Access to Destinations: Monitoring Land Use Activity Changes in the Twin Cities Metropolitan Region

Abstract

This study presents an effort to track and model land use change in the Twin Cities Metropolitan Region. To that end, we make use of a unique, high-resolution, cell-level set of land use data for the Twin Cities. The data represent 75 meter by 75 meter land use cells, observed at several points in time during the period from 1958 to 2005. These data are used to validate three different types of land use models, which then are used to forecast land use several decades into the future. The models applied in this study include Markov Chain models, Markov Chain-Cellular Automata (MC-CA) models, and an empirical model based on a logistic regression specification. The models are intended to have a simple, transparent structure that allows the user to identify sources of forecast error. Forecasts of land use are made both for the entire study area and also for a specific corridor along State Highway 610 in the northwestern suburbs of the Twin Cities. The study concludes with a brief discussion of the limitations of the models, and how they might meaningfully be expanded and applied.