The Test Base On Monte Carlo Simulation For Spatial Autocorrelation

Spatial statistic had been researched since several decades ago in the oversea, but it is a new field in China. Recently the national scholar makes great progress in applying spatial statistic.As an important part of GIS, with GIS development, the scholars pay attention to spatial statistic. This paper analyzes original method and spatial statistic method by Monte Carlo simulation. Comparing two methods to draw following conclusions: (1) Two methods will get the different results without random error influencing, when we test Normal distribution data. Further, considering random error influencing, we will get the similar test result, in the result that random error have no influence.(2 ) Two methods will get the different results without random error influencing, when we test Random distribution data. Further, considering random error influencing, we will get the same Morans'I and the similar test result, in the result that random error have no influence.(3 ) Two methods will get the different results without random error influencing, when we test Poisson distribution data. Further, considering random error influencing, we will get the same Morans'I and the similar test result, in the result that random error have no influence.It is found that statistic test and spatial statistic test gain different results by this studying. It proves that test spatial autocorrelation will gain falsehood result by statistic test, because there is correlation between spatial data, which can't satisfy with statistic hypotheses, thus, it is necessary to analyze correlation between spatial data, when building spatial model.