Methodology to determine the soil sampling grid for precision agriculture in a coffee field

The objective of this study was to develop and propose a methodology to evaluate the quality of different sampling grids. In addition, it allows us to choose the sampling grid that better suits one or a set of variables. The structure and magnitude of the spatial dependence were characterized by sem...

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Autores:
Ferraz, Gabriel Araújo e Silva
De Oliviera, Marcelo Silva
Da Silva, Fábio Moreira
Avelar, Rogner Carvalho
Da Silva, Flávio Castro
Ferraz, Patricia Ferreira Ponciano
Tipo de recurso:
Article of journal
Fecha de publicación:
2017
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/60420
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/60420
http://bdigital.unal.edu.co/58752/
Palabra clave:
62 Ingeniería y operaciones afines / Engineering
Geostatistics
spatial variability
soil fertility
accuracy index
precision index
optimum grid indicator
geoestadística
variabilidad espacial
fertilidad del suelo
índice de exactitude
índice de precisión
indicador de cuadricula óptima
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
Description
Summary:The objective of this study was to develop and propose a methodology to evaluate the quality of different sampling grids. In addition, it allows us to choose the sampling grid that better suits one or a set of variables. The structure and magnitude of the spatial dependence were characterized by semivariogram. It allowed us to apply validation techniques that worked as a base to create an index to evaluate the grid quality and to develop an indicator that points out the best sampling grid. To test the proposed methodology, an experiment was performed at the Brejão farm, in Brazil. We have developed and compared twenty sampling grids, which were applied to four soil variables sampled in georeferenced locations. An accuracy index (AI), a precision index (PI) and the optimum grid indicator (OGI) were developed and proposed, which allowed us to choose the best grid among the sampling grids.