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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
08/06/2022 |
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Actualizado : |
08/06/2022 |
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Autor : |
VANCUTSEM, C.; PEKEL, J.-F.; KAYITAKIRE F.; DUVEILLER, G.; MERONI, M.; BAETHGEN, W.; CECCATO, P. |
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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. |
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Título : |
Mapping winter and summer crops in Uruguay using MODIS time series. [Conference paper]. |
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Complemento del título : |
2nd International Conference on Agro-Geoinformatics: Information for Sustainable Agriculture, Agro-Geoinformatics 2013. August 12-16 2013. Code 101027 |
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Fecha de publicación : |
2013 |
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Fuente / Imprenta : |
Second International Conference on Agro-Geoinformatics (Agro-Geoinformatics), 2013, pp. 292-295, doi: http://doi.rog/10.1109/Argo-Geoinformatics.2013.6621924 |
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ISBN : |
978-147990868-4 |
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DOI : |
10.1109/Argo-Geoinformatics.2013.6621924 |
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Idioma : |
Inglés |
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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 |
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Palabras claves : |
Agricultural monitoring; Cropland mapping; Land use; Mean compositing; MODIS time series; Phenology; Spatial and temporal resolutions; Uruguay. |
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Asunto categoría : |
A50 Investigación agraria |
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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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Registro completo
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Biblioteca (s) : |
INIA Tacuarembó. |
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Fecha actual : |
10/02/2015 |
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Actualizado : |
13/06/2018 |
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Tipo de producción científica : |
Documentos |
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Autor : |
JAURENA, M.; ANTUNEZ, J.; DIAZ, S.; ZAGO, R.; SOSA, M.; WUNDERLICH, E.; JUSTO, A. |
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Afiliación : |
MARTIN ALEJANDRO JAURENA BARRIOS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JUAN ANGEL ANTUNEZ GAITES, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SAULO SEBASTIAN DIAZ OLIVERA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; RODRIGO ZAGO FAGUNDES, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARTIN OSORIO SOSA PINTADO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; EDUARDO WUNDERLICH; ANDRE JUSTO. |
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Título : |
Evolución del índice verde del campo natural en condiciones de riego y secano. |
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Fecha de publicación : |
2015 |
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Fuente / Imprenta : |
In: INIA TACUAREMBÓ. JORNADA DE DIVULGACIÓN, 6 DE FEBRERO, 2015, TAMBORES, URUGUAY. Manejo de la fertilización de pasturas, forrajes y campo natural bajo riego suplementario. Tacuarembó (Uruguay): INIA, 2015. |
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Páginas : |
p. 25-26 |
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Serie : |
(Serie Actividades de Difusión; 742) |
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ISSN : |
1688-9258 |
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Idioma : |
Español |
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Contenido : |
El sensoriamiento remoto a nivel del terreno es una nieva herramienta que se está validando para la estimación del crecimiento y el contenido de proteína del forraje del campo natural. Dicho instrumento permite el cálculo en tiempo real de Índices de Vegetación por Diferencia Normalizada (NDVI), el cual se ha demostrado en diversos experimentos a nivel de sensores remotos satelitales que tiene una alta relación con la tasa de acumulación de biomasa de la pastura y con los niveles de nutrición nitrogenada. |
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Palabras claves : |
INDICE VERDE. |
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Thesagro : |
CAMPO NATURAL; INDICES. |
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Asunto categoría : |
-- |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/10226/1/SAD-742p21-22.pdf
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Marc : |
LEADER 01381naa a2200265 a 4500
001 1052192
005 2018-06-13
008 2015 bl uuuu u00u1 u #d
022 $a1688-9258
100 1 $aJAURENA, M.
245 $aEvolución del índice verde del campo natural en condiciones de riego y secano.
260 $c2015
300 $ap. 25-26
490 $a(Serie Actividades de Difusión; 742)
520 $aEl sensoriamiento remoto a nivel del terreno es una nieva herramienta que se está validando para la estimación del crecimiento y el contenido de proteína del forraje del campo natural. Dicho instrumento permite el cálculo en tiempo real de Índices de Vegetación por Diferencia Normalizada (NDVI), el cual se ha demostrado en diversos experimentos a nivel de sensores remotos satelitales que tiene una alta relación con la tasa de acumulación de biomasa de la pastura y con los niveles de nutrición nitrogenada.
650 $aCAMPO NATURAL
650 $aINDICES
653 $aINDICE VERDE
700 1 $aANTUNEZ, J.
700 1 $aDIAZ, S.
700 1 $aZAGO, R.
700 1 $aSOSA, M.
700 1 $aWUNDERLICH, E.
700 1 $aJUSTO, A.
773 $tIn: INIA TACUAREMBÓ. JORNADA DE DIVULGACIÓN, 6 DE FEBRERO, 2015, TAMBORES, URUGUAY. Manejo de la fertilización de pasturas, forrajes y campo natural bajo riego suplementario. Tacuarembó (Uruguay): INIA, 2015.
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INIA Tacuarembó (TBO) |
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