An overview of Google Earth Engine for disaster risk management

Google Earth Engine (GEE) has emerged as a transformative tool in disaster risk management (DRM), offering unparalleled access to multisource Earth observation data for large-scale geospatial analysis and real-time disaster monitoring. Through datasets from platforms such as Landsat, Sentinel, and MODIS, GEE facilitates more accurate flood mapping, drought monitoring, and wildfire detection, significantly improving disaster preparedness and response. The platform’s ability to process synthetic aperture radar (SAR) data provides essential flood monitoring insights in cloud-covered regions. In addition, GEE’s integration of machine learning (ML) techniques enhanced predictive modeling and risk assessment, resulting in more accurate disaster forecasting and optimized resource allocation. Moreover, academic institutions in countries like China, the United States, and India are leading in providing potential GEE applications in DRM. Emerging research trends emphasize the increasing use of real-time satellite data and the incorporation of artificial intelligence for multihazard risk assessments. While the GEE has been widely adopted in developed regions, extending its benefits to data-scarce areas remains a significant challenge, particularly in the Global South. Future research should focus on expanding real-time monitoring capabilities, incorporating deep learning models, and addressing the increasing demands of climate change adaptation and urban resilience. GEE’s continued evolution will be critical for advancing global disaster preparedness and enabling more robust, data-driven responses to natural hazards.