G-SIVAR: A Global Spatial Indicator Based on Variogram

• Autor(a) principal: Naizer, Cláudia Cristina Baptista Ramos
• Data de Publicação: 2019
• Outros Autores: Rodrigues, David Souza, Junior, Jorge Ubirajara Pedreira, Pitombo, Cira Souza
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Boletim de Ciências Geodésicas
• Texto Completo: https://revistas.ufpr.br/bcg/article/view/72044
• topic: Geociências, Ciências da Terra; Spatial association, Moran, Pseudo-significance test, Semivariogram.

Among the exploratory spatial data analysis tools, there are indicators of spatial association, which measure the degree of spatial dependence of analysed data and can be applied to quantitative data. Another procedure available is geostatistics, which is based on the variogram, describing quantitatively and qualitatively the spatial structure of a variable. The aim of this paper is to use the concept of the variogram to develop a global indicator of spatial association (Global Spatial Indicator Based on Variogram – G-SIVAR). The G-SIVAR indicator has a satisfactory performance for spatial association, with sensibility for anisotropy cases. Because the indicator is based on geostatistics, it is appropriate for quantitative and qualitative data. The developed indicator is derived from theoretical global variogram, providing more details of the spatial structure of the data. The G-SIVAR indicator is based on spatial dissimilarity, while traditional indexes, such as Moran’s I, are based on spatial similarity.