Improving coffee yield interpolation in the presence of outliers using multivariate geostatistics and satellite data.

the objective of this study was to evaluate the use of remotely sensed data as auxiliary variables in the block cokriging (BCOK) modeling of coffee yield characterized by the presence of outliers.

Detalles Bibliográficos
Autores: SILVA, C. de O. F., GREGO, C. R., MANZIONE, R. L., OLIVEIRA, S. R. de M.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:Brasil
Institución:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
Repositorio:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Idioma:inglés
OAI Identifier:oai:www.alice.cnptia.embrapa.br:doc/1161056
Acceso en línea:http://www.alice.cnptia.embrapa.br/alice/handle/doc/1161056
https://doi.org/10.3390/agriengineering6010006
Access Level:acceso abierto
Palabra clave:Cokrigagem
Variograma
Agricultura digital
Dados de satélite
Geoestatística
Coffee yield
Cokriging
Variogram
Digital agriculture
Café
Coffea Arábica
Agricultura de Precisão
Sensoriamento Remoto
Precision agriculture
Remote sensing
Geostatistics
Descripción
Sumario:the objective of this study was to evaluate the use of remotely sensed data as auxiliary variables in the block cokriging (BCOK) modeling of coffee yield characterized by the presence of outliers.