Rapid flood extent mapping is an important task for planning response and relief operations. Moreover, vulnerability assessment of a geographical area or a population segment helps humanitarian organizations take timely and informed decisions. In this consortium project funded by QNRF, we aim to leverage two types of non-traditional data sources i.e., satellite and social media and develop robust remote sensing and social media analysis models for real-time data processing. We aim to develop flood segmentation models for both radar and optical satellite imagery. Moreover, to maximize our relevant data points from social media, we aim to develop models to analyze both text and image modalities. In terms of vulnerability assessment, we aim to map social sensing data signals with traditional vulnerability indices, including physical, social, and economic and propose novel indicators useful for vulnerability assessment.