Directional Differences in Thematic Maps of Soil Chemical Attributes with Geometric Anisotropy

Dyogo Lesniewski Ribeiro, Tamara Cantú Maltauro (), Luciana Pagliosa Carvalho Guedes, Miguel Angel Uribe-Opazo () and Gustavo Henrique Dalposso
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Dyogo Lesniewski Ribeiro: Engineering, Mathematics and Technology Department, Western Paraná State University, UNIOESTE, Cascavel 85819-110, Brazil
Tamara Cantú Maltauro: Engineering, Mathematics and Technology Department, Western Paraná State University, UNIOESTE, Cascavel 85819-110, Brazil
Luciana Pagliosa Carvalho Guedes: Engineering, Mathematics and Technology Department, Western Paraná State University, UNIOESTE, Cascavel 85819-110, Brazil
Miguel Angel Uribe-Opazo: Engineering, Mathematics and Technology Department, Western Paraná State University, UNIOESTE, Cascavel 85819-110, Brazil
Gustavo Henrique Dalposso: PPGBIO—Programa de Pós-Graduação em Tecnologias em Biociências, Federal Technological University of Paraná, UTFPR, Toledo 85902-490, Brazil

Stats, 2024, vol. 7, issue 1, 1-14

Abstract: In the study of the spatial variability of soil chemical attributes, the process is considered anisotropic when the spatial dependence structure differs in relation to the direction. Anisotropy is a characteristic that influences the accuracy of the thematic maps that represent the spatial variability of the phenomenon. Therefore, the linear anisotropic Gaussian spatial model is important for spatial data that present anisotropy, and incorporating this as an intrinsic characteristic of the process that describes the spatial dependence structure improves the accuracy of the spatial estimation of the values of a georeferenced variable in unsampled locations. This work aimed at quantifying the directional differences existing in the thematic map of georeferenced variables when incorporating or not incorporating anisotropy into the spatial dependence structure through directional spatial autocorrelation. For simulated data and soil chemical properties (carbon, calcium and potassium), the Moran directional index was calculated, considering the predicted values at unsampled locations, and taking into account estimated isotropic and anisotropic geostatistical models. The directional spatial autocorrelation was effective in evidencing the directional difference between thematic maps elaborated with estimated isotropic and anisotropic geostatistical models. This measure evidenced the existence of an elliptical format of the subregions presented by thematic maps in the direction of anisotropy that indicated a greater spatial continuity for greater distances between pairs of points.

Keywords: directional spatial autocorrelation; geostatistic; simulation (search for similar items in EconPapers)
JEL-codes: C1 C10 C11 C14 C15 C16 (search for similar items in EconPapers)
Date: 2024
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