Glacier Mapping

Glacier mapping aims to accurately delineate glacier boundaries and monitor their changes over time, crucial for understanding climate change impacts and managing water resources. Current research heavily utilizes deep learning, employing convolutional neural networks (CNNs), transformer models, and hybrid architectures like U-Nets, often incorporating multi-sensor data (optical, radar, lidar) to improve accuracy, particularly in challenging areas like debris-covered or calving glaciers. These advancements enable more efficient and accurate global-scale glacier monitoring, providing essential data for improved climate models and hazard assessments.