Floods

clusters computed by our model for the 2021 Ahr Valley flood in Germany.

Improving Disaster Management with Multimodal Information from Social Media

Thu, 30/10/2025 - 10:00

When a natural disaster occurs, the situation on-site can be quite chaotic and overwhelming, making it hard to understand for emergency responders. To react effectively, a detailed understanding of the situation on the ground is required, as it determines where resources and manpower are deployed. After events such as floods or earthquakes, traditional methods of information gathering and transportation are often hindered, e.g. by physical barriers or overwhelmed call centres.

Leveraging Information Fusion for Enhanced Natural Disaster Management

Wed, 13/03/2024 - 10:00

Seeking to provide insights on human life protection and ways to lessen the effects of catastrophic events, this article explores the importance of the information fusion approach and its application in a variety of natural disaster management (NDM) contexts.

Enhancing Disaster Preparedness through Synthetic Data Generation in AI and Machine Learning

Thu, 02/11/2023 - 10:00

Data is often considered the lifeblood of machine learning algorithms. The availability of vast amounts of data has played a vital role in the rapid development of AI applications across various domains. However, a significant challenge that researchers and practitioners face in the AI landscape is the issue of data scarcity. Data scarcity refers to the limited availability or inadequacy of high-quality data for training AI models.

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