Modeling landowner interactions and development patterns at the urban fringe

Projecting Urbanization and Landscape Change at Large Scale Using the FUTURES Model

“…For example, reluctance to sell or develop in certain areas due to local factors is captured through the stochastic patch growing algorithm. While the social components of urban growth are considerably more complex at local scales compared to the stochastic processes simulated with the patch growing algorithm, the difficulty of efficiently capturing these key drivers across large extents necessitates a generalized approach [18].…”

“…Traditionally, land change for large regions has been done using cellular automata (CA) models (e.g., CLUE, SLEUTH) with simplified inputs that can be obtained for large extents and using simple geographic rules that are broadly applicable [8,15]. Agent-based models that include high levels of model complexity, however, are often better at mimicking local processes by incorporating behavioral drivers [18], resulting in increased local pattern simulation accuracy. The computational demands (local agent decisions) and data requirements (local model of behavior), however, means that it is rarely practical to use ABMs for simulating urbanization for large regions.…”

“…[8,15]. While agent-based modeling (ABM) frameworks incorporate social factors that may more closely approximate local conditions and resulting patterns of change, their implementation is rarely possible at large, regional to continental extents [18,19] due to empirical and computational requirements of incorporating behavioral drivers of land change [20].…”

Effects of Changing Scales on Landscape Patterns and Spatial Modeling Under Urbanization

“…The main reason for these was that a large amount of cultivated land was transformed to construction land, creating a more fragmented landscape in the and AI (aggregation index) at the whole region scale block. The fragmentation in the urban-rural fringe areas caused by urbanization were also found in other areas, like Xi'an (Hou et al, 2020), Beijing , North America (Koch et al, 2019), and Leiria City (Barros et al, 2018). The evolutionary characteristics of the ED and SHDI in space from 1995 to 2010 coincided with PD.…”

Integrated urban mobility policies in metropolitan areas: A system dynamics approach for the Rhine-Ruhr metropolitan region in Germany

“…This phenomenon-referred to as urban sprawl-remains a complex and elusive concept (Galster et al, 2001). However, key attributes of urban sprawl include J o u r n a l P r e -p r o o f extension of the city area beyond walkable range (Rahman, 2016), a decline in urban densities (Ewing et al, 2016), increased consumption of land resources by urban dwellers (Huang et al, 2010), ongoing suburbanisation (Koch et al, 2019) and fragmentation of open spaces as well as built-up areas (Oueslati et al 2015;Dorning et al, 2014). Numerous studies have identified the primary factors that drive urban sprawl, including a rise in household incomes, individual preferences, technological progress in the automobile industry, affordability of vehicles and a decline in commuting costs (Deng et al, 2008;Patacchini and Zenou, 2009; Seto, 2011; Oueslati et al, 2015).…”