Integrating AI with Remote Sensing for Real-Time Disaster Monitoring and Rapid Response
Eniola Onatayo · International Journal of Research Publication and Reviews · 2025
The integration of Artificial Intelligence (AI) with remote sensing technologies presents a transformative approach to disaster monitoring and rapid response.As natural disasters become increasingly frequent and severe due to climate change, the need for effective real-time monitoring systems has never been more critical.Remote sensing provides vast amounts of data through satellite imagery and aerial surveillance, which can be harnessed to assess and predict disaster scenarios.By employing AI algorithms, particularly machine learning and deep learning techniques, these datasets can be analysed efficiently to identify patterns, detect anomalies, and facilitate predictive modelling.This integration allows for the real-time assessment of disaster impacts, enabling quicker decision-making and resource allocation.Furthermore, AI can enhance the accuracy of damage assessments, improving the effectiveness of emergency response efforts.The combination of AI and remote sensing not only enhances situational awareness but also aids in the formulation of strategic responses to mitigate disaster impacts.As we narrow our focus, this paper explores specific case studies where AI-driven remote sensing has been successfully implemented in disaster scenarios, highlighting best practices and lessons learned.The findings underscore the potential of this integrated approach to revolutionize disaster management practices, ultimately saving lives and reducing economic losses.