Publicação
Discovering spatio-temporal patterns in precision agriculture based on triclustering
| Resumo: | Agriculture has undergone some very important changes over the last few decades. The emergence and evolution of precision agriculture has allowed to move from the uniform site management to the site-specific management, with both economic and environmental advantages. However, to be implemented effectively, site-specific management requires within-field spatial variability to be well-known and characterized. In this paper, an algorithm that delineates within-field management zones in a maize plantation is introduced. The algorithm, based on triclustering, mines clusters from temporal remote sensing data. Data from maize crops in Alentejo, Portugal, have been used to assess the suitability of applying triclustering to discover patterns over time, that may eventually help farmers to improve their harvests. |
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| Autores principais: | Melgar-Garcia, Laura |
| Outros Autores: | Godinho, Teresa; Espada, Rita; Gutíerrez-Avilés, David; Martínez-Alvarez, Francisco; Trancoso, Alicia; Rubio-Escudero, Cristina; Brito, Isabel |
| Assunto: | Triclustering Spatio-temporal patterns Precision agriculture Remote sensing |
| Ano: | 2020 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico de Beja |
| Idioma: | inglês |
| Origem: | Repositório Institucional do IPBeja |
| Resumo: | Agriculture has undergone some very important changes over the last few decades. The emergence and evolution of precision agriculture has allowed to move from the uniform site management to the site-specific management, with both economic and environmental advantages. However, to be implemented effectively, site-specific management requires within-field spatial variability to be well-known and characterized. In this paper, an algorithm that delineates within-field management zones in a maize plantation is introduced. The algorithm, based on triclustering, mines clusters from temporal remote sensing data. Data from maize crops in Alentejo, Portugal, have been used to assess the suitability of applying triclustering to discover patterns over time, that may eventually help farmers to improve their harvests. |
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