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...
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| Format: | Article |
| Language: | English |
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Centro Editorial of Facultad de Ciencias Agrarias, Universidad Nacional de Colombia
2017-05-01
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| Series: | Agronomía Colombiana |
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| Online Access: | https://revistas.unal.edu.co/index.php/agrocol/article/view/62875 |
| _version_ | 1828910131096584192 |
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| author | Luis Joel Martínez M. |
| author_facet | Luis Joel Martínez M. |
| author_sort | Luis Joel Martínez M. |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-13T18:38:21Z |
| format | Article |
| id | doaj.art-42dd7798972843ef98a7c0da8ced52d7 |
| institution | Directory Open Access Journal |
| issn | 0120-9965 2357-3732 |
| language | English |
| last_indexed | 2024-12-13T18:38:21Z |
| publishDate | 2017-05-01 |
| publisher | Centro Editorial of Facultad de Ciencias Agrarias, Universidad Nacional de Colombia |
| record_format | Article |
| series | Agronomía Colombiana |
| spelling | doaj.art-42dd7798972843ef98a7c0da8ced52d72022-12-21T23:35:17ZengCentro Editorial of Facultad de Ciencias Agrarias, Universidad Nacional de ColombiaAgronomía Colombiana0120-99652357-37322017-05-0135220521510.15446/agron.colomb.v35n2.6287547207Relationship between crop nutritional status, spectral measurements and Sentinel 2 imagesLuis Joel Martínez M.0Faculty of Agricultura Sciences, Universidad Nacional de Colombia, Bogota (Colombia).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.https://revistas.unal.edu.co/index.php/agrocol/article/view/62875spectral reflectancespectroradiometrycrop nutrition. |
| spellingShingle | Luis Joel Martínez M. Relationship between crop nutritional status, spectral measurements and Sentinel 2 images Agronomía Colombiana spectral reflectance spectroradiometry crop nutrition. |
| title | 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_short | Relationship between crop nutritional status, spectral measurements and Sentinel 2 images |
| title_sort | relationship between crop nutritional status spectral measurements and sentinel 2 images |
| topic | spectral reflectance spectroradiometry crop nutrition. |
| url | https://revistas.unal.edu.co/index.php/agrocol/article/view/62875 |
| work_keys_str_mv | AT luisjoelmartinezm relationshipbetweencropnutritionalstatusspectralmeasurementsandsentinel2images |