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| 1. |  | DEL CAMPO, M.; VIÑOLES, C.; SILVA, J.; LISBOA, J.; AMOZA, S.; SOARES DE LIMA, J.M. Bienestar animal: evaluación de estrés en terneros al momento del destete definitivo, con y sin el uso de técnicas de pre-acondicionamiento desde edades tempranas. In: AUPA, Proceedings del VII Congreso Uruguayo de Producción Animal. Sección Una Sola Salud (Single Health Section), 14 y 15 diciembre 2021. Archivos Latinoamericanos de Producción Animal, 29(Supl.1), p.111-113. (Archivos Latinoamericanos de Producción Animal, Vol.29, Supl.1) Corresponding author: M. del Campo, Instituto Nacional de Investigación Agropecuaria (INIA), Tacuarembó, Ruta 5 km 386 (Uruguay), mailto:mdelcampo@inia.org.uy| Biblioteca(s): INIA Las Brujas. |
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 | Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
28/10/2024 |
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Actualizado : |
28/10/2024 |
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Tipo de producción científica : |
Artículos Indexados |
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Autor : |
LENA, H.; CAL, A.; PRECIOZZI, J. |
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Afiliación : |
HORACIO LENA, Universidad de la República, Facultad de Ingeniería, Facultad de Ciencias Sociales, Uruguay; ADRIAN TABARE CAL ALVAREZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JAVIER PRECIOZZI, Universidad de la República, Facultad de Ingeniería Digital Sense, Uruguay. |
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Título : |
Sentinel-2 analysis for classification of winter crops in Uruguay. [Conference paper]. |
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Fecha de publicación : |
2024 |
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Fuente / Imprenta : |
IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024, pp.4819-4823. https://doi.org/10.1109/IGARSS53475.2024.10641161 |
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ISBN : |
979-835036032-5 |
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Idioma : |
Inglés |
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Notas : |
Correspondence: Lena, H.; Universidad de la República, Facultad de Ingeniería, Facultad de Ciencias Sociales, Uruguay; email:horacio.lena@cienciassociales.edu.uy -- Publisher: Institute of Electrical and Electronics Engineers Inc. -- Sponsors: The Institute of Electrical and Electronics Engineers, Geoscience and Remote Sensing Society (GRSS). -- |
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Contenido : |
ABSTRACT.- Crop type classification with satellite imageries is widely applied to support sustainable agricultural practices and for continuous crop monitoring [1], [2], [3]. In this work, we present a study for the classification of winter crops on a nationwide perspective for Uruguay. We have analyzed Uruguay's three most widely extended winter crops: wheat, barley, and rapeseed. We have trained a classifier based on XGBoost that uses temporal series built from Sentinel-2 image data. For training, we used the information from previous years and reported the results the following year. To our knowledge, this is the first work that proposes a clear and systematic way to classify winter crops in Uruguay based on historical data without needing samples of the actual year. We have obtained high precision and recall values for rapeseed and results comparable with other regions' work for wheat and barley. © 2024 IEEE. |
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Palabras claves : |
Crop classification; Decent work and economic growth - Goal 8; Remote sensing; Responsible consumption and production - Goal 12; SISTEMAS DE INFORMACIÓN Y TRANSFORMACIÓN DIGITAL - INIA; Sustainable Development Goals (SDGs); XGBoost; Zero hunger - Goal 2. |
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Asunto categoría : |
P40 Meteorología y climatología |
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Marc : |
LEADER 02234nam a2200253 a 4500
001 1064899
005 2024-10-28
008 2024 bl uuuu u01u1 u #d
020 $a979-835036032-5
100 1 $aLENA, H.
245 $aSentinel-2 analysis for classification of winter crops in Uruguay. [Conference paper].$h[electronic resource]
260 $aIGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024, pp.4819-4823. https://doi.org/10.1109/IGARSS53475.2024.10641161$c2024
500 $aCorrespondence: Lena, H.; Universidad de la República, Facultad de Ingeniería, Facultad de Ciencias Sociales, Uruguay; email:horacio.lena@cienciassociales.edu.uy -- Publisher: Institute of Electrical and Electronics Engineers Inc. -- Sponsors: The Institute of Electrical and Electronics Engineers, Geoscience and Remote Sensing Society (GRSS). --
520 $aABSTRACT.- Crop type classification with satellite imageries is widely applied to support sustainable agricultural practices and for continuous crop monitoring [1], [2], [3]. In this work, we present a study for the classification of winter crops on a nationwide perspective for Uruguay. We have analyzed Uruguay's three most widely extended winter crops: wheat, barley, and rapeseed. We have trained a classifier based on XGBoost that uses temporal series built from Sentinel-2 image data. For training, we used the information from previous years and reported the results the following year. To our knowledge, this is the first work that proposes a clear and systematic way to classify winter crops in Uruguay based on historical data without needing samples of the actual year. We have obtained high precision and recall values for rapeseed and results comparable with other regions' work for wheat and barley. © 2024 IEEE.
653 $aCrop classification
653 $aDecent work and economic growth - Goal 8
653 $aRemote sensing
653 $aResponsible consumption and production - Goal 12
653 $aSISTEMAS DE INFORMACIÓN Y TRANSFORMACIÓN DIGITAL - INIA
653 $aSustainable Development Goals (SDGs)
653 $aXGBoost
653 $aZero hunger - Goal 2
700 1 $aCAL, A.
700 1 $aPRECIOZZI, J.
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