摘要：City growth and changes in land-use patterns cause various important social and environmental impacts. To understand the spatial and temporal dynamics of these processes, the factors that drive urban development must be identified and analyzed, especially those factors that can be used to predict future changes and their potential environmental effects. Our objectives were to quantify the relationship between urban growth and its driving forces and to predict the spatial growth pattern based on historical land-use changes for the city of Los Ángeles in central Chile. This involved the analysis of images from 1978, 1992, and 1998 and characterization of the spatial pattern of land-use change; the construction of digital coverage in GIS; the selection of predictive variables through univariate analysis; the construction of logistic regression models using growth vs. nongrowth for 1978–1992 as the dependent variable; and the prediction of the probability of land-use change by applying the regression model to the 1992–1998 period. To investigate the influence of spatial scale, we constructed several sets of models that contained (1) only distance variables, e.g., distance to highways; (2) only scale-dependent density variables, e.g., density of urban area within a 600-m radius; (3) both distance and density variables; and (4) both distance and density variables at several spatial scales. The environmental variables were included in all models. The combination of distance and density variables at several scales is required to appropriately capture the multiscale urban growth process. The best models correctly predict ~90% of the observed land-use changes for 1992–1998. The distance to access roads, densities of the urban road system and urbanized area at various scales, and soil type were the strongest predictors of the growth pattern. Other variables were less important or not significant in explaining the urban growth process. Our approach, which combines spatial modeling tools and GIS, significantly advances the understanding of urban growth patterns, provides an important contribution to urban planning and management, and can be applied widely.
