GLOF-Vulnerability Identification Based on Automatic Method for Mapping Glacial Lakes in Cordillera Blanca (Peru)

• Nury Arosquipa USP
• R. Hirata USP

Resumo

Glacial lake outburst floods (GLOFs) pose a significant threat to high-mountain communities and infrastructure, particularly in glacierized regions such as the Cordillera Blanca, Peru. This study presents an automated method for mapping glacial lakes using Sentinel-2 satellite imagery with enhanced band combinations and a segmentation-based foundational model (SAM 2.1). Our method enables consistent multitemporal lake extraction, which successfully mapped 80% of 448 manually identified glacial lakes. We performed a comparative analysis of images taken from May 2016 and May 2024, and identified five lakes potentially vulnerable to GLOFs. Notably, Lake Parón and Lake Piticocha experienced significant surface area expansion of 13.79 and 3.72 hectares, respectively. The other three lakes showed significally expansion despite its smaller size. GLOF simulations incorporating local topography and lake size indicate potential impacts on urban areas (e.g., Caraz city) and agricultural land. These findings highlight the importance of standarized and automated glacial lake monitoring for early risk assessment and disaster preparedness in the face of climate-driven glacial change.

Palavras-chave: Graphics, Image segmentation, Image color analysis, Prevention and mitigation, Urban areas, Lakes, Feature extraction, Surface topography, Satellite images, Monitoring