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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
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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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INIA Las Brujas (LB) |
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| Registros recuperados : 28 | |
| 2. |  | SAWCHIK, J.; PÉREZ BIDEGAIN, M.; GARCÍA, C. Impact of winter cover crops on soil properties under soybean cropping systems. In: INTERNATIONAL SOIL TILLAGE RESEARCH ORGANIZATION. 19., SOCIEDAD URUGUAYA DE CIENCIA DEL SUELO, 4., 2012, Montevideo, UY. [Oral presentation]: paper no. 376. Montevideo, UY: ISTRO, 2012. 8 p. También publicado en: Agrociencia Uruguay, v. 16, n. especial, p. 288-293, 2012.| Tipo: Artículos en Revistas Indexadas Nacionales | Circulación / Nivel : B - 2 |
| Biblioteca(s): INIA La Estanzuela. |
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| 3. | | ALVARIÑO, S.; BOCCO, A.; TERRA, R.; BIDEGAIN, M.; CRUZ, G. Caracterización de la variabilidad espacial y temporal de la evapotranspiración de referencia (ET0) en Uruguay. In: Zorrilla, G.; Martínez, S.; Terra, J. A. Saravia, H. (Eds.) Arroz 2018. Montevideo (UY): INIA, 2018. (INIA Serie Técnica; 246)| Tipo: Capítulo en Libro Técnico-Científico |
| Biblioteca(s): INIA Treinta y Tres. |
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| 5. | | TISCORNIA, G.; GIMÉNEZ, A.; BIDEGAIN, M.; METHOL, M. Atlas de sequías de America Latina y el Caribe. URUGUAY. In: Núñez Cobo, J.; Verbist, K. (Eds.). 2018. Atlas de sequías de América Latina y el Caribe. UNESCO y CAZALAC. pp. 120-126. La publicación completa ha sido elaborada por el Centro de Zonas Áridas y Semiáridas de América Latina y el Caribe (CAZALAC) y el Programa Hidrológico Internacional de la UNESCO (PHI) en el marco del proyecto ´Fortaleciendo la Seguridad...| Tipo: Capítulo en Libro Técnico-Científico |
| Biblioteca(s): INIA Las Brujas. |
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| 8. | | PÉREZ BIDEGAIN, M.; SAWCHIK, J.; BARRETO, P.; PÉREZ, M.M. Pesticide runoff into surface water in a mollisol under no tillage. In: INTERNATIONAL SOIL TILLAGE RESEARCH ORGANIZATION. 19., SOCIEDAD URUGUAYA DE CIENCIA DEL SUELO, 4., 2012, Montevideo, UY. Poster presentation: 372. Montevideo, UY: ISTRO, 2012.| Biblioteca(s): INIA La Estanzuela. |
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| 10. | | JORGE, G.; PÉREZ BIDEGAIN, M.; TERRA, J.A.; SAWCHIK, J. WEPP as a tool for enabling a more comprehensive analysis of the environmental impacts of soil erosion. In: INTERNATIONAL SOIL TILLAGE RESEARCH ORGANIZATION. 19., SOCIEDAD URUGUAYA DE CIENCIA DEL SUELO, 4., 2012, Montevideo, UY. [Oral presentation]: paper no. 133. Montevideo, UY: ISTRO, 2012. También publicado en: Agrociencia Uruguay, v. 16, n. especial, p. 268-273, 2012.| Tipo: Artículos en Revistas Indexadas Nacionales | Circulación / Nivel : B - 2 |
| Biblioteca(s): INIA La Estanzuela; INIA Treinta y Tres. |
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| 12. | | PEREZ-BIDEGAIN, M.; CLERICI, C.; HILL, M.; SAWCHIK, J.; TERRA, J.A.; GARCÍA-PRÉCHAC, F. Experimental validation and regulatory application of USLE/RULE in Uruguay. [Abstract]. ln: Annual Soil and Water Conservation Conference, 70., July 2015, Greensboro, North Carolina, US. Abstract Book. Soil and Water Conservation Society, 2015. p. 52.| Tipo: Abstracts/Resúmenes |
| Biblioteca(s): INIA Treinta y Tres. |
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| 15. | | HASTINGS, F.; FUENTES, I.; PÉREZ-BIDEGAIN, M.; NAVAS, R.; GORGOGLIONE, A. Land-cover mapping of agricultural areas using machine learning in Google Earth engine. (Conference paper) 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 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...| Tipo: Capítulo en Libro Técnico-Científico |
| Biblioteca(s): INIA Las Brujas. |
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| 19. | | PÉREZ-BIDEGAIN, M.; HILL, M.; CLERICI, C.; TERRA, J.A.; SAWCHIK, J.; GARCÍA-PRÉCHAC, F. Regulatory utilization of USLE/RUSLE erosion rate estimates in Uruguay: a policy coincident with the UN sustainable development goals. In: Lal, R.; Horn, R.; Kosaki, T., eds. Soil and sustainable development goals. Stuttgar, Germany: Catena-Scheweizerbar. 2018, p. 82-91.| Tipo: Capítulo en Libro Técnico-Científico |
| Biblioteca(s): INIA Treinta y Tres. |
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| Registros recuperados : 28 | |
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