内嵌空间聚类算法的分区地理元胞自动机建模与应用

Partitioned Geo-Cellular Automata Modelling Embedded Spatial Cluster Algorithm

传统的地理元胞自动机(Geo-Cellular Automata;GeoCA)模型,大多采用统一的转换规则驱动元胞空间内的所有元胞进行演变。然而,许多地理现象都存在着空间异质性,统一的元胞转换规则忽略了空间异质性的存在。针对这一问题,本文提出了空间聚类的分区地理元胞自动机模型,采用空间聚类算法对元胞空间进行分区,对不同的分区分别求取转换规则,以此来提高地理元胞自动机的模拟精度。以杭州市为案例区,采用本文提出的空间聚类的分区地理元胞自动机模型,对研究区2000-2005年的城市用地变化进行了模拟。结果表明:与采用统一转换规则的GeoCA相比,引入空间聚类算法的分区GeoCA具有较高的模拟精度,尤其是在空间形态和整体结构上,具有较好的模拟效果。

All cells under the unpartitioned geo-cellular automata（GeoCA） modeling evolved according the transfer probability which is decided by generic transfer rule fixed for the entire region.However,there always exists spatial heterogeneity in most geographical phenomenon,and these spatial heterogeneities are quite often ignored in generic unpartitioned geo-cellular automata modeling due to the generic transfer rules are employed to drive all cells to evolve.The accuracy of unpartitioned GeoCA simulation result is limited because of the ignorance of spatial heterogeneities in this kind of GeoCA models.To overcome this disadvantage of unpartitioned GeoCA,a partitioned GeoCA based on spatial cluster is discussed in this paper.Under the partitioned GeoCA modeling framework,cellular space is departed into several partitions by spatial cluster,and then a set of transfer rules corresponding to each partition are calculated accordingly.And then,taking Hangzhou City as a case,the Partitioned GeoCA modeling based on spatial cluster is employed to simulate the land use change in the period between 2000 and 2005.In this case study,the study area of Hanzhou is divided into 5 partitions by using K-Means cluster algorithm,and then C5.0 decision tree is employed to obtain cellular transfer rules for each partition of the case study area.In each partition,corresponding cellular transfer rules are employed to drive GeoCA to run simulation.Finally,confusion matrix and Moran I index are calculated to evaluate accuracy of simulated results by using the GeoCA modelling.Results show that the accuracy of the partitioned GeoCA modeling approach owns a higher simulation accuracy compared with those simulated based on unpartitioned GeoCA simulation.On the other hand,when Moran I index is employed to evaluate the accuracy of simulation result,the result of partitioned GeoCA modeling embedded spatial cluster is closer to the real land use pattern.The empirical study shows that a more accurate simulation result can be achieved by using the partitioned GeoCA modeling embedded spatial cluster.