Urban expansion simulation from the perspective of land acquisition-based on bargaining model and ant colony optimization

Abstract

As a major method to serve the demand for land requirement in Chinese urban construction, land acquisition has been intensified since the speeding up of urbanization. However, clashes arise during the process of land acquisition, out of conflicts of interests, which to some extent have affected the development and direction of urban expansion, as well as social harmony and stability. Therefore, the urban expansion simulation should be based on smooth land acquisition technique. In this study, urban expansion was simulated from the perspective of land acquisition, based on coupled bargaining model and modified ant colony optimization (ACO) algorithm. First, the bargaining model with fairness preferences should be set up for the government and farmers, to search for the candidate areas for urban expansion, both sides of which could reach a consensus without conflicts of interest. Then, urban expansion simulation is applied to all the candidate areas, taking advantage of the modified ACO algorithm. The model considered the built-up area in Wuhan city as the demonstration area and simulated conditions of land use in 2016 and 2026. The result showed that the coupled model could simulate decision-making behavior of the government and farmers in land acquisition veritably, so as to protect farmers' economic interests, with an increase of over 50% on average, and ensure government's appropriate profit. Moreover, the simulation accuracies of the coupled model was found to be better than that of the traditional cellular automata model, and the Kappa coefficient was 0.65, which supports the effectiveness of the model in simulating urban expansion. Further, it was estimated that the urban land use of Wuhan will cover 516.22 km2 in 2026, and the southeastern part of the city will be the hot spot area of urban expansion.