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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 : |
23/10/2020 |
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Actualizado : |
09/04/2021 |
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Tipo de producción científica : |
Capítulo en Libro Técnico-Científico |
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Autor : |
HASTINGS, F.; FUENTES, I.; PÉREZ-BIDEGAIN, M.; NAVAS, R.; GORGOGLIONE, A. |
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Afiliación : |
FLORENCIA HASTINGS, School of Agronomy Universidad de la República, Montevideo, Uruguay; Directorate of Natural Resources, Ministry of Agriculture, Livestock and Fisheries, Montevideo, Uruguay; IGNACIO FUENTES, School of Life and Environmental Sciences, University of Sydney, Sydney, Australia; MARIO PÉREZ-BIDEGAIN, School of Agronomy, Universidad de la República, Montevideo, Uruguay; RAFAEL NAVAS NÚÑEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ÁNGELA GORGOGLIONE, School of Engineering, Universidad de la República, Montevideo, Uruguay. |
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Título : |
Land-cover mapping of agricultural areas using machine learning in Google Earth engine. (Conference paper) |
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Fecha de publicación : |
2020 |
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Fuente / Imprenta : |
In: Gervasi O. et al. (eds) Computational Science and Its Applications - ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science, vol 12252. International Conference on Computational Science and Its Applications. Springer, Cham. https://doi.org/10.1007/978-3-030-58811-3_52 |
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ISBN : |
e-ISBN: 978-3-030-58811-3 |
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DOI : |
10.1007/978-3-030-58811-3_52 |
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Idioma : |
Inglés |
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Notas : |
Article history: First Online 29 September 2020. Volume Editors: Gervasi O.,Murgante B.,Misra S. .,Garau C.,Blecic I.,Taniar D.,Apduhan B.O.,Rocha A.M.A.C.,Tarantino E.,Torre C.M.,Karaca Y. Publisher: Springer Science and Business Media Deutschland GmbH.
20th International Conference on Computational Science and Its Applications, ICCSA 2020; Cagliari; Italy; 1 July 2020 through 4 July 2020; Code 249529.
Corresponding author: Hastings, F.; School of Agronomy, Universidad de la República, Av. Gral. Eugenio Garzón 780, Montevideo, Uruguay; email:fhastings@mgap.gub.uy |
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Contenido : |
Land-cover mapping is critically needed in land-use planning and policy making. Compared to other techniques, Google Earth Engine (GEE) offers a free cloud of satellite information and high computation capabilities. In this context, this article examines machine learning with GEE for land-cover mapping. For this purpose, a five-phase procedure is applied: (1) imagery selection and pre-processing, (2) selection of the classes and training samples, (3) classification process, (4) post-classification, and (5) validation. The study region is located in the San Salvador basin (Uruguay), which is under agricultural intensification. As a result, the 1990 land-cover map of the San Salvador basin is produced. The new map shows good agreements with past agriculture census and reveals the transformation of grassland to cropland in the period 1990?2018. © 2020, Springer Nature Switzerland AG. |
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Palabras claves : |
Agricultural region; Google earth engine; Land-cover map; Supervised classification. |
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Asunto categoría : |
A50 Investigación agraria |
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Marc : |
LEADER 02413nam a2200229 a 4500
001 1061424
005 2021-04-09
008 2020 bl uuuu u0uu1 u #d
024 7 $a10.1007/978-3-030-58811-3_52$2DOI
100 1 $aHASTINGS, F.
245 $aLand-cover mapping of agricultural areas using machine learning in Google Earth engine. (Conference paper)$h[electronic resource]
260 $aIn: Gervasi O. et al. (eds) Computational Science and Its Applications - ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science, vol 12252. International Conference on Computational Science and Its Applications. Springer, Cham. https://doi.org/10.1007/978-3-030-58811-3_52$c1007
500 $aArticle history: First Online 29 September 2020. Volume Editors: Gervasi O.,Murgante B.,Misra S. .,Garau C.,Blecic I.,Taniar D.,Apduhan B.O.,Rocha A.M.A.C.,Tarantino E.,Torre C.M.,Karaca Y. Publisher: Springer Science and Business Media Deutschland GmbH. 20th International Conference on Computational Science and Its Applications, ICCSA 2020; Cagliari; Italy; 1 July 2020 through 4 July 2020; Code 249529. Corresponding author: Hastings, F.; School of Agronomy, Universidad de la República, Av. Gral. Eugenio Garzón 780, Montevideo, Uruguay; email:fhastings@mgap.gub.uy
520 $aLand-cover mapping is critically needed in land-use planning and policy making. Compared to other techniques, Google Earth Engine (GEE) offers a free cloud of satellite information and high computation capabilities. In this context, this article examines machine learning with GEE for land-cover mapping. For this purpose, a five-phase procedure is applied: (1) imagery selection and pre-processing, (2) selection of the classes and training samples, (3) classification process, (4) post-classification, and (5) validation. The study region is located in the San Salvador basin (Uruguay), which is under agricultural intensification. As a result, the 1990 land-cover map of the San Salvador basin is produced. The new map shows good agreements with past agriculture census and reveals the transformation of grassland to cropland in the period 1990?2018. © 2020, Springer Nature Switzerland AG.
653 $aAgricultural region
653 $aGoogle earth engine
653 $aLand-cover map
653 $aSupervised classification
700 1 $aFUENTES, I.
700 1 $aPÉREZ-BIDEGAIN, M.
700 1 $aNAVAS, R.
700 1 $aGORGOGLIONE, A.
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| 2. |  | VALENZUELA MARTÍNEZ, S.; TORRES-DINI, D.; CARRASCO-LETELIER, L.; NAYA, H. Estudio metagenómico en suelos forestados por Eucalyptus. In: JORNADAS DE LA SOCIEDAD URUGUAYA DE BIOCIENCIAS, 14., 2012, Piriápolis, Maldonado, UY. Montevideo: SUB, 2012.| Biblioteca(s): INIA La Estanzuela. |
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| 4. | | MARÍN, M.F.; NAYA, H.; ESPASANDIN, A.C.; NAVAJAS, E.; DEVINCENZI, T.; CARRIQUIRY, M. Energy efficiency, reproductive performance, and metabolic parameters of grazing Hereford heifers. Livestock Science, 2024, Volume 279, e105389. https://doi.org/10.1016/j.livsci.2023.105389 Article history: Received 21 September 2023; Received in revised form 9 November 2023; Accepted 1 December 2023; Available online 2 December 2023. -- Correspondence: Marín, M.F.; Departamento de Producción Animal y Pasturas, Facultad de...| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| 5. | | PERAZA, P.; FERNÁNDEZ-CALERO, T.; NAYA, H.; SOTELO-SILVEIRA, J.; NAVAJAS, E. Exploring the linkage between ruminal microbial communities on postweaning and finishing diets and their relation to residual feed intake in beef cattle. Microorganisms, 2024, Volume 12, Issue 12, 2437. https://doi.org/10.3390/microorganisms12122437 -- OPEN ACCESS. Article history: Submission received 7 November 2024, Revised 19 November 2024, Accepted 20 November 2024, Published: 27 November 2024. -- Academic Editor: Marianna Marangi. -- Funding: This research was funded by the Instituto Nacional...| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| 7. | | MARÍN, M.F.; NAYA, H.; DEVINCENZI, T.; NAVAJAS, E.; ESPASANDIN, A. C.; CARRIQUIRY, M. Heart rate of grazing Hereford heifers classified by paternal RFI. [Poster] EAAP - 72nd Annual Meeting, Davos, Switzerland. Session 23, Poster 11. In: Annual Meeting of the European Federation of Animal Science (EAAP), 72., 30 August - 3 September 2021, Davos, Switzerland. Book of abstracts. Wageningen, NL: WAP, 2021. p.278. doi: https://doi.org/10.3920/978-90-8686-918-3 Conference website: www.eaap2021.org| Biblioteca(s): INIA Las Brujas. |
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| 8. | | MARÍN, M.F.; NAYA, H.; NAVAJAS, E.; DEVINCENZI, T.; ESPASANDIN, A.C.; CARRIQUIRY, M. O45 Energy efficiency of Hereford heifers classified by paternal Residual Feed Intake. [conference abstract]. Animal - science proceedings, August 2022, Volume 13, Issue 3, pages 298-299. https://doi.org/10.1016/j.anscip.2022.07.055 Article history: Available online 16 September 2022, Version of Record 16 September 2022. -- Funding: This work was possible given the postgraduate scholarship awarded to M.F. Marín by la Comisión Académica de Posgrados (Universidad de la...| Tipo: Abstracts/Resúmenes |
| Biblioteca(s): INIA Las Brujas. |
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| 9. | | MARÍN, M.; NAYA, H.; ESPASANDÍN, A.C.; NAVAJAS, E.; DEVINCENZI, T.; CARRIQUIRY, M. P56. Reproductive performance of grazing hereford heifers classified by paternal residual feed intake. [conference abstract]. Animal - science proceedings, July 2023, Volume 14, Issue 4, Page 637. https://doi.org/10.1016/j.anscip.2023.04.151 -- OPEN ACCESS. Article history: Available online 4 August 2023, Version of Record 4 August 2023. -- Corresponding author: M.F. Marín. mfedericamarin@gmail.com --
Part of special issue: 11th International Symposium on the Nutrition of Herbivores (ISNH...| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| 10. | | Aguilar, I.; Pravia, M.I.; Ravagnolo, O.; Chiappesoni, G.; Mattos, M.; Ahlig, I.; Urioste, J.; Naya, H. Servicio de evaluación de reproductores Aberdeen Angus Las Brujas, Canelones (Uruguay): INIA, 2004. 23 p| Biblioteca(s): INIA La Estanzuela. |
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| 11. | | URIOSTE, J.I.; PRAVIA, M.I.; ALVEZ, G.; NAYA, H.; SPANGENBERG, L.; RAVAGNOLO, O.; LEMA, O.M. OS, software para el estudio de objetivos de selección en ganado de carne.[Presentación oral]. In: Seminario de Actualización Técnica. Mejoramiento genético animal en bovinos para carne, 7 agosto, Tacuarembó. Tacuarembó: INIA, 2015.| Tipo: Presentaciones Orales |
| Biblioteca(s): INIA Treinta y Tres. |
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| 12. | | URIOSTE, J.I.; PRAVIA, M.I.; ALVEZ, G.; NAYA, H.; SPANGENBERG, L.; RAVAGNOLO, O.; SOARES DE LIMA, J.M.; LEMA, O.M. OS, un software para estimación de objetivos de selección en ganado de carne. [Resumen] G3 - Trabajos cortos: Genética. In: Congreso Asociación Uruguaya de Producción Animal (AUPA) (5º, 3-4 Dic. 2014, Montevideo, UY). 2 p.| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Las Brujas. |
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| Registros recuperados : 12 | |
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