Sea ice is a porous, two-phase material whose evolution influences climate, ecosystems, and human activities in polar regions. Rapid declines in Arctic sea ice thickness highlight the need for monitoring approaches that resolve small-scale spatial variability, beyond the coarse resolution of satellite-derived products. Seismic methods, based on the analysis of seismic waves guided in the ice layer, provide high-resolution local estimates of ice thickness, but have so far been limited to individual source–receiver paths. Here, we present a methodology to generate maps of sea ice thickness from seismic data. We analyze two complementary datasets acquired on fast ice: controlled-source data recorded by a 16-geophone array in the St. Lawrence Estuary (Canada), and passive data collected by a dense 247-geophone array in Svalbard (Norway). Ice thickness is first estimated along individual paths through waveform inversion based on spectral element modeling. These path-specific estimates are then integrated within a tomographic framework to reconstruct spatially continuous sea ice thickness maps. Our results demonstrate that both active and passive seismic measurements can resolve spatial heterogeneity in ice thickness at high resolution. This seismic-tomographic approach provides a practical and scalable tool for fine-scale monitoring of sea ice in rapidly changing polar environments.