Optimization Method for Land Use of the Xi’an Rail Transit Station Area Based on a Multi-Objective Model

Author:

Tong Haiyan1,Dong Xiao1,Liu Jiaping2

Affiliation:

1. School of Architecture, Chang’an University, Xi’an 710061, China

2. School of Architecture, Xi’an University of Architecture and Technology, Xi’an 710055, China

Abstract

For the intensive, efficient, and sustainable utilization of land resources, it is of great significance to optimize the spatial allocation of different types of land use intensity in rail transit station areas. The current land use optimization model has some shortcomings in objective function, constraint conditions, and the solution process. In response to this, a new multi-objective optimization model for rail transit station land use was built. With station space efficiency as the starting point, the three objectives of the model optimization were the traffic volume, environment quality, and land balance of the rail transit station, and the constraint conditions were the plot ratio, environment quality, and efficiency level. Lingo was used to solve the optimal plot ratio of different types of land use intensity. Compared with the non-inferior solution of the rail transit station area multi-objective original model, the ideal plot ratio of various land uses obtained by the optimized new model was more reasonable. There was a relatively large gap between the non-inferior solutions of some original models and the actual conditions. In contrast, the optimized new model had stronger maneuverability. The deviation ranges of the two models were −0.4% to 0.9% on the residential land plot ratio adjustment index, −3.2% to 4.8% on the public land plot ratio adjustment index, and 1.1% to 1.9% on the commercial land plot ratio adjustment index. This research aimed to provide a basis and reference for the land use and planning of Xi’an rail transit station.

Funder

National Natural Science Foundation of China

Publisher

MDPI AG

Subject

Nature and Landscape Conservation,Ecology,Global and Planetary Change

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