Arctic coastal environments are rapidly changing in response to sea ice loss, permafrost degradation, and changing sea states. Intensification of Arctic coastal dynamics has been broadly noted, but variability in landscape morphology and local soil and/or permafrost conditions makes coastal erosion difficult to predict. Many of the environmental factors that influence erosion processes vary over a wide range of temporal and spatial scales. Further, in situ data collection in Arctic environments is limited. Remotely sensed observations and geospatial datasets allow us to examine the variability in coastal landscapes over large spatial extents to understand both the variability in surface and subsurface landscape conditions and how erosion rates vary with these conditions. Here, we present a compilation of remotely sensed and geospatial datasets on the North Slope of Alaska and use it to develop a set of coastal typologies that capture the variability in environments susceptible to coastal erosion. We describe the relationships between surface and subsurface characteristics and historical erosion rates, and we examine the sensitivity of erosion to numerous local conditions. Finally, we present a framework for using geospatial and remotely sensed data in combination with numerical modeling to estimate rates of shoreline change and sediment fluxes at the coarse scale of Earth system models.