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, 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.
Saved in:
| Main Author: | |
|---|---|
| Format: | Digital revista |
| Language: | eng |
| Published: |
Universidad Nacional de Colombia - Sede Bogotá - Facultad de Ciencias Agrarias
2017
|
| Online Access: | https://revistas.unal.edu.co/index.php/agrocol/article/view/62875 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| id |
oai:www.revistas.unal.edu.co:article-62875 |
|---|---|
| record_format |
ojs |
| institution |
UNAL |
| collection |
OJS |
| country |
Colombia |
| countrycode |
CO |
| component |
Revista |
| access |
En linea |
| databasecode |
rev-agrocol |
| tag |
revista |
| region |
America del Sur |
| libraryname |
tema Nacional de Bibliotecas de la UNAL |
| language |
eng |
| format |
Digital |
| author |
Martínez M., Luis Joel |
| spellingShingle |
Martínez M., Luis Joel Relationship between crop nutritional status, spectral measurements and Sentinel 2 images |
| author_facet |
Martínez M., Luis Joel |
| author_sort |
Martínez M., Luis Joel |
| title |
Relationship between crop nutritional status, spectral measurements and Sentinel 2 images |
| 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 |
| 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. |
| publisher |
Universidad Nacional de Colombia - Sede Bogotá - Facultad de Ciencias Agrarias |
| publishDate |
2017 |
| url |
https://revistas.unal.edu.co/index.php/agrocol/article/view/62875 |
| work_keys_str_mv |
AT martinezmluisjoel relationshipbetweencropnutritionalstatusspectralmeasurementsandsentinel2images AT martinezmluisjoel relacionentreelestadonutricionaldeloscultivoslasmedicionesespectralesylasimagenessentinel2 |
| _version_ |
1755913398077358080 |
| spelling |
oai:www.revistas.unal.edu.co:article-628752020-12-20T22:24:01Z Relationship between crop nutritional status, spectral measurements and Sentinel 2 images Relación entre el estado nutricional de los cultivos, las mediciones espectrales y las imágenes Sentinel 2 Martínez M., Luis Joel spectral reflectance spectroradiometry crop nutrition reflectancia espectral espectroradiometría nutrición de cultivos 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. Con el fin de monitorear el estado nutricional de algunos cultivos con base en espectroscopía de plantas e imágenes satelitales 2 en Colombia, se tomaron datos de reflectancia entre 350 y 2.500 nm con un espectrómetro FieldSpec 4 en cultivos de caucho, arroz, caña de azúcar, maíz, soya, marañón y palma de aceite, en pasturas y sabanas naturales y se determinó el contenido de nutrientes minerales en hojas. Se calcularon varios índices de vegetación y posiciones de borde rojo usando varios métodos, a partir de datos espectrales e imágenes de satélite Sentinel 2 y se correlacionaron con el contenido de nutrientes en las hojas. Los resultados mostraron correlaciones entre índices espectrales, principalmente aquellos que involucraron la respuesta espectral en el rango de borde rojo, con N, P, K y Cu aunque los mejores coeficientes de correlación fueron para N. La primera derivada de la reflectancia, su transformación por la state normal variate y la segundas derivadas mostraron un gran potencial para monitorear el contenido de N en los cultivos. El índice del modelo verde y el modelo de borde rojo calculados a partir de imágenes Sentinel 2 tuvieron el mejor desempeño para monitorear el contenido de N, aunque en las condiciones del área de estudio la presencia de nubes afectó el uso de estas imágenes. Las imágenes Sentinel 2 permitieron calcular algunos índices de vegetación que se obtienen con otras imágenes, como Landsat o SPOT, pero adicionalmente otros índices y cálculos basados en las bandas del borde rojo, lo cual es una gran contribución para obtener más información de los cultivos su variabilidad espacial y temporal. Universidad Nacional de Colombia - Sede Bogotá - Facultad de Ciencias Agrarias 2017-05-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://revistas.unal.edu.co/index.php/agrocol/article/view/62875 10.15446/agron.colomb.v35n2.62875 Agronomía Colombiana; Vol. 35 No. 2 (2017); 205-215 Agronomía Colombiana; Vol. 35 Núm. 2 (2017); 205-215 Agronomía Colombiana; v. 35 n. 2 (2017); 205-215 2357-3732 0120-9965 eng https://revistas.unal.edu.co/index.php/agrocol/article/view/62875/63793 Copyright (c) 2017 Agronomía Colombiana https://creativecommons.org/licenses/by-nc-sa/4.0 |