ScholarGate
助手

方法对比

并排查看您选择的方法;存在差异的行会高亮显示。

时空盖瑞C指数×时空莫兰指数×
领域空间分析空间分析
方法族Regression modelRegression model
起源年份1954 / 2010s1981
提出者Geary (1954); extended to space-time by Anselin and othersCliff & Ord (extended to space-time domain)
类型Spatial autocorrelation statisticSpatial autocorrelation statistic
开创性文献Geary, R. C. (1954). The Contiguity Ratio and Statistical Mapping. The Incorporated Statistician, 5(3), 115-145. DOI ↗Cliff, A. D., & Ord, J. K. (1981). Spatial Processes: Models and Applications. Pion. ISBN: 978-0850860818
别名ST-Geary's C, spatiotemporal Geary C, space-time contiguity ratio, space-time local spatial autocorrelationspace-time autocorrelation index, ST Moran's I, spatiotemporal Moran's I, space-time I statistic
相关65
摘要Space-Time Geary's C extends the classical Geary contiguity ratio to panel or longitudinal spatial data, measuring autocorrelation across both geographic neighbors and adjacent time periods simultaneously. Values below 1 indicate positive space-time clustering; values above 1 indicate dispersion, and a value near 1 suggests random arrangement across the space-time lattice.Space-Time Moran's I extends the classic Moran's I statistic into the spatiotemporal domain, measuring whether observations that are close in both space and time tend to be more similar than those that are distant. It detects clustering, dispersion, or randomness across a combined space-time weight matrix, making it a foundational tool in epidemiology, criminology, and environmental monitoring.
ScholarGate数据集
  1. v1
  2. 2 来源
  3. PUBLISHED
  1. v1
  2. 2 来源
  3. PUBLISHED

前往搜索 下载幻灯片

ScholarGate方法对比: Space-Time Geary's C · Space-Time Moran's I. 于 2026-06-19 检索自 https://scholargate.app/zh/compare