ArticlePloS one2021
An analytical process of spatial autocorrelation functions based on Moran's index.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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39 citing papers in PubMed.
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- Geospatial Distribution of Tuberculosis Incidence and Determinants of Tuberculosis Treatment Outcomes in Nzema East Municipality, Ghana.Public health challenges · 2025Article
- Study on the driving mechanisms of spatiotemporal nonstationarity of vegetation dynamics in Heilongjiang Province.Scientific reports · 2025Article
- Prevalence and Spatial distribution characteristics of human echinococcosis in Ningxia Hui Autonomous Region, 2011-2023.BMC public health · 2025Article
- Spatiotemporal evolution and driving factors of eco-environmental quality in the Beijing-Tianjin-Hebei urban agglomeration in China.Scientific reports · 2025Article
- Spatial and temporal distribution patterns and factors influencing hepatitis B in China: a geo-epidemiological study.BMC public health · 2025Article
- Machine Learning and Spatio Temporal Analysis for Assessing Ecological Impacts of the Billion Tree Afforestation Project.Ecology and evolution · 2025Article
- Spatio-temporal evolution and convergence patterns of E-commerce development in China: Regional disparities and policy implications.PloS one · 2025Article
- Spatiotemporal analysis of pulmonary tuberculosis in the central region of the Zhejiang Province, China (2016-2024).Frontiers in public health · 2025Article
- Spatial patterns of childhood obesity clusters linked to socioeconomic inequalities.Frontiers in public health · 2025Article
- Urban resilience assessment framework and spatiotemporal dynamics in Hubei, China.Scientific reports · 2024Article
- Analysis of Trends and Influencing Factors of Cytokine-Adsorbing Therapies: A Nationwide Ecological Study in Japan.Cureus · 2024Article
- Spatiotemporal evolution and development path of healthcare services supply in China.BMC health services research · 2024Article
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Abstract
A number of spatial statistic measurements such as Moran's I and Geary's C can be used for spatial autocorrelation analysis. Spatial autocorrelation modeling proceeded from the 1-dimension autocorrelation of time series analysis, with time lag replaced by spatial weights so that the autocorrelation functions degenerated to autocorrelation coefficients. This paper develops 2-dimensional spatial autocorrelation functions based on the Moran index using the relative staircase function as a weight function to yield a spatial weight matrix with a displacement parameter. The displacement bears analogy with the time lag in time series analysis. Based on the spatial displacement parameter, two types of spatial autocorrelation functions are constructed for 2-dimensional spatial analysis. Then the partial spatial autocorrelation functions are derived by using the Yule-Walker recursive equation. The spatial autocorrelation functions are generalized to the autocorrelation functions based on Geary's coefficient and Getis' index. As an example, the new analytical framework was applied to the spatial autocorrelation modeling of Chinese cities. A conclusion can be reached that it is an effective method to build an autocorrelation function based on the relative step function. The spatial autocorrelation functions can be employed to reveal deep geographical information and perform spatial dynamic analysis, and lay the foundation for the scaling analysis of spatial correlation.
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