We present a multilevel modeling framework for simulating the emergence of landscape spatial structure in urbanizing regions using a combination of field-based and object-based representations of land change. The FUTure Urban-Regional Environment Simulation (FUTURES) produces regional projections of landscape patterns using coupled submodels that integrate nonstationary drivers of land change: per capita demand, site suitability, and the spatial structure of conversion events. Patches of land change events are simulated as discrete spatial objects using a stochastic region-growing algorithm that aggregates cell-level transitions based on empirical estimation of parameters that control the size, shape, and dispersion of patch growth. At each time step, newly constructed patches reciprocally influence further growth, which agglomerates over time to produce patterns of urban form and landscape fragmentation. Multilevel structure in each submodel allows drivers of land change to vary in space (e.g., by jurisdiction), rather than assuming spatial stationarity across a heterogeneous region. We applied FUTURES to simulate land development dynamics in the rapidly expanding metropolitan region of Charlotte, North Carolina, between 1996 and 2030, and evaluated spatial variation in model outcomes along an urban–rural continuum, including assessments of cell- and patch-based correctness and error. Simulation experiments reveal that changes in per capita land consumption and parameters controlling the distribution of development affect the emergent spatial structure of forests and farmlands with unique and sometimes counterintuitive outcomes.

Land that is of great value for conservation can also be highly suitable for human use, resulting in competition between urban development and the protection of natural resources. To assess the effectiveness of proposed regional land conservation strategies in the context of rapid urbanization, we measured the impacts of simulated development patterns on two distinct conservation goals: protecting priority natural resources and limiting landscape fragmentation. Using a stochastic, patch-based land change model (FUTURES) we projected urbanization in the North Carolina Piedmont according to status quo trends and several conservation-planning strategies, including constraints on the spatial distribution of development, encouraging infill, and increasing development density. This approach allows simulation of population-driven land consumption without excluding the possibility of development, even in areas of high conservation value. We found that if current trends continue, new development will consume 11% of priority resource lands, 21% of forested land, and 14% of farmlands regionally by 2032. We also found that no single conservation strategy was optimal for achieving both conservation goals. For example, strategies that excluded development from priority areas caused increased fragmentation of forests and farmlands, while infill strategies increased loss of priority resources proximal to urban areas. Exploration of these land change scenarios not only confirmed that a failure to act is likely to result in irreconcilable losses to a conservation network, but that all conservation plans are not equivalent in effect, highlighting the importance of analyzing tradeoffs between alternative conservation planning approaches