Integrating Geospatial Technologies, AI, and Regional Policy Frameworks to Address Climate Induced and Irregular Migration: Implications for U.S. Border Security and Global Migration Governance
Olusola AKANNI
*
Department of Migration Studies, University of San Francisco, CA, USA.
Nomathemba TSHUMA
Department of Migration Studies, University of San Francisco, CA, USA.
*Author to whom correspondence should be addressed.
Abstract
Numerous factors such as climate change has forced thousands of people to seek refuge in safer neighborhoods and irregular migration patterns are reshaping global power dynamics, challenging both individual populations and traditional border security strategies. This study explores how cross-border collaboration, leveraging geospatial monitoring technologies and artificial intelligence (AI), can enhance migration management. By analyzing the impact of hurricanes, land degradation, and coastal flooding, the research highlights how real-time environmental data and predictive AI tools provide localized insights for decision-makers. The paper also discusses how regional alliances can develop safer migration routes particularly between Mexico and the United States to mitigate the risks associated with dangerous and unauthorized pathways. Ethical considerations surrounding surveillance and privacy are addressed, advocating for balanced reforms in political systems. Key recommendations include the deployment of AI-based early warning systems, revised asylum policies, and strengthened climate resilience networks, aligning border security measures with humanitarian principles.
Keywords: Geospatial technologies, artificial intelligence (AI), climate-induced migration, border security, human trafficking, regional migration agreements