Please use this identifier to cite or link to this item:
acessibilidade
http://hdl.handle.net/20.500.12207/6015
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Melgar-Garcia, Laura | - |
dc.contributor.author | Godinho, Maria Teresa | - |
dc.contributor.author | Espada, Rita | - |
dc.contributor.author | Gutiérrez-Avilés, David | - |
dc.contributor.author | Martínez-Álvarez, Francisco | - |
dc.contributor.author | Troncoso, Alicia | - |
dc.contributor.author | Rubio-Escudero, Cristina | - |
dc.contributor.author | Brito, Isabel Sofia | por |
dc.date.accessioned | 2023-11-04T02:46:08Z | - |
dc.date.available | 2023-11-04T02:46:08Z | - |
dc.date.issued | 2020-08 | - |
dc.identifier.citation | Melgar-García L., Godinho, M., Rita, E., Gutiérrez-Avilés, D., Brito, I., Martínez-Álvarez, F., Troncoso, A., Rubio-Escudero, C. (2021) Discovering Spatio-Temporal Patterns in Precision Agriculture Based on Triclustering. In: Herrero Á., Cambra C., Urda D., Sedano J., Quintián H., Corchado E. (eds) 15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020). SOCO 2020. Advances in Intelligent Systems and Computing, vol 1268. Springer, https://doi.org/10.1007/978-3-030-57802-2_22 | por |
dc.identifier.isbn | 978-3-030-57801-5 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.12207/6015 | - |
dc.description.abstract | 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 frommaize 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. | por |
dc.language.iso | eng | por |
dc.publisher | Springer | por |
dc.relation | Fundação para a Ciência e a Tecnologia (FCT), under the project UIDB/04561/2020 | por |
dc.relation | Spanish Ministry of Economy and Competitiveness for the support under project TIN2017-88209 | por |
dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04561%2F2020/PT | por |
dc.relation.ispartof | Advances in Intelligent Systems and Computing book series (AISC, volume 1268) | por |
dc.rights | openAccess | por |
dc.rights.uri | http://creativecommons.org/licenses/by-sa/4.0/ | por |
dc.subject | Triclustering | por |
dc.subject | Spatio-temporal patterns | por |
dc.subject | Precision agriculture | por |
dc.subject | Remote sensing | por |
dc.subject | Agricultura de precisão | por |
dc.subject | Sensoriamento remoto | por |
dc.title | Discovering spatio-temporal patterns in precision agriculture based on triclustering | por |
dc.type | article | por |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | https://link.springer.com/chapter/10.1007/978-3-030-57802-2_22 | por |
degois.publication.firstPage | 226 | por |
degois.publication.lastPage | 236 | por |
degois.publication.title | SOCO 2020: 15th International Conference on Soft Computing Models in Industrial and Environmental Applications | por |
dc.identifier.doi | https://doi.org/10.1007/978-3-030-57802-2_22 | por |
Appears in Collections: | D-MCF - Artigos em revistas indexadas à WoS/Scopus |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Advances in intelligent systems and computing.pdf | 695.47 kB | Adobe PDF | View/Open | |
Capa_FichaTecnica.pdf | 312.66 kB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License