Integration of Multinomial-Logistic and Markov-Chain Models to Derive Land-Use Change Dynamics

Abstract

Land-use change reflects the relationship between human activities and environmental processes over time and space. Modeling land-use change dynamics is of particular environmental, social, and economic importance at regional scales. This paper develops a new approach to model land-use changes by making use of multiple categories that incorporate socioeconomic and environmental factors with multinomial logistic models and Markov chains to quantify the impact of these variables on land-use change dynamics for the years 1990, 2000, and 2010. Spatial autocorrelation and colinearity tests were utilised to screen the most suitable independent variables before modeling. The multinomial logistic model was evaluated by means of a likelihood ratio test and pseudo