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Deep Learning Models for Estimation of Flood Severity Using Multimodal and Satellite Images

This paper addresses the Multimedia Satellite Task at MediaEval 2019. We have focussed on the challenge of extracting information present in satellite images. Satellite images provide variety of information like weather, how any event on land unfolds and hence they play an important role in disaster management. We present our approaches for three subtasks: (1) Image-based News Topic Disambiguation, (2) Multimodal Flood Level Estimation from news, (3) Classification of citycentered satellite sequences. All three tasks are related to classifying the images as flood related or not. We have discussed about the performance of proposed CNN models and pre-trained models in the context of binary classification of images for flood related data.