Modeling high-resolution spatiotemporal land-use data

Spatiotemporal land-use data offer the potential to improve our understanding of the past as well as enhance our ability to manage land and plan for the future. Although there is a need for spatiotemporal data in decision making, local governments often do not have or even do not see the need for these data. This paper addresses these information gaps by both presenting and testing a model that outputs annual parcel-level land-use data based on a single year’s cadastral layer and demonstrating the policy relevance of model outputs. Spatiotemporal data are modeled from an attribute recording date of building construction associated with parcels and a small number of straightforward transition rules. Model validation is demonstrated with an error analysis of estimated land-use transitions indicating accurate results over the time period of the modeling. The policy relevance of the modeling is demonstrated by incorporating spatiotemporal data outputs into the evaluation of local government goals, objectives and policy as articulated in a comprehensive plan. The value of the model lies in its explanatory power, simplicity, and potential to address local government issues with both spatial and temporal dimension