Armaan Brar

Urban subsidence, largely driven by extensive groundwater extraction, presents significant challenges to infrastructure and urban planning, particularly in rapidly urbanizing regions like Mexico City. This study utilizes Sentinel-1 synthetic aperture radar (SAR) data in conjunction with advanced interferometric techniques—Small Baseline Subset (SBAS) and Persistent Scatterers (PS)—to monitor and analyze subsidence patterns across Mexico City from 2019 to 2024. By integrating these methods, the study provides a detailed understanding of both broad subsidence trends and localized deformations, revealing critical insights into infrastructure vulnerabilities. The analysis identifies specific areas, particularly in Venustiano Carranza and Iztapalapa, where subsidence poses significant risks to buildings and infrastructure, underscoring the importance of targeted mitigation efforts. The study also highlights the potential for future research to incorporate additional data sources, such as high-resolution optical imagery and ground-based GPS measurements, as well as advanced deep learning techniques, to further refine subsidence monitoring and enhance urban planning strategies.
Keywords: Urban subsidence, Sentinel-1 SAR, SBAS, Persistent Scatterers, Mexico City, ground deformation, infrastructure risk, remote sensing, interferometric techniques, groundwater extraction.