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Biblioteca (s) : |
INIA Las Brujas. |
Fecha : |
08/06/2022 |
Actualizado : |
08/06/2022 |
Autor : |
VANCUTSEM, C.; PEKEL, J.-F.; KAYITAKIRE F.; DUVEILLER, G.; MERONI, M.; BAETHGEN, W.; CECCATO, P. |
Afiliación : |
C. VANCUTSEM, European Commission, Joint Research Centre, Institute for Environment and Sustainability, 1-21027 Ispra (VA), Via E. Fermi 2749, Italy; J.-F. PEKEL, European Commission, Joint Research Centre, Institute for Environment and Sustainability, 1-21027 Ispra (VA), Via E. Fermi 2749, Italy; F. KAYITAKIRE, European Commission, Joint Research Centre, Institute for Environment and Sustainability, 1-21027 Ispra (VA), Via E. Fermi 2749, Italy; G. DUVEILLER, European Commission, Joint Research Centre, Institute for Environment and Sustainability, 1-21027 Ispra (VA), Via E. Fermi 2749, Italy; M. MERONI, European Commission, Joint Research Centre, Institute for Environment and Sustainability, 1-21027 Ispra (VA), Via E. Fermi 2749, Italy; WALTER E. BAETHGEN, International Research Institute for Climate and Society (IRI), Earth Institute at Columbia University, Palisades, NY 10964-8000, 61 Route 9W, Monell Building, United States; P. CECCATO, International Research Institute for Climate and Society (IRI), Earth Institute at Columbia University, Palisades, NY 10964-8000, 61 Route 9W, Monell Building, United States. |
Título : |
Mapping winter and summer crops in Uruguay using MODIS time series. [Conference paper]. |
Complemento del título : |
2nd International Conference on Agro-Geoinformatics: Information for Sustainable Agriculture, Agro-Geoinformatics 2013. August 12-16 2013. Code 101027 |
Fecha de publicación : |
2013 |
Fuente / Imprenta : |
Second International Conference on Agro-Geoinformatics (Agro-Geoinformatics), 2013, pp. 292-295, doi: http://doi.rog/10.1109/Argo-Geoinformatics.2013.6621924 |
ISBN : |
978-147990868-4 |
DOI : |
10.1109/Argo-Geoinformatics.2013.6621924 |
Idioma : |
Inglés |
Contenido : |
ABSTRACT - Agricultural monitoring is a major concern to economies largely based on agriculture like Uruguay. In order to improve crop yield forecasts, identification of crop types must be performed early in the planting season. However, this task is generally difficult because of the spatial heterogeneity of the landscape, the different crop cycles, the spectral similarity with grassland, and the inter-annual variability due to climatic events and fallow periods. In collaboration with INIA, this study investigates remote sensing methods for dynamic mapping of cropland areas and for producing a map of winter and summer crops at 250m using MODIS time series. The originality of the approach consists of: (i) exploiting all the multi-spectral information using an adaptive compositing method for a better discrimination of cropland types and to better capture their spatio-temporal variability; (ii) a spatio-temporal analysis of various land use types prior to the classification for a better knowledge of crops behaviours and the selection of the most discriminating seasons in the classification; and (iii) combining NDVI profiles, multi-spectral composites with reference dataset, high resolution images and expert knowledge. The accuracy of the product is assessed based on a reference dataset of crop fields. The results confirm the relevance of MODIS time series in term of spatial and temporal resolutions for mapping cropland areas and characterizing the inter-annual variability. Thanks to a good reference dataset and an analysis of crops spectro-temporal behaviour, it was possible to identify cropland areas from other land use types and discriminate summer crops from winter crops. MenosABSTRACT - Agricultural monitoring is a major concern to economies largely based on agriculture like Uruguay. In order to improve crop yield forecasts, identification of crop types must be performed early in the planting season. However, this task is generally difficult because of the spatial heterogeneity of the landscape, the different crop cycles, the spectral similarity with grassland, and the inter-annual variability due to climatic events and fallow periods. In collaboration with INIA, this study investigates remote sensing methods for dynamic mapping of cropland areas and for producing a map of winter and summer crops at 250m using MODIS time series. The originality of the approach consists of: (i) exploiting all the multi-spectral information using an adaptive compositing method for a better discrimination of cropland types and to better capture their spatio-temporal variability; (ii) a spatio-temporal analysis of various land use types prior to the classification for a better knowledge of crops behaviours and the selection of the most discriminating seasons in the classification; and (iii) combining NDVI profiles, multi-spectral composites with reference dataset, high resolution images and expert knowledge. The accuracy of the product is assessed based on a reference dataset of crop fields. The results confirm the relevance of MODIS time series in term of spatial and temporal resolutions for mapping cropland areas and characterizing the inter-annual variability. Tha... Presentar Todo |
Palabras claves : |
Agricultural monitoring; Cropland mapping; Land use; Mean compositing; MODIS time series; Phenology; Spatial and temporal resolutions; Uruguay. |
Asunto categoría : |
A50 Investigación agraria |
Marc : |
LEADER 02708nam a2200301 a 4500 001 1063255 005 2022-06-08 008 2013 bl uuuu u01u1 u #d 020 $a978-147990868-4 024 7 $a10.1109/Argo-Geoinformatics.2013.6621924$2DOI 100 1 $aVANCUTSEM, C. 245 $aMapping winter and summer crops in Uruguay using MODIS time series. [Conference paper].$h[electronic resource] 260 $aSecond International Conference on Agro-Geoinformatics (Agro-Geoinformatics), 2013, pp. 292-295, doi: http://doi.rog/10.1109/Argo-Geoinformatics.2013.6621924$c2013 520 $aABSTRACT - Agricultural monitoring is a major concern to economies largely based on agriculture like Uruguay. In order to improve crop yield forecasts, identification of crop types must be performed early in the planting season. However, this task is generally difficult because of the spatial heterogeneity of the landscape, the different crop cycles, the spectral similarity with grassland, and the inter-annual variability due to climatic events and fallow periods. In collaboration with INIA, this study investigates remote sensing methods for dynamic mapping of cropland areas and for producing a map of winter and summer crops at 250m using MODIS time series. The originality of the approach consists of: (i) exploiting all the multi-spectral information using an adaptive compositing method for a better discrimination of cropland types and to better capture their spatio-temporal variability; (ii) a spatio-temporal analysis of various land use types prior to the classification for a better knowledge of crops behaviours and the selection of the most discriminating seasons in the classification; and (iii) combining NDVI profiles, multi-spectral composites with reference dataset, high resolution images and expert knowledge. The accuracy of the product is assessed based on a reference dataset of crop fields. The results confirm the relevance of MODIS time series in term of spatial and temporal resolutions for mapping cropland areas and characterizing the inter-annual variability. Thanks to a good reference dataset and an analysis of crops spectro-temporal behaviour, it was possible to identify cropland areas from other land use types and discriminate summer crops from winter crops. 653 $aAgricultural monitoring 653 $aCropland mapping 653 $aLand use 653 $aMean compositing 653 $aMODIS time series 653 $aPhenology 653 $aSpatial and temporal resolutions 653 $aUruguay 700 1 $aPEKEL, J.-F. 700 1 $aKAYITAKIRE F. 700 1 $aDUVEILLER, G. 700 1 $aMERONI, M. 700 1 $aBAETHGEN, W. 700 1 $aCECCATO, P.
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Registro original : |
INIA Las Brujas (LB) |
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha actual : |
12/06/2020 |
Actualizado : |
12/06/2020 |
Tipo de producción científica : |
Informes Agroclimáticos |
Autor : |
INIA (INSTITUTO NACIONAL DE INVESTIGACIÓN AGROPECUARIA); GRAS |
Afiliación : |
UNIDAD DE AGROCLIMA Y SISTEMAS DE INFORMACIÓN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Informe agroclimático 2020- Situación a Mayo. |
Fecha de publicación : |
2020 |
Fuente / Imprenta : |
Montevideo (Uruguay): INIA, 2020. |
Páginas : |
4 p. |
Serie : |
(Informe Agroclimático; Año 15, No.5) |
Idioma : |
Español |
Notas : |
Equipo de trabajo INIA-GRAS (Unidad de Agtech y sistemas de Información): Adrián Cal, Guadalupe Tiscornia, Carlos Schiavi, Gabriel García. |
Contenido : |
Contenido. Síntesis de la Situación Agroclimática de Mayo-- Perspectivas Climáticas Trimestrales elaboradas por el IRI de la Universidad de Columbia -- Índice de Vegetación (IVDN) -- Precipitaciones -- Porcentaje de Agua Disponible (PAD) -- Índice de Bienestar Hídrico (IBH) -- Agua No Retenida (ANR) -- Perspectivas Climáticas Jun-Jul-Ago elaboradas por el IRI de la Universidad de Columbia. Destacamos para este mes: Previsión de condiciones ambientales para corderos recién nacidos. Y el
nuevo producto complementario: Climatología del índice de enfriamiento (Chill Index) para ovinos sobre Uruguay (1981-2015).
Se encuentran disponibles en la web del GRAS dentro del ítem: "Alertas y herramientas". Acceso directo: http://www.inia.uy/gras/Alertas-y-herramientas |
Palabras claves : |
AGROCLIMA; AGROCLIMATOLOGÍA; AGTECH; BOLETIN AGROCLIMÁTICO; CARACTERIZACIÓN AGROCLIMÁTICA; DIRECCION VIENTO; ESTACIONES AGROMETEOROLOGICAS; ESTACIONES AUTOMATICAS; ESTACIONES INIA; ESTADO DEL TIEMPO; ESTRÉS HÍDRICO; GRAFICAS AGROCLIMATICAS; GRAS; HELIOFANOGRAFO; INFORMACION SATELITAL; INFORME AGROCLIMÁTICO 2020; INUNDACIONES; LLUVIAS DIARIAS; MAXIMA; MEDIA; MINIMA; PANEL SOLAR; PERSPECTIVAS CLIMATICAS; PLUVIOMETRO; PRECIPITACION NACIONAL; PREVENCION HELADAS; PRONOSTICO; SENSOR; SIMETRICO; TANQUE A; TERMOCUPLAS; TERMOHIDROGRAFO; VARIABLES AGROCLIMATICAS; VELETA. |
Thesagro : |
AGROCLIMATOLOGIA; CAMBIO CLIMATICO; CLIMA; CLIMATOLOGIA; ESTACIONES METEOROLOGICAS; ESTRES HIDRICO; EVAPORACION; EVAPOTRANSPIRACION; HUMEDAD; HUMEDAD RELATIVA; LLUVIA; METEOROLOGIA; PERSPECTIVAS; PLUVIOMETROS; PRONOSTICO DEL TIEMPO; SENSORES; SISTEMAS; SISTEMAS DE INFORMACION; SUELO; TEMPERATURA; TERMOMETROS. |
Asunto categoría : |
P40 Meteorología y climatología |
URL : |
http://www.inia.uy/Publicaciones/Documentos%20compartidos/Informe%20agroclimatico%20INIA-GRAS%20mayo%20de%202020.pdf
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Marc : |
LEADER 03096nam a2200817 a 4500 001 1061125 005 2020-06-12 008 2020 bl uuuu u0uu1 u #d 100 1 $aINIA (INSTITUTO NACIONAL DE INVESTIGACIÓN AGROPECUARIA) 245 $aInforme agroclimático 2020- Situación a Mayo.$h[electronic resource] 260 $aMontevideo (Uruguay): INIA$c2020 300 $a4 p. 490 $a(Informe Agroclimático; Año 15, No.5) 500 $aEquipo de trabajo INIA-GRAS (Unidad de Agtech y sistemas de Información): Adrián Cal, Guadalupe Tiscornia, Carlos Schiavi, Gabriel García. 520 $aContenido. Síntesis de la Situación Agroclimática de Mayo-- Perspectivas Climáticas Trimestrales elaboradas por el IRI de la Universidad de Columbia -- Índice de Vegetación (IVDN) -- Precipitaciones -- Porcentaje de Agua Disponible (PAD) -- Índice de Bienestar Hídrico (IBH) -- Agua No Retenida (ANR) -- Perspectivas Climáticas Jun-Jul-Ago elaboradas por el IRI de la Universidad de Columbia. Destacamos para este mes: Previsión de condiciones ambientales para corderos recién nacidos. Y el nuevo producto complementario: Climatología del índice de enfriamiento (Chill Index) para ovinos sobre Uruguay (1981-2015). Se encuentran disponibles en la web del GRAS dentro del ítem: "Alertas y herramientas". Acceso directo: http://www.inia.uy/gras/Alertas-y-herramientas 650 $aAGROCLIMATOLOGIA 650 $aCAMBIO CLIMATICO 650 $aCLIMA 650 $aCLIMATOLOGIA 650 $aESTACIONES METEOROLOGICAS 650 $aESTRES HIDRICO 650 $aEVAPORACION 650 $aEVAPOTRANSPIRACION 650 $aHUMEDAD 650 $aHUMEDAD RELATIVA 650 $aLLUVIA 650 $aMETEOROLOGIA 650 $aPERSPECTIVAS 650 $aPLUVIOMETROS 650 $aPRONOSTICO DEL TIEMPO 650 $aSENSORES 650 $aSISTEMAS 650 $aSISTEMAS DE INFORMACION 650 $aSUELO 650 $aTEMPERATURA 650 $aTERMOMETROS 653 $aAGROCLIMA 653 $aAGROCLIMATOLOGÍA 653 $aAGTECH 653 $aBOLETIN AGROCLIMÁTICO 653 $aCARACTERIZACIÓN AGROCLIMÁTICA 653 $aDIRECCION VIENTO 653 $aESTACIONES AGROMETEOROLOGICAS 653 $aESTACIONES AUTOMATICAS 653 $aESTACIONES INIA 653 $aESTADO DEL TIEMPO 653 $aESTRÉS HÍDRICO 653 $aGRAFICAS AGROCLIMATICAS 653 $aGRAS 653 $aHELIOFANOGRAFO 653 $aINFORMACION SATELITAL 653 $aINFORME AGROCLIMÁTICO 2020 653 $aINUNDACIONES 653 $aLLUVIAS DIARIAS 653 $aMAXIMA 653 $aMEDIA 653 $aMINIMA 653 $aPANEL SOLAR 653 $aPERSPECTIVAS CLIMATICAS 653 $aPLUVIOMETRO 653 $aPRECIPITACION NACIONAL 653 $aPREVENCION HELADAS 653 $aPRONOSTICO 653 $aSENSOR 653 $aSIMETRICO 653 $aTANQUE A 653 $aTERMOCUPLAS 653 $aTERMOHIDROGRAFO 653 $aVARIABLES AGROCLIMATICAS 653 $aVELETA 700 1 $aGRAS
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