Abstract

This study models changes in land cover and land use in the intermediate city of Puerto Montt, Chile, up to 2050. Three distinct time periods-1988, 2005, and 2020-were used to examine Puerto Montt's urban growth during these years. These periods were described using the Local Climate Zones (LCZ) technique. Urban growth scenarios were simulated using the Patch-generating Land Use Simulation (PLUS) model. Using Machine Learning (ML) techniques, this model has been widely utilized to explain how urban growth patterns have evolved based on the dynamics that drive changes in land use and land cover. Three scenarios were developed for this study: Business-As-Usual (BAU) (S1), Urban-Regional Planning (S2), and Conservationist (S3). According to the findings, Puerto Montt is predicted to undergo morphological changes by 2050, shifting from rural areas primarily composed of woods and agricultural land to open, low-density, low-rise areas outside the municipal limits set by the Communal Regulatory Plans. According to this study, Puerto Montt's relative entropy level was high, ranging from 0.87 to 0.96, with a maximum value of 1.00 by 2050. These findings are anticipated to provide planners and decision-makers with further knowledge on the territorial design of upcoming urban areas.