Floodwater-Level Estimation from Social Media Images
Master Thesis + PhD project, EcoVision Lab, Photogrammetry and Remote Sensing, ETH Zürich, Zurich
In this paper, we have presented a model to predict flood-water level from images gathered from social media platforms in a fully automatized way. The prediction is done using a deep learning framework. More specifically we have build this model on top of the Mask R-CNN architecture. The proposed model performs instance segmentation and at the same time predicts flood level whenever an instance of some specific objects is detected. We further provide a method to combine the multiple object instances level predictions and obtain a single water level prediction for the entire image. The conducted experiments proved the ability of the trained model to effectively predict water level from images within an acceptable error.
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