Please use this identifier to cite or link to this item:
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1161056
Title: | Improving coffee yield interpolation in the presence of outliers using multivariate geostatistics and satellite data. |
Authors: | SILVA, C. de O. F.![]() ![]() GREGO, C. R. ![]() ![]() MANZIONE, R. L. ![]() ![]() OLIVEIRA, S. R. de M. ![]() ![]() |
Affiliation: | CÉSAR DE OLIVEIRA FERREIRA SILVA, UNIVERSIDADE ESTADUAL DE CAMPINAS; CELIA REGINA GREGO, CNPTIA; RODRIGO LILLA MANZIONE, UNIVERSIDADE DE SÃO PAULO; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA, UNIVERSIDADE ESTADUAL DE CAMPINAS. |
Date Issued: | 2024 |
Citation: | AgriEngineering, v. 6, n. 1, p. 81-94, Mar. 2024. |
Description: | 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. |
Thesagro: | Café Coffea Arábica Agricultura de Precisão Sensoriamento Remoto |
NAL Thesaurus: | Precision agriculture Remote sensing Geostatistics |
Keywords: | Cokrigagem Variograma Agricultura digital Dados de satélite Geoestatística Coffee yield Cokriging Variogram Digital agriculture |
ISSN: | 2624-7402 |
DOI: | https://doi.org/10.3390/agriengineering6010006 |
Type of Material: | Artigo de periódico |
Access: | openAccess |
Appears in Collections: | Artigo em periódico indexado (CNPTIA)![]() ![]() |
Files in This Item:
File | Description | Size | Format | |
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AP-Improving-coffee-2024.pdf | 3.83 MB | Adobe PDF | ![]() View/Open |