论文部分内容阅读
元胞自动机近年来被广泛应用于动态模拟城市扩张,但其邻域类型一般固定于摩尔邻域。文章基于Geo-CA理论,自定义扩展邻域类型,并结合特定地理位置多层次约束性条件构建CA模型,扩展了CA模型的空间建模功能。以武汉市为例,将2000年和2009年TM遥感影像和城市用地数据作为基础,结合武汉市城市规划图、DEM、道路交通图、水域等多层次图像,构成空间数据库,建立武汉市城市扩张扩展邻域CA模型。最后以2009年数据为基础,对武汉市2018年城市用地扩张情况进行预测,为武汉市城镇建设提供参考。
Cellular automata have been widely used in recent years to simulate urban expansion dynamically, but their neighborhood types are generally fixed in the molar neighborhood. Based on the theory of Geo-CA, the article defines the extended neighborhood type and constructs the CA model based on the multi-level binding conditions of specific geographical locations, expanding the spatial modeling function of the CA model. Taking Wuhan as an example, based on TM remote sensing images of 2000 and 2009 and urban land use data, a spatial database was constructed based on multi-level images of Wuhan city planning map, DEM, road traffic map and water area to establish Wuhan city expansion Extended neighborhood CA model. Finally, based on the data of 2009, this paper predicts the expansion of urban land in Wuhan in 2018, providing a reference for the urban construction in Wuhan.