Snow cover significantly influences ground temperatures in Arctic permafrost regions, thus accurate monitoring of snow properties—such as depth and albedo—is essential for understanding permafrost stability, but remains difficult in urban Arctic environments due to complex surface conditions and limited validated satellite methods.

This study addresses these challenges by integrating high-resolution Sentinel-2 satellite imagery with field measurements to analyze seasonal snow cover dynamics in Utqiaġvik, Alaska. We examined how infrastructure density affects snow retention and melt patterns. Snow depth and albedo were derived using empirical models based on the Normalized Difference Snow Index (NDSI) and validated with in situ data collected during a May 2025 field campaign.

Results show that areas with high building density experience earlier and more rapid snowmelt, while lower-density zones retain snow cover and higher albedo later into the spring. However, urban snow management practices, such as snow piling, can prolong snow cover in specific locations. The strong agreement between satellite and field data confirms the reliability of this remote sensing approach.

Our findings offer a scalable method for snow monitoring in permafrost-affected communities and highlight the role of urban infrastructure in shaping snow cover dynamics under a changing Arctic climate.