Visual Question Answering system integrated with Unmanned Aerial Vehicle\n(UAV) has a lot of potentials to advance the post-disaster damage assessment\npurpose. Providing assistance to affected areas is highly dependent on\nreal-time data assessment and analysis. Scope of the Visual Question Answering\nis to understand the scene and provide query related answer which certainly\nfaster the recovery process after any disaster. In this work, we address the\nimportance of \\textit{visual question answering (VQA)} task for post-disaster\ndamage assessment by presenting our recently developed VQA dataset called\n\\textit{HurMic-VQA} collected during hurricane Michael, and comparing the\nperformances of baseline VQA models.\n