Environmentally Extended Input-Output Databases (EEIOs) provide an effective tool for assessing environmental impacts around the world. These databases have yielded many scientific and policy relevant insights, especially through the national accounting of impacts embodied in trade. However, most approaches average out the spatial variation in different factors, usually at the level of the nation, but sometimes at the subnational level. It is a natural next step to connect trade with local environmental impacts and local consumption. Due to investments in earth observation many new data sets are now available, offering a huge potential for coupling environmental data sets with economic models such as Multi-Region Input-Output (MRIO) models. A key tool for linking these scales are Spatially Explicit Input-Output (SIO) models, which provide both demand and supply perspectives by linking producers and consumers. Here we define an SIO model as a model having a resolution greater than the underlying input-output transaction matrix. Given the increasing interest in this approach, we present a timely review of the methods used, insights gained, and limitations of various approaches for integrating spatial data in input-output modeling. We highlight the evolution of these approaches, and review the methodological approaches used in SIO models so far. We investigate the temporal and spatial resolution of such approaches and analyze the general advantages and limitations of the modeling framework. Finally, we make suggestions for the future development of SIO models.