A data infrastructure would provide access to a common set of data resources that are necessary for running and validating models of land change. Infrastructure developments that aim to support compilation, curation, and comparison of the heterogeneous data sources for input to land change models would advance this kind of access directly.
Community modeling and governance
A consistent and widely adopted community modeling and governance infrastructure is important to support developments in LCM. Such an infrastructure would provide mechanisms for making decisions and advancing modeling capabilities within a broad community and toward specific, achievable goals and capabilities. In particular, it would provide a framework for reaching community agreement on specific goals and endpoints to move modeling and data capabilities forward.
There are a variety of practices that can enhance land-change modeling to make it more scientifically rigorous and useful in application. Some of these practices are established but not always followed, while others require more research to test and establish.
Sensitivity analysis is an established procedure whereby the investigator examines the variation in model output due to specific amounts of variation in model input, parameter values, or structure.
Pattern validation requires matching the choice of a metric that compares model output to data with the purpose of the modeling exercise for the particular application; how this is best done requires additional research.
Structural validation, or validating model processes, remains a challenging task in part because the underlying processes that give rise to observed land-use patterns are themselves not fully observable. Continued research on how to validate the maintained assumptions that are necessary in order to even specify a model would benefit model validation and projections.
Multiple communities of science and practice in critical areas associated with environmental sustainability, including food, water, energy, climate, health, and urbanization, are adopting land-change models (LCMs) to help with understanding and improving human-environment interactions at multiple scales. While LCMs have already contributed in all of these areas, an opportunity exists to consolidate the understanding of land system interactions, refine and improve the