Wainwright Community - Permafrost Thaw Risk Assessment Project

This pilot project develops a geospatial deep learning framework to assess permafrost thaw risk and identify potential relocation or neighborhood extension areas within a buffer zone of the Wainwright region. A 100 m spatial resolution grid system was overlaid across the study area and ingested multiple data layers including drained lakes, ice wedge polygons, InSAR data, contaminated sites, and infrastructure. Future work will include gravel-extraction sites, coastal erosion, thaw slumps, subsidence, ArcticDEM, and detailed infrastructure datasets. All derived features form an input matrix. These variables are combined into a composite risk index, which serves as the target for a deep learning autoencoder pipeline. After data scaling and encoding, the first draft of a deep autoencoder was applied to learn a compressed latent representation, to predict risk level. The resulting risk map is expected to provide actionable insights for community planners seeking to prioritize high risk zones and plan extension or relocation strategies under changing permafrost conditions.