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| Registros recuperados : 28 | |
| 2. |  | BÉGUÉ, A.; ARVOR, D.; LELONG, C.; VINTROU, E.; SIMÕES, M. Agricultural systems studies using remote sensing. In: TENKABAIL, P. S. (Ed.). Land resources monitoring, modeling, and mapping with remote sensing. Boca Raton: CRC Press, 2015. cap. 5, p. 113-130.| Biblioteca(s): Embrapa Solos. |
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| 3. | | MULIANGA, B.; BÉGUÉ, A.; SIMÕES, M.; CLOUVEL, P.; TODOROFF, P. Estimating potential soil erosion for environmental services in a sugarcane growing área ussing multisource remote sensing data. In: SPIE REMOTE SENSING, 4., 2013, Dresden. Remote sensing for agriculture, ecosystems, and hydrology XV: proceedings... Bellingham: SPIE, 2013. v. 8887. Ref. 88871W.| Biblioteca(s): Embrapa Solos. |
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| 10. | | ARVOR, D.; MEIRELLES, M. S. P.; DUBREUIL, V.; BEGUÈ, A.; SHIMABUKURO, Y. E. Analyzing the agricultural transition in Mato Grosso, Brazil, using satellite-derived indices. Applied Geography, v. 32, p. 702-713, 2011.| Biblioteca(s): Embrapa Solos. |
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| 11. | | KUCHLER, P. C.; BÉGUÉ, A.; SIMÕES, M.; GAETANO, R.; ARVOR, D.; FERRAZ, R. P. D. Assessing the optimal preprocessing steps of MODIS time series to map cropping systems in Mato Grosso, Brazil. International Journal of Applied Earth Observation and Geoinformation, v. 92, 102150, Oct. 2020.| Biblioteca(s): Embrapa Solos. |
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| 18. | | BELLÓN, B.; BÉGUÉ, A.; LO SEEN, D.; LEBOURGEOIS, V.; EVANGELISTA, B. A.; SIMÕES, M.; FERRAZ, R. P. D. Improved regional-scale Brazilian cropping systems' mapping based on a semi-automatic object-based clustering approach. International Journal of Applied Earth Observation and Geoinformation, V. 68, p. 127-138, Jun. 2018.| Biblioteca(s): Embrapa Pesca e Aquicultura; Embrapa Solos. |
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| 19. | | KUCHLER, P. C.; SIMÕES, M.; BÉGUÉ, A.; MACHADO, P. L. O. de A.; FERRAZ, R. P. D.; MADARI, B. E.; FREITAS, P. L. de; MANZATTO, C. V. Monitoring Brazilian low-carbon agriculture plan: the potential of remote sensing to detect adoption of selected agricultural practices. In: EFITA WCCA CONGRESS, 2017, Montpellier. Conference proceedings. Montpellier: Efita, 2017. p. 169-170.| Biblioteca(s): Embrapa Arroz e Feijão. |
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| 20. | | KUCHLER, P. C.; SIMÕES, M.; BÉGUÉ, A.; MACHADO, P. L. O. de A.; FERRAZ, R. P. D.; MADARI, B. E.; FREITAS, P. L. de; MANZATTO, C. V. Monitoring Brazilian low-carbon agriculture plan: the potential of remote sensing to detect adoption of selected agricultural practices. In: EFITA WCCA CONGRESS, 2017, Montpellier. Conference proceedings. Montpellier: Efita, 2017. p. 169-170.| Biblioteca(s): Embrapa Solos. |
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| Registros recuperados : 28 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Solos. |
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Data corrente: |
06/01/2022 |
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Data da última atualização: |
28/03/2023 |
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Autoria: |
JOLIVOT, A.; LEBOURGEOIS, V.; LEROUX, L.; AMELINE, M.; ANDRIAMANGA, V.; BELLÓN, B.; CASTETS, M.; CRESPIN-BOUCAUD, A.; DEFOURNY, P.; DIAZ, S.; DIEYE, M.; DUPUY, S.; FERRAZ, R. P. D.; GAETANO, R.; GELY, M.; JAHEL, C.; KABORE, B.; LELONG, C.; LE MAIRE, G.; LO SEEN, D.; MUTHONI, M.; NDAO, B.; NEWBY, T.; SANTOS, C. L. M. de O.; RASOAMALALA, E.; SIMÕES, M.; THIAW, I.; TIMMERMANS, A.; TRAN, A.; BÉGUÉ, A. |
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Afiliação: |
AUDREY JOLIVOT, CIRAD/TETIS; VALENTINE LEBOURGEOIS, CIRAD/TETIS; LOUISE LEROUX, CIRAD/AIDA/Centre de Suivi Ecologique; MAEL AMELINE, CIRAD/TETIS; VALÉRIE ANDRIAMANGA, CIRAD/Centre National de la Recherche Appliquée au Développement Rural; BEATRIZ BELLÓN, CIRAD/TETIS; MATHIEU CASTETS, CIRAD/TETIS; ARTHUR CRESPIN-BOUCAUD, CIRAD/TETIS; PIERRE DEFOURNY, Université Catholique de Louvain; SANTIANA DIAZ, CIRAD/TETIS; MOHAMADOU DIEYE, Institut Sénégalais de Recherches Agricoles; STÉPHANE DUPUY, CIRAD/TETIS; RODRIGO PECANHA DEMONTE FERRAZ, CNPS; RAFFAELE GAETANO, CIRAD/TETIS; MARIE GELY, CIRAD/TETIS; CAMILLE JAHEL, CIRAD/TETIS; BERTIN KABORE, Independent consultant: Ouagadougou, Burkina Faso; CAMILLE LELONG, CIRAD/TETIS; GUERRIC LE MAIRE, CIRAD/Eco&Sols; DANNY LO SEEN, CIRAD/TETIS; MARTHA MUTHONI, Independent consultant: Nairobi, Kenya; BABACAR NDAO, Centre de Suivi Ecologique/Université Cheikh Anta Diop de Dakar; TERRY NEWBY, Agricultural Research Council; CECÍLIA LIRA MELO DE OLIVEIRA SANTOS, UNICAMP; ELOISE RASOAMALALA, CIRAD/Centre National de la Recherche Appliquée au Développement Rural; MARGARETH GONCALVES SIMOES, CNPS; IBRAHIMA THIAW, Université Cheikh Anta Diop de Dakar; ALICE TIMMERMANS, Université Catholique de Louvain; ANNELISE TRAN, CIRAD/TETIS; AGNÈS BÉGUÉ, CIRAD/TETIS. |
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Título: |
Harmonized in situ datasets for agricultural land use mapping and monitoring in tropical countries. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Earth System Science Data, v. 13, n. 2, p. 5951-5967, 2021. |
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DOI: |
https://doi.org/10.5194/essd-13-5951-2021 |
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Idioma: |
Inglês |
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Conteúdo: |
The availability of crop type reference datasets for satellite image classification is very limited for complex agricultural systems as observed in developing and emerging countries. Indeed, agricultural land use is very dynamic, agricultural censuses are often poorly georeferenced and crop types are difficult to interpret directly from satellite imagery. In this paper, we present a database made of 24 datasets collected in a standardized manner over nine sites within the framework of the international JECAM (Joint Experiment for Crop Assessment and Monitoring) initiative; the sites were spread over seven countries of the tropical belt, and the number of data collection years depended on the site (from 1 to 7 years between 2013 and 2020). These quality-controlled datasets are distinguished by in situ data collected at the field scale by local experts, with precise geographic coordinates, and following a common protocol. Altogether, the datasets completed 27 074 polygons (20 257 crops and 6817 noncrops, ranging from 748 plots in 2013 (one site visited) to 5515 in 2015 (six sites visited)) documented by detailed keywords. These datasets can be used to produce and validate agricultural land use maps in the tropics. They can also be used to assess the performances and robustness of classification methods of cropland and crop types/practices in a large range of tropical farming systems. The dataset is available at https://doi.org/10.18167/DVN1/P7OLAP (Jolivot et al., 2021). |
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Thesagro: |
Cobertura do Solo; Sensoriamento Remoto; Sistema de Cultivo. |
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Thesaurus NAL: |
Cropland; Cropping systems; Remote sensing. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/229993/1/Harmonized-in-situ-datasets-for-agricultural-land-use-2021.pdf
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Marc: |
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005 2023-03-28
008 2021 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.5194/essd-13-5951-2021$2DOI
100 1 $aJOLIVOT, A.
245 $aHarmonized in situ datasets for agricultural land use mapping and monitoring in tropical countries.$h[electronic resource]
260 $c2021
520 $aThe availability of crop type reference datasets for satellite image classification is very limited for complex agricultural systems as observed in developing and emerging countries. Indeed, agricultural land use is very dynamic, agricultural censuses are often poorly georeferenced and crop types are difficult to interpret directly from satellite imagery. In this paper, we present a database made of 24 datasets collected in a standardized manner over nine sites within the framework of the international JECAM (Joint Experiment for Crop Assessment and Monitoring) initiative; the sites were spread over seven countries of the tropical belt, and the number of data collection years depended on the site (from 1 to 7 years between 2013 and 2020). These quality-controlled datasets are distinguished by in situ data collected at the field scale by local experts, with precise geographic coordinates, and following a common protocol. Altogether, the datasets completed 27 074 polygons (20 257 crops and 6817 noncrops, ranging from 748 plots in 2013 (one site visited) to 5515 in 2015 (six sites visited)) documented by detailed keywords. These datasets can be used to produce and validate agricultural land use maps in the tropics. They can also be used to assess the performances and robustness of classification methods of cropland and crop types/practices in a large range of tropical farming systems. The dataset is available at https://doi.org/10.18167/DVN1/P7OLAP (Jolivot et al., 2021).
650 $aCropland
650 $aCropping systems
650 $aRemote sensing
650 $aCobertura do Solo
650 $aSensoriamento Remoto
650 $aSistema de Cultivo
700 1 $aLEBOURGEOIS, V.
700 1 $aLEROUX, L.
700 1 $aAMELINE, M.
700 1 $aANDRIAMANGA, V.
700 1 $aBELLÓN, B.
700 1 $aCASTETS, M.
700 1 $aCRESPIN-BOUCAUD, A.
700 1 $aDEFOURNY, P.
700 1 $aDIAZ, S.
700 1 $aDIEYE, M.
700 1 $aDUPUY, S.
700 1 $aFERRAZ, R. P. D.
700 1 $aGAETANO, R.
700 1 $aGELY, M.
700 1 $aJAHEL, C.
700 1 $aKABORE, B.
700 1 $aLELONG, C.
700 1 $aLE MAIRE, G.
700 1 $aLO SEEN, D.
700 1 $aMUTHONI, M.
700 1 $aNDAO, B.
700 1 $aNEWBY, T.
700 1 $aSANTOS, C. L. M. de O.
700 1 $aRASOAMALALA, E.
700 1 $aSIMÕES, M.
700 1 $aTHIAW, I.
700 1 $aTIMMERMANS, A.
700 1 $aTRAN, A.
700 1 $aBÉGUÉ, A.
773 $tEarth System Science Data$gv. 13, n. 2, p. 5951-5967, 2021.
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