“…The constraints of the model include limiting land-use density, land-use variety. Besides, the objective of maximizing the land value around station and the constraint of pollution cost control was also considered in a TOD model built in [26]. The accessibility around the station was taken as an objective in [20].…”
“…The constraints of the model include limiting land-use density, land-use variety. Besides, the objective of maximizing the land value around station and the constraint of pollution cost control was also considered in a TOD model built in [26]. The accessibility around the station was taken as an objective in [20].…”
“…Economic benefit is mainly measured by the unit output or by the conversion cost of each land use [19,20], either by Gross Domestic Product (GDP) allocation or conversion cost, respectively. Within land-use models, economic factors can be evaluated for maximum housing capacity, maximum social equity, and minimum taxes [18,[21][22][23]. Among various ecological factors, Ecosystem Services Value (ESV), namely the value of ecosystem service and natural capital estimated by economic rules, is widely used due to its clear scientific significance and ease of calculation [24][25][26].…”
Practical efficient regional land-use planning requires planners to balance competing uses, regional policies, spatial compatibilities, and priorities across the social, economic, and ecological domains. Genetic algorithm optimization has progressed complex planning, but challenges remain in developing practical alternatives to random initialization, genetic mutations, and to pragmatically balance competing objectives. To meet these practical needs, we developed a Land use Intensity-restricted Multi-objective Spatial Optimization (LIr-MSO) model with more realistic patch size initialization, novel mutation, elite strategies, and objectives balanced via nominalizations and weightings. We tested the model for Dapeng, China where experiments compared comprehensive fitness (across conversion cost, Gross Domestic Product (GDP), ecosystem services value, compactness, and conflict degree) with three contrast experiments, in which changes were separately made in the initialization and mutation. The comprehensive model gave superior fitness compared to the contrast experiments. Iterations progressed rapidly to near-optimality, but final convergence involved much slower parent–offspring mutations. Tradeoffs between conversion cost and compactness were strongest, and conflict degree improved in part as an emergent property of the spatial social connectedness built into our algorithm. Observations of rapid iteration to near-optimality with our model can facilitate interactive simulations, not possible with current models, involving land-use planners and regional managers.
“…Urban railroads, as representative public transportation systems, have played an essential role in forming spatial structures and functional systems during industrialization in the development of the Seoul metropolitan area [1]. As the station area is where the population and logistics are concentrated, transit-oriented development (TOD) planning is implemented in many cities as a strategic tool for sustainable urban planning and management [2,3]. According to TOD planning, well-designed station development areas not only promote the ridership of public transportation among automobile users, but also operate as a center for organizing community development and restoring sluggish urban areas [4][5][6].…”
Transit-oriented development (TOD) pursues sustainable urban development through compact growth, mixed-use zoning, and pedestrian-friendly neighborhood design in cooperation with transportation planning. Seoul has actively developed urban rail transit since the 1970s based on a TOD concept, and each station’s areas have differently evolved throughout the history of urbanization in Seoul. In response to investigating the complications of current TOD, this paper evaluates TOD characteristics through accessibility and clustering analysis methods and categorizes TOD types using the targeted 246 subway station areas at the neighborhood level. As a result, subway TODs are grouped into the four distinct categories of (1) high-density: a form of mainly mixed-use with residential and retail development and good accessibility; (2) moderate-density: average accessibility and high-mixed use; (3) compact business district setting: highly accessible to offices and retail; and (4) compact housing: high-rise apartments with schools and retail. The results also find that Cluster 2 is the most common TOD type and redevelopment possibility in Seoul, with relatively lower ranks in the building floor area (GFA) and diversity in comparison to other TOD contexts. Cluster 3 has the most significant transit demand, generating an active transit environment in Seoul. Different urban development periods impact the characteristics of TOD types.
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