Our findings examine several data inputs for probabilistic regional sea-level rise (SLR) impact predictions. To predict coastal response to SLR, detailed information on the landscape, including elevation, vegetation, and/or level of development, is needed. However, we find that the inherent relationship between elevation and land cover datasets (e.g., beaches tend to be low lying) is used to reduce error in a coastal response to SLR model, suggesting new applications for areas of limited data.