Application of Artificial Intelligence Algorithms for Earthquake Damage Mapping Using Very High-Resolution Satellite Imagery: Case Studies from Al Hoceima, Morocco, and Gaziantep, Turkey

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Abstract

Seismic events continue to challenge the resilience of urban systems, particularly in regions marked by tectonic complexity and high population density. In such contexts, timely and accurate damage assessment remains critical for effective emergency response. This study explores the potential of very high-resolution (VHR) satellite imagery integrated with artificial intelligence (AI) to enhance the spatial understanding of post-earthquake structural impacts. By focusing on two distinct seismic events, the 2004 Al Hoceima earthquake in Morocco and the 2023 Gaziantep earthquake in Turkey. The research underscores the utility of AI-supported remote sensing in overcoming the limitations of conventional ground-based methods. Emphasis is placed on the capacity of VHR imagery to capture subtle spatial variations that are often overlooked during manual assessments. The findings highlight the potential of integrating AI with satellite data as a scalable, transferable, and practical solution for disaster risk management. Broader implications are drawn for future applications in real-time decision making, urban resilience planning, and the development of data-driven humanitarian strategies.

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