Evaluation of the health status of Araucaria araucana trees using hyperspectral images
The Araucaria araucana is an endemic species from Chile and Argentina, which has a high biological, scientific and cultural value and since 2016 has shown a severe affection of leaf damage in some individuals, causing in some cases their death. The purpose of this research was to detect, from hypers...
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Universitat Politècnica de València
2018-12-01
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| Series: | Revista de Teledetección |
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| Online Access: | https://polipapers.upv.es/index.php/raet/article/view/10916 |
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| author | N. Medina P. Vidal R. Cifuentes J. Torralba F. Keusch |
| author_facet | N. Medina P. Vidal R. Cifuentes J. Torralba F. Keusch |
| author_sort | N. Medina |
| collection | DOAJ |
| description | The Araucaria araucana is an endemic species from Chile and Argentina, which has a high biological, scientific and cultural value and since 2016 has shown a severe affection of leaf damage in some individuals, causing in some cases their death. The purpose of this research was to detect, from hyperspectral images, the individuals of the Araucaria species (Araucaria araucana (Molina and K. Koch)) and its degree of disease, by isolating its spectral signature and evaluating its physiological state through indices of vegetation and positioning techniques of the inflection point of the red edge, in a sector of the Ralco National Reserve, Biobío Region, Chile. Seven images were captured with the HYSPEX VNIR-1600 hyperspectral sensor, with 160 bands and a random sampling was carried out in the study area, where 90 samples of Araucarias were collected. In addition, from the remote sensing techniques applied, spatial data mining was used, in which Araucarias were classified without symptoms of disease and with symptoms of disease. A 55.11% overall accuracy was obtained in the classification of the image, 53.4% in the identification of healthy Araucaria and 55.96% in the identification of affected Araucaria. In relation to the evaluation of their sanitary status, the index with the best percentage of accuracy is the MSR (70.73%) and the one with the lowest value is the SAVI (35.47%). The positioning technique of the inflection point of the red edge delivered an accuracy percentage of 52.18% and an acceptable Kappa index. |
| format | Article |
| id | doaj-art-7d2d5dacb5004f98a18b58b9b4cd1d6c |
| institution | Kabale University |
| issn | 1133-0953 1988-8740 |
| language | English |
| publishDate | 2018-12-01 |
| publisher | Universitat Politècnica de València |
| record_format | Article |
| series | Revista de Teledetección |
| spelling | doaj-art-7d2d5dacb5004f98a18b58b9b4cd1d6c2025-01-02T14:10:16ZengUniversitat Politècnica de ValènciaRevista de Teledetección1133-09531988-87402018-12-01052415310.4995/raet.2018.109167227Evaluation of the health status of Araucaria araucana trees using hyperspectral imagesN. Medina0P. Vidal1R. Cifuentes2J. Torralba3F. Keusch4Universidad MayorUniversidad MayorUniversidad MayorUniversitat Politècnica de ValènciaUniversidad MayorThe Araucaria araucana is an endemic species from Chile and Argentina, which has a high biological, scientific and cultural value and since 2016 has shown a severe affection of leaf damage in some individuals, causing in some cases their death. The purpose of this research was to detect, from hyperspectral images, the individuals of the Araucaria species (Araucaria araucana (Molina and K. Koch)) and its degree of disease, by isolating its spectral signature and evaluating its physiological state through indices of vegetation and positioning techniques of the inflection point of the red edge, in a sector of the Ralco National Reserve, Biobío Region, Chile. Seven images were captured with the HYSPEX VNIR-1600 hyperspectral sensor, with 160 bands and a random sampling was carried out in the study area, where 90 samples of Araucarias were collected. In addition, from the remote sensing techniques applied, spatial data mining was used, in which Araucarias were classified without symptoms of disease and with symptoms of disease. A 55.11% overall accuracy was obtained in the classification of the image, 53.4% in the identification of healthy Araucaria and 55.96% in the identification of affected Araucaria. In relation to the evaluation of their sanitary status, the index with the best percentage of accuracy is the MSR (70.73%) and the one with the lowest value is the SAVI (35.47%). The positioning technique of the inflection point of the red edge delivered an accuracy percentage of 52.18% and an acceptable Kappa index.https://polipapers.upv.es/index.php/raet/article/view/10916Imágenes hiperespectralesAraucaria araucanarespuesta espectralred edgeíndices de vegetaciónReserva Nacional Ralco |
| spellingShingle | N. Medina P. Vidal R. Cifuentes J. Torralba F. Keusch Evaluation of the health status of Araucaria araucana trees using hyperspectral images Revista de Teledetección Imágenes hiperespectrales Araucaria araucana respuesta espectral red edge índices de vegetación Reserva Nacional Ralco |
| title | Evaluation of the health status of Araucaria araucana trees using hyperspectral images |
| title_full | Evaluation of the health status of Araucaria araucana trees using hyperspectral images |
| title_fullStr | Evaluation of the health status of Araucaria araucana trees using hyperspectral images |
| title_full_unstemmed | Evaluation of the health status of Araucaria araucana trees using hyperspectral images |
| title_short | Evaluation of the health status of Araucaria araucana trees using hyperspectral images |
| title_sort | evaluation of the health status of araucaria araucana trees using hyperspectral images |
| topic | Imágenes hiperespectrales Araucaria araucana respuesta espectral red edge índices de vegetación Reserva Nacional Ralco |
| url | https://polipapers.upv.es/index.php/raet/article/view/10916 |
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