Escalating global disasters demand a strategic transition from static mapping to dynamic intelligence in crisis management. This bibliometric analysis maps the evolutionary trajectory of GIS in disaster research, using a dataset of 3,061 publications from the Web of Science (1993–2025). The findings reveal a profound epistemic transition: the field has evolved from an initial phase of “Reactive Baselining” (1993–2010) to the current era of “Disaster Intelligence” (2019–2025), driven by the integration of AI, deep learning, and real-time spatiotemporal analytics. However, the analysis also uncovers a polarized knowledge landscape where innovation is heavily concentrated in China, the United States, and Western Europe, revealing a significant “digital divide” that restricts the transferability of advanced geospatial tools to under-resourced regions in the Global South. Furthermore, the operationalization of technologies such as digital twins is hindered by interoperability and ethical data governance challenges. Policy implications are critical; to bridge the gap between algorithmic potential and on-the-ground reality, stakeholders must prioritize equitable capacity building, standardize cross-border data protocols, and establish rigorous privacy frameworks. This study provides a strategic roadmap for leveraging next-generation geospatial solutions to foster adaptive, resilient, and ethically governed global disaster management.
Tarhan et al. (Fri,) studied this question.