A robust estimator and the cross semi-variogram in spatial variability analysis of soil and plants attributes
The knowledge of the soil attributes spatial variability that influence crop yield is essential for precision agriculture. If the behavior of these attributes presents spatial dependence, then it is recommended to use geostatistics to describe this spatial structure and to estimate values in non sam...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2008 |
| País: | Brasil |
| Institución: | Universidade Estadual de Maringá (UEM) |
| Repositorio: | Acta Scientiarum. Agronomy (Online) |
| Idioma: | portugués |
| OAI Identifier: | oai:periodicos.uem.br/ojs:article/1984 |
| Acceso en línea: | http://www.periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/1984 |
| Access Level: | acceso abierto |
| Palabra clave: | agricultura de precisão semivariograma estimador robusto 5.00.00.00-4 Ciências Agrárias |
| Sumario: | The knowledge of the soil attributes spatial variability that influence crop yield is essential for precision agriculture. If the behavior of these attributes presents spatial dependence, then it is recommended to use geostatistics to describe this spatial structure and to estimate values in non sampled places. In order to have good estimates, unbiased, precise and robust estimators are necessary. Many studies use the classic estimator of Matheron, however, the use of a robust estimator is recommended to data with long tail or asymmetrical distribution. The objectives of this study were to use Cressie and Hawkins’ estimator to generate experimental semi-variograms of Phosphorus, Potassium and soybean yield in an experimental agricultural area, to produce their contour maps and to correlate them through crossed semi-variogram. This experiment resulted in maps that illustrate the spatial variability of the variables and their correlations, used as a management tool or documentation in a modern agricultural practice. |
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