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Two Approaches to Blending Spatial Weights and Temporal Weights in Calculating Spatiotemporal Autocorrelation

机译:计算时空自相关的两种融合空间权重和时间权重的方法

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Since Moran's seminal paper on an index to measure spatial autocorrelation among a set of geographic objects, spatial autocorrelation coefficients have been widely used in many research and application fields. In this paper, we provide detailed reasoning for indices for measuring spatiotemporal autocorrelation. We first briefly highlight the classic Moran's Index for measuring spatial autocorrelation. Next we introduce two methods that we used to blend spatial and temporal weights. Also the simulation experiment was adopted to evaluate the difference between the two methods.
机译:自从Moran在关于测量一组地理对象之间的空间自相关的索引的开创性论文以来,空间自相关系数已在许多研究和应用领域中得到广泛使用。在本文中,我们为测量时空自相关的指标提供了详细的推理方法。我们首先简要介绍用于测量空间自相关的经典Moran指数。接下来,我们介绍两种用于混合空间和时间权重的方法。还通过仿真实验来评估两种方法之间的差异。

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