This paper presents the various algorithms that the CERTH-ITI team has implemented to tackle three tasks that relate to the problem of flood severity estimation, using satellite images and online media content. Deep Convolutional Neural Networks were deployed to classify articles as flood event-related based on their images, but also to detect flooding events in satellite sequences. Remote sensing indices play a key role in the machine learning approach to identify changes between satellite imagery, while visual and textual features were exploited to estimate whether an image shows people standing in flooded areas.