Predicting land-cover and land-use change in the urban fringe: A case in Morelia city, Mexico

Land-cover and land-use (LCLU) change was quantified for the last 35 years within and in the vicinity of a fast growing city in Mexico, using rectified aerial photographs and geographic information systems (GIS). LCLU change was projected for the next 20 years using Markov chains and regression analyses. The study explored the relationships between urban growth and landscape change, and between urban growth and population growth. The analysis of Markov matrices suggests that the highest LCLU attractor is the city of Morelia, followed by plantations and croplands. Grasslands and shrublands are the least stable categories. The most powerful use of the Markov transition matrices seems to be at the descriptive rather than the predictive level. Linear regression between urban and population growth offered a more robust prediction of urban growth in Morelia. Hence, we suggest that linear regression should be used when projecting growth tendencies of cities in regions with similar characteristics.