Relationship between crop nutritional status, spectral measurements and Sentinel 2 images
In order to monitor the nutritional status of some crops based on plant spectroscopy and Sentinel 2 satellite images in Colombia, spectral reflectance data were taken between 350 and 2,500 nm with a FieldSpec 4 spectrometer in rubber, rice, sugar cane, maize, soybean, cashew, oil palm crops, pasture...
- Autores:
-
Martínez M., Luis Joel
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2017
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/68194
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/68194
http://bdigital.unal.edu.co/69227/
- Palabra clave:
- 63 Agricultura y tecnologías relacionadas / Agriculture
spectral reflectance
spectroradiometry
crop nutrition.
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
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Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Martínez M., Luis Joel4c150a88-6b39-458a-8e14-c13ccaab12e93002019-07-03T06:06:34Z2019-07-03T06:06:34Z2017-05-01ISSN: 2357-3732https://repositorio.unal.edu.co/handle/unal/68194http://bdigital.unal.edu.co/69227/In order to monitor the nutritional status of some crops based on plant spectroscopy and Sentinel 2 satellite images in Colombia, spectral reflectance data were taken between 350 and 2,500 nm with a FieldSpec 4 spectrometer in rubber, rice, sugar cane, maize, soybean, cashew, oil palm crops, pastures and natural savanna. Furthermore contents of mineral nutrients in leaves were determined. Several vegetation indexes and red edge positions were calculated using various methods from spectral data and Sentinel 2 satellite images and were correlated with leaf nutrient content. The results showed correlations between spectral indices, mainly those involving a spectral response in the red-edge range with the N, P, K and Cu although the best correlation coefficients were for N. First reflectance derivatives, transformations by the State Normal Variate and second reflectance derivatives showed great potential to monitor N content in crops. The green model index and the red-edge model computed from Sentinel 2 images had the best performance to monitor N content, although in the study area, presence of clouds affected the use of these images. The Sentinel 2 images allowed calculating some vegetation indexes obtained with other images, such as Landsat or SPOT, but additionally other indexes and calculations based on the bands of the red-edge, which is a great contribution to obtain more information of crops on their spatial and temporal variability.application/pdfspaUniversidad Nacional de Colombia - Sede Bogotá - Facultad de Ciencias Agrariashttps://revistas.unal.edu.co/index.php/agrocol/article/view/62875Universidad Nacional de Colombia Revistas electrónicas UN Agronomía ColombianaAgronomía ColombianaMartínez M., Luis Joel (2017) Relationship between crop nutritional status, spectral measurements and Sentinel 2 images. Agronomía Colombiana, 35 (2). pp. 205-215. ISSN 2357-373263 Agricultura y tecnologías relacionadas / Agriculturespectral reflectancespectroradiometrycrop nutrition.Relationship between crop nutritional status, spectral measurements and Sentinel 2 imagesArtículo de revistainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/ARTORIGINAL62875-364716-1-PB.pdfapplication/pdf1097767https://repositorio.unal.edu.co/bitstream/unal/68194/1/62875-364716-1-PB.pdfbb8f33cf8420dc59f78174c64beaa800MD51THUMBNAIL62875-364716-1-PB.pdf.jpg62875-364716-1-PB.pdf.jpgGenerated Thumbnailimage/jpeg8461https://repositorio.unal.edu.co/bitstream/unal/68194/2/62875-364716-1-PB.pdf.jpg4354519fd447a92daf9815b543d4a4e2MD52unal/68194oai:repositorio.unal.edu.co:unal/681942023-06-02 23:03:47.719Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co |
dc.title.spa.fl_str_mv |
Relationship between crop nutritional status, spectral measurements and Sentinel 2 images |
title |
Relationship between crop nutritional status, spectral measurements and Sentinel 2 images |
spellingShingle |
Relationship between crop nutritional status, spectral measurements and Sentinel 2 images 63 Agricultura y tecnologías relacionadas / Agriculture spectral reflectance spectroradiometry crop nutrition. |
title_short |
Relationship between crop nutritional status, spectral measurements and Sentinel 2 images |
title_full |
Relationship between crop nutritional status, spectral measurements and Sentinel 2 images |
title_fullStr |
Relationship between crop nutritional status, spectral measurements and Sentinel 2 images |
title_full_unstemmed |
Relationship between crop nutritional status, spectral measurements and Sentinel 2 images |
title_sort |
Relationship between crop nutritional status, spectral measurements and Sentinel 2 images |
dc.creator.fl_str_mv |
Martínez M., Luis Joel |
dc.contributor.author.spa.fl_str_mv |
Martínez M., Luis Joel |
dc.subject.ddc.spa.fl_str_mv |
63 Agricultura y tecnologías relacionadas / Agriculture |
topic |
63 Agricultura y tecnologías relacionadas / Agriculture spectral reflectance spectroradiometry crop nutrition. |
dc.subject.proposal.spa.fl_str_mv |
spectral reflectance spectroradiometry crop nutrition. |
description |
In order to monitor the nutritional status of some crops based on plant spectroscopy and Sentinel 2 satellite images in Colombia, spectral reflectance data were taken between 350 and 2,500 nm with a FieldSpec 4 spectrometer in rubber, rice, sugar cane, maize, soybean, cashew, oil palm crops, pastures and natural savanna. Furthermore contents of mineral nutrients in leaves were determined. Several vegetation indexes and red edge positions were calculated using various methods from spectral data and Sentinel 2 satellite images and were correlated with leaf nutrient content. The results showed correlations between spectral indices, mainly those involving a spectral response in the red-edge range with the N, P, K and Cu although the best correlation coefficients were for N. First reflectance derivatives, transformations by the State Normal Variate and second reflectance derivatives showed great potential to monitor N content in crops. The green model index and the red-edge model computed from Sentinel 2 images had the best performance to monitor N content, although in the study area, presence of clouds affected the use of these images. The Sentinel 2 images allowed calculating some vegetation indexes obtained with other images, such as Landsat or SPOT, but additionally other indexes and calculations based on the bands of the red-edge, which is a great contribution to obtain more information of crops on their spatial and temporal variability. |
publishDate |
2017 |
dc.date.issued.spa.fl_str_mv |
2017-05-01 |
dc.date.accessioned.spa.fl_str_mv |
2019-07-03T06:06:34Z |
dc.date.available.spa.fl_str_mv |
2019-07-03T06:06:34Z |
dc.type.spa.fl_str_mv |
Artículo de revista |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/article |
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info:eu-repo/semantics/publishedVersion |
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http://purl.org/coar/resource_type/c_6501 |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.content.spa.fl_str_mv |
Text |
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http://purl.org/redcol/resource_type/ART |
format |
http://purl.org/coar/resource_type/c_6501 |
status_str |
publishedVersion |
dc.identifier.issn.spa.fl_str_mv |
ISSN: 2357-3732 |
dc.identifier.uri.none.fl_str_mv |
https://repositorio.unal.edu.co/handle/unal/68194 |
dc.identifier.eprints.spa.fl_str_mv |
http://bdigital.unal.edu.co/69227/ |
identifier_str_mv |
ISSN: 2357-3732 |
url |
https://repositorio.unal.edu.co/handle/unal/68194 http://bdigital.unal.edu.co/69227/ |
dc.language.iso.spa.fl_str_mv |
spa |
language |
spa |
dc.relation.spa.fl_str_mv |
https://revistas.unal.edu.co/index.php/agrocol/article/view/62875 |
dc.relation.ispartof.spa.fl_str_mv |
Universidad Nacional de Colombia Revistas electrónicas UN Agronomía Colombiana Agronomía Colombiana |
dc.relation.references.spa.fl_str_mv |
Martínez M., Luis Joel (2017) Relationship between crop nutritional status, spectral measurements and Sentinel 2 images. Agronomía Colombiana, 35 (2). pp. 205-215. ISSN 2357-3732 |
dc.rights.spa.fl_str_mv |
Derechos reservados - Universidad Nacional de Colombia |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.license.spa.fl_str_mv |
Atribución-NoComercial 4.0 Internacional |
dc.rights.uri.spa.fl_str_mv |
http://creativecommons.org/licenses/by-nc/4.0/ |
dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Atribución-NoComercial 4.0 Internacional Derechos reservados - Universidad Nacional de Colombia http://creativecommons.org/licenses/by-nc/4.0/ http://purl.org/coar/access_right/c_abf2 |
eu_rights_str_mv |
openAccess |
dc.format.mimetype.spa.fl_str_mv |
application/pdf |
dc.publisher.spa.fl_str_mv |
Universidad Nacional de Colombia - Sede Bogotá - Facultad de Ciencias Agrarias |
institution |
Universidad Nacional de Colombia |
bitstream.url.fl_str_mv |
https://repositorio.unal.edu.co/bitstream/unal/68194/1/62875-364716-1-PB.pdf https://repositorio.unal.edu.co/bitstream/unal/68194/2/62875-364716-1-PB.pdf.jpg |
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