war-torn states. Our implementation is open-source on GitHub: https://github.com/ekinugurel/SatMobFusion.