Use este identificador para citar ou linkar para este item: http://repositorio.ufla.br/jspui/handle/1/48335
Título: Geostatistical-based index for spatial variability in soil properties
Palavras-chave: Within-field variability
Spatial dependence
Autocorrelation
Semivariogram
Variabilidade espacial
Dependência espacial
Autocorrelação
Semivariograma
Propriedades do solo
Data do documento: Set-2020
Editor: Sociedade Brasileira de Ciência do Solo / Universidade Federal de Viçosa
Citação: APPEL NETO, E.; SEIDEL, E. J.; OLIVEIRA, M. S. de. Geostatistical-based index for spatial variability in soil properties. Revista Brasileira de Ciência do Solo, Viçosa, MG, v. 44, e0200086, 2020. DOI: https://doi.org/10.36783/18069657rbcs20200086.
Resumo: The assessment of spatial variability of environmental variables such as soil properties is important for site-specific management. A geostatistical index that allows quantifying and characterizing the structure of spatial variability is fundamental in this context. Thus, this study aimed to develop a new spatial dependency index, called the Spatial Dependence Measure (SDM) for the spherical, exponential, Gaussian, cubic, pentaspherical, and wave semivariogram models; and comparing it with some of the indexes available in the literature. The SDM is also dimensionless, in the same way as the Spatial Dependence Index (SDI), also considering more parameters of the semivariogram, when compared to the Spatial Dependence Degree (SPD) and Relative Nugget Effect (NE) indexes. In a simulation data study, it is observed that the SDI and SDM indexes showed an advantage over the SPD (or NE). To exemplify the application of the SDM in the proposal for the classification of soil properties, we used estimates of geostatistical parameters presented in the two studies. The results indicate that the SDM can be a measure that, analyzed together with the SDI, can help to improve the description of the spatial variability structure. Thus, this study expands the number of geostatisitcal-based measures and increases the power of decision on the description of the degree of spatial variability of agricultural and soil attributes.
URI: http://repositorio.ufla.br/jspui/handle/1/48335
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