Remote Sensing-Based Framework for Detecting and Interpreting Permafrost Terrain Hydrologic Connectivity

Arctic coasts are among the most vulnerable landscape on Earth, where periglacial terrain undergoes thermal contraction and expansion through seasonal freeze–thaw cycles. Along the Utqiaġvik (formerly Barrow), Alaska coastline, shifting thermal regimes have accelerated ice wedge degradation, influenced by the evolution of polygonal trough networks. However, accurately mapping trough structure, variability, and hydrologic connectivity across spatial scales remains challenging. This study integrates high-resolution remote sensing and terrain modeling to investigate the relationship between surface hydrology and ice wedge polygon morphology. Using a 0.5 m resolution LiDAR-derived digital elevation model (DEM), ice wedge polygons were manually delineated and compared with Thiessen (Voronoi)  polygons to evaluate differences in structure, spatial extent, and representation of natural variability. Intersection analyses revealed significant discrepancies in boundary alignment and area estimates between the two approaches. Hydrologic influences on polygon development were assessed through compound terrain analysis, drainage network extraction, and surface flow modeling. Results show strong spatial correspondence between modeled flow paths and mapped trough networks, indicating that surface hydrology plays a key role in ice wedge thaw and trough evolution. Calculated hydrologic and morphometric parameters suggest high runoff potential, driven by flat terrain, permafrost-limited infiltration, dense drainage networks, and short overland flow paths. High TWI (> 12) and SPI (> 60) values mark zones of concentrated surface saturation and flow accumulation, often coinciding with trough depressions. Despite high runoff potential, minimal gradients lead to slow-moving flow and persistent surface ponding, contributing to widespread wetland formation. This integrated approach demonstrates the value of combining high-resolution topographic data with hydrologic modeling to improve detection and interpretation of permafrost terrain features. The framework developed offers a scalable method for monitoring Arctic terrain dynamics and enhances remote sensing applications for assessing permafrost vulnerability.