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基于改进logistic-CA的城市形态多情景模拟预测分析——以天津滨海地区为例 被引量:13

A Method of Simulation and Prediction of Urban Morphology under Multiscenarios
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摘要 logistic-CA模型在城市分析应用中,发挥了重要作用,但该模型仅能模拟历史演化趋势下的城市形态演化,无法准确模拟既定年份的城市面积,更无法模拟预测多情景城市形态演化。因此,本文对logistic-CA模型进行了改进:一是嵌入了灰色不等时距预测模型;二是增加不同情景中驱动力的logistic回归系数计算方法。改进后的lo-gistic-CA模型,具备了模拟多情景城市形态演化的能力,模拟预测了天津市滨海地区2011-2020年3种情景的城市形态的演化空间过程特征,即历史外推、内生发展、外生发展3种情景。从而掌握城市形态扩展的必然性、可能性、特定区域的空间扩展影响因素,实现对城市发展过程的有效控制。 As one type of CA, logistic-CA now has been successfully adopted in urban studies. But logistic-CA model can only be applied to simulation according to historical evolution trend. Besides, the quantity of prediction in a certain year cannot be correctly obtained. In this study, we have carded out two modifications on the togistic-CA model, one is to insert grey prediction; the other is making the model capable of simulating urban mor- phology evolution under multi-scenarios. Then we applied this model to simulate and predict urban morphology evolution of the coastal area in Tianjin Municipality, in order to investigate the regularity and characteristics un- der three scenarios, e.g. historical extrapolation, endogenous development and exogenous development, so as to better grasp urban morphology evolution regularities. The simulation of three scenarios shows that urban mor- phology inevitably grows followed a cross form, but the characteristic of three scenarios are a lots of differences. Modified logistic-CA model gives full play to the advantage of CA, that is, bottom-up simulation of urban spatial process under multi-scenarios. Through examination, the modified model has a high accuracy in simulation and prediction, which achieves the goal of quantitative simulation and prediction of urban morphology evolution un- der multi-scenarios. It is necessary for urban planning to master the expansion of the inevitability of urban form, in order to grasp the possibility of a specific area to achieve effective control of the urban development process.
出处 《地球信息科学学报》 CSCD 北大核心 2013年第3期380-388,共9页 Journal of Geo-information Science
基金 国家自然科学基金项目(1278330)
关键词 logistic-CA 多情景 城市形态 模拟 预测 logistic-CA multi-scenarios urban morphology simulation prediction
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