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.
| Autores: | , , , |
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| 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 |
| 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. |
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