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The forests of coastal Alaska and British Columbia are globally significant for their high carbon storage capacity and complex forest structure, hosting some of the densest values of aboveground biomass in the world. These ecosystems support biodiversity, provide critical habitat, and serve as long-term carbon sinks, offering resilience to climate change. However, comprehensive, spatially continuous estimates of forest structure across this region have been limited, particularly across political boundaries. In this study, we used a Gradient Nearest Neighbor (GNN) modeling approach to integrate extensive forest inventory plot data with satellite-derived environmental variables. This approach enabled us to produce moderate-resolution (30-meter) maps of aboveground biomass, species biomass, forest age, basal area, and additional structural attributes. Our results indicated that climate and topography accounted for the majority of the explainable variation across all modeling regions. Predictions of aboveground live biomass were higher than previous estimates, particularly in Southeast Alaska, where estimates were 30–53 % greater than previous studies. Forest structure varied across the region, with older forests found in Southeast Alaska and higher tree densities in British Columbia. Collectively, the coastal forests of Alaska and British Columbia store approximately 3.58 petagrams of carbon. These spatially explicit maps offer critical insights for carbon monitoring, forest management, and biodiversity conservation across this ecologically diverse and politically fragmented landscape.