# Natural Disasters Detection in Social Media and Satellite imagery: a survey

arXiv: https://arxiv.org/abs/1901.04277 · HTML: https://mlsanity.com/paper/1901.04277/

## Key facts

- Cited by 27 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Jan 2019.

## Built on by (most cited first, 27 of 27)

- [Incidents1M: a large-scale dataset of images with natural disasters, damage, and incidents](https://mlsanity.com/paper/2201.04236/) (2022)
- [MEDIC: A Multi-Task Learning Dataset for Disaster Image Classification](https://mlsanity.com/paper/2108.12828/) (2021)
- [Harnessing Large Language Models for Disaster Management: A Survey](https://mlsanity.com/paper/2501.06932/) (2025)
- [Continual Learning for Smart City: A Survey](https://mlsanity.com/paper/2404.00983/) (2024)
- [ContCommRTD: A Distributed Content-based Misinformation-aware Community Detection System for Real-Time Disaster Reporting](https://mlsanity.com/paper/2301.12984/) (2023)
- [Social Media as an Instant Source of Feedback on Water Quality](https://mlsanity.com/paper/2202.04462/) (2022)
- [Common Practices and Taxonomy in Deep Multi-view Fusion for Remote Sensing Applications](https://mlsanity.com/paper/2301.01200/) (2022)
- [CrisisViT: A Robust Vision Transformer for Crisis Image Classification](https://mlsanity.com/paper/2401.02838/) (2024)
- [Robust Training of Social Media Image Classification Models for Rapid Disaster Response](https://mlsanity.com/paper/2104.04184/) (2021)
- [Document Provenance and Authentication through Authorship Classification](https://mlsanity.com/paper/2303.01197/) (2023)
- [Stylometry Analysis of Multi-authored Documents for Authorship and Author Style Change Detection](https://mlsanity.com/paper/2401.06752/) (2024)
- [A Named Entity Recognition and Topic Modeling-based Solution for Locating and Better Assessment of Natural Disasters in Social Media](https://mlsanity.com/paper/2405.00903/) (2024)
- [Floods Relevancy and Identification of Location from Twitter Posts using NLP Techniques](https://mlsanity.com/paper/2301.00321/) (2023)
- [Sentiment Analysis of Users' Reviews on COVID-19 Contact Tracing Apps with a Benchmark Dataset](https://mlsanity.com/paper/2103.01196/) (2021)
- [Explainable Event Recognition](https://mlsanity.com/paper/2110.00755/) (2021)
- [NLP Techniques for Water Quality Analysis in Social Media Content](https://mlsanity.com/paper/2112.11441/) (2021)
- [Relevance Classification of Flood-related Twitter Posts via Multiple Transformers](https://mlsanity.com/paper/2301.00320/) (2023)
- [MONITRS: Multimodal Observations of Natural Incidents Through Remote Sensing](https://mlsanity.com/paper/2507.16228/) (2025)
- [Visual Sentiment Analysis: A Natural DisasterUse-case Task at MediaEval 2021](https://mlsanity.com/paper/2111.11471/) (2021)
- [SolarFormer: Multi-scale Transformer for Solar PV Profiling](https://mlsanity.com/paper/2310.20057/) (2023)
- [Deep Models for Visual Sentiment Analysis of Disaster-related Multimedia Content](https://mlsanity.com/paper/2112.12060/) (2021)
- [Deep Learning Driven Detection of Tsunami Related Internal GravityWaves: a path towards open-ocean natural hazards detection](https://mlsanity.com/paper/2308.04611/) (2023)
- [Event detection from novel data sources: Leveraging satellite imagery alongside GPS traces](https://mlsanity.com/paper/2401.10890/) (2024)
- [S3Former: Self-supervised High-resolution Transformer for Solar PV Profiling](https://mlsanity.com/paper/2405.04489/) (2024)
- [Social Media Informatics for Sustainable Cities and Societies: An Overview of the Applications, associated Challenges, and Potential Solutions](https://mlsanity.com/paper/2412.03600/) (2024)
- [AI and Generative AI Transforming Disaster Management: A Survey of Damage Assessment and Response Techniques](https://mlsanity.com/paper/2505.08202/) (2025)
- [Cross-Modal Rationale Transfer for Explainable Humanitarian Classification on Social Media](https://mlsanity.com/paper/2603.18611/) (2026)

## Abstract (arXiv)

The analysis of natural disaster-related multimedia content got great attention in recent years. Being one of the most important sources of information, social media have been crawled over the years to collect and analyze disaster-related multimedia content. Satellite imagery has also been widely explored for disasters analysis. In this paper, we survey the existing literature on disaster detection and analysis of the retrieved information from social media and satellites. Literature on disaster detection and analysis of related multimedia content on the basis of the nature of the content can be categorized into three groups, namely (i) disaster detection in text; (ii) analysis of disaster-related visual content from social media; and (iii) disaster detection in satellite imagery. We extensively review different approaches proposed in these three domains. Furthermore, we also review benchmarking datasets available for the evaluation of disaster detection frameworks. Moreover, we provide a detailed discussion on the insights obtained from the literature review, and identify future trends and challenges, which will provide an important starting point for the researchers in the field.