The insights gained from these analyses are pivotal for refining AI-driven disaster prediction models. For the Tōhoku earthquake, our work supports the development of enhanced tsunami warning systems and informs structural engineering practices to withstand high-magnitude seismic events. For the Bárðarbunga eruption, our findings enable better prediction of volcanic activity and associated seismic risks, facilitating improved evacuation plans and infrastructure protection. By leveraging these analyses, Map Transit contributes to more accurate early warning systems, robust risk assessments, and effective mitigation strategies, ultimately reducing the impact of natural disasters on communities and economies.