As storms and floods become a hazard, our research highlights the need for solutions and shows how geospatial technologies are developing. The suggested approach, which increases resistance to floods, earthquakes, and storms by utilizing state-of-the-art techniques like convolutional neural networks (CNNs), ANNs, and deep learning, signifies a paradigm shift in disaster management. The integration of various geographical data, such as satellite photos, sensor networks, and historical data, forms the core of our methodology. To increase the accuracy of predictions, neural networks are utilized to examine trends in past data. Continual feedback from the integration of real data enables the system to continuously adjust and enhance its conclusions in response to changes. This study demonstrates the technology’s potential to protect lives and reduce the economic impact of hurricanes and floods. CNN), artificial neural network (ANN), emergency preparedness, early warning.