The theme of this year’s International Day for Disaster Risk Reduction, “Fund Resilience, Not Disasters,” calls for the urgent need to shift from reactive spending on recovery to proactive investment in disaster risk reduction. Advancements in satellite imagery analysis and artificial intelligence (AI) now enable us to map hazards, exposures and vulnerabilities more effectively, providing timely and clearer insights into who and what is at risk, and guiding more targeted investments in resilience and disaster preparedness. Leveraging these advances is essential to building resilience and is an imperative to safeguard lives and livelihoods in Asia and the Pacific - the world’s most disaster-prone region. 

Building on advances in big Earth data, cloud computing, and artificial intelligence, a new tool - SatGPT - offers an innovative solution that supports flood risk mapping. Developed by UN ESCAP in collaboration with regional technical and institutional partners, it represents a functional, next-generation spatial decision support system designed for rapid deployment, which would be most beneficial in flood-prone and resource-limited contexts. 

By mapping historical hotspots and past flooding events using a massive collection of archived satellite imagery, insights from SatGPT help inform the allocation of disaster risk reduction investments to where they are needed most, reducing both human and economic losses. SatGPT contributes to the implementation of  the four pillars of the Early Warnings for All Initiative by enhancing disaster risk knowledge and providing historical flooding data. It can also contribute to improved forecasting models, strengthen early warning analysis, and inform preparedness and response strategies. SatGPT and other technological advancements open an opportunity to deliver risk information that is consistent, accessible, comparable, and open-source, enabling evidence-based disaster risk reduction investment decisions. 

Country-specific initiatives further demonstrate the value of Earth observation data and digital innovations. For example, the Philippine Space Agency Integrated Network for Space-Enabled Actions towards Sustainability (PINAS) builds a community empowered by space data, connecting citizens, public, and private sectors to work together toward improved disaster response and sustainable development. Indonesia is developing an AI project on flood mapping with pilot sites in Jakarta and North Java Island, and SatGPT is planned to be integrated into this platform. Thailand is developing the Check Nahm (Check Flood) flood warning application that consolidates data from various sources, including CCTV cameras, to enhance early warning systems, provide near real-time updates on the flood situation, and forecasts. The application’s cloud-based data integration can also incorporate SatGPT’s historical mapping capabilities. The University of Hong Kong in Hong Kong, China, demonstrates how flooding exacerbates social inequalities by integrating geospatial information, AI and socioeconomic data. The vulnerability difference was calculated based on the defined social classes and climate scenarios, demonstrating that people with weaker socioeconomic status will face higher exposure risks and greater impacts due to inequality.

The Jakarta Ministerial Declaration on Space Applications for Sustainable Development in Asia and the Pacific highlighted the strong potential of emerging technology applications from the fourth industrial revolution to advance the Sustainable Development Goals. To translate the Declaration into tangible impacts, countries in the region have focused on equipping young government professionals with the skills to rapidly analyze trends and transform geospatial information into actionable insights using SatGPT and other AI-powered tools, driving smarter and faster disaster risk reduction decisions.  Future efforts will respond to countries’ need for enhanced AI development, access to open-source data, standardized methodologies, and opportunities for capacity development. They will also further strengthen the capacities of local governments and communities to adapt and apply AI-powered tools like SatGPT to generate localized insights on high-risk areas, making mitigation and adaptation investments more effective.

As we champion funding for resilience and co-develop AI-powered disaster tools, it is vital to remember that data and technology are only as meaningful as the lives they aim to protect. Behind every map and dataset are real communities facing real risks. Keeping this human perspective at the center of innovation ensures that our efforts remain grounded in empathy, purpose and impact.

The authors would like to acknowledge the contribution of Thanabordee Sakunarunphet, Geo-Informatics and Space Technology Development Agency (GISTDA) and Silvan Anggia Bayu Setia Permana, National Research Innovation Agency (BRIN) to this article.