This paper explores the inter-connectedness of the evolution of transportation networks and land use through the application of a Markov Chain mode. The model investigates how individual cells, with both land use and transportation network attributes, change over time. While this paper does not consider land use density directly, it does not consider land use type, and as cells change, it can be concluded that some form of development is likely to be occurring. The next section of the paper outlines the Markov Chain model and a discussion of the Twin Cities data used in the study follows. The subsequent section develops the transition probability matrices used by the Markov Chain. Those matrices are analyzed in order to understand the empirical regularities that appear in the data. They are then applied to both assess the predictive ability of the Markov Chain model (comparing what the model would predict with what actually happened), and then applying the mode to forecast future changes the Twin Cities area. The paper concludes with some suggestions for future research.
Document type: Part of book or chapter of book
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