Assessment of Image-Texture Improvement Applied to Unmanned Aerial Vehicle Imagery for the Identification of Biotic Stress in Espeletia. Case Study: Moorlands of Chingaza (Colombia)
Fuente:
Redalyc
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Artículo científico |
| Sprache: | en |
| Veröffentlicht: |
Universidad Militar Nueva Granada
2020
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1876422317817462784 |
|---|---|
| author | Laura Martín |
| author_facet | Laura Martín |
| contents | Assessment of Image-Texture Improvement Applied to Unmanned Aerial Vehicle Imagery for the Identification of Biotic Stress in Espeletia. Case Study: Moorlands of Chingaza (Colombia) Laura Martín Javier Medina Erika Upegui Ingeniería Espeletia Biotic stress maximum likelihood texture measurements support vector machine Espeletia is one of the most representative endemic species of moorland ecosystems and is currently being affected by biotic stress. Meanwhile, the analysis of images obtained by means of unmanned aerial vehicle imagery has proved its usefulness in environmental monitoring activities. This work is aimed at establishing whether image-texture analysis applied to unmanned aerial vehicle imagery from Moorlands of Chingaza (Colombia) allows the identification of biotic stress in Espeletia. To this end, this study makes use of occurrence analysis, gray-level co-occurrence matrix, and Fourier transform. Identification of healthy/unhealthy Espeletia is conducted using maximum likelihood tests and support vector machines. The results are assessed based on overall accuracy, the kappa coefficient and Bhattacharyya distance. By combining spectral and image-texture information, it is shown that classification accuracy increases, reaching kappa coefficient values of 0.9824 and overall accuracy values of 99.51%. 2020 artículo científico 0124-8170 https://www.redalyc.org/articulo.oa?id=91164537003 https://www.redalyc.org/journal/911/91164537003/ https://www.redalyc.org/journal/911/91164537003/html/ https://www.redalyc.org/journal/911/91164537003/91164537003.epub https://www.redalyc.org/journal/911/91164537003/movil 10.18359/rcin.3342 en http://www.redalyc.org/revista.oa?id=911 Ciencia e Ingeniería Neogranadina application/pdf Universidad Militar Nueva Granada Ciencia e Ingeniería Neogranadina (Colombia) Num.1 Vol.30 |
| format | Artículo científico |
| id | redalyc_91164537003 |
| institution | Redalyc |
| language | en |
| publishDate | 2020 |
| publisher | Universidad Militar Nueva Granada |
| spellingShingle | Assessment of Image-Texture Improvement Applied to Unmanned Aerial Vehicle Imagery for the Identification of Biotic Stress in Espeletia. Case Study: Moorlands of Chingaza (Colombia) Laura Martín Ingeniería Espeletia Biotic stress maximum likelihood texture measurements support vector machine Assessment of Image-Texture Improvement Applied to Unmanned Aerial Vehicle Imagery for the Identification of Biotic Stress in Espeletia. Case Study: Moorlands of Chingaza (Colombia) Laura Martín Javier Medina Erika Upegui Ingeniería Espeletia Biotic stress maximum likelihood texture measurements support vector machine Espeletia is one of the most representative endemic species of moorland ecosystems and is currently being affected by biotic stress. Meanwhile, the analysis of images obtained by means of unmanned aerial vehicle imagery has proved its usefulness in environmental monitoring activities. This work is aimed at establishing whether image-texture analysis applied to unmanned aerial vehicle imagery from Moorlands of Chingaza (Colombia) allows the identification of biotic stress in Espeletia. To this end, this study makes use of occurrence analysis, gray-level co-occurrence matrix, and Fourier transform. Identification of healthy/unhealthy Espeletia is conducted using maximum likelihood tests and support vector machines. The results are assessed based on overall accuracy, the kappa coefficient and Bhattacharyya distance. By combining spectral and image-texture information, it is shown that classification accuracy increases, reaching kappa coefficient values of 0.9824 and overall accuracy values of 99.51%. 2020 artículo científico 0124-8170 https://www.redalyc.org/articulo.oa?id=91164537003 https://www.redalyc.org/journal/911/91164537003/ https://www.redalyc.org/journal/911/91164537003/html/ https://www.redalyc.org/journal/911/91164537003/91164537003.epub https://www.redalyc.org/journal/911/91164537003/movil 10.18359/rcin.3342 en http://www.redalyc.org/revista.oa?id=911 Ciencia e Ingeniería Neogranadina application/pdf Universidad Militar Nueva Granada Ciencia e Ingeniería Neogranadina (Colombia) Num.1 Vol.30 |
| title | Assessment of Image-Texture Improvement Applied to Unmanned Aerial Vehicle Imagery for the Identification of Biotic Stress in Espeletia. Case Study: Moorlands of Chingaza (Colombia) |
| topic | Ingeniería Espeletia Biotic stress maximum likelihood texture measurements support vector machine |
| url | https://www.redalyc.org/articulo.oa?id=91164537003 https://www.redalyc.org/journal/911/91164537003/ https://www.redalyc.org/journal/911/91164537003/html/ https://www.redalyc.org/journal/911/91164537003/91164537003.epub https://www.redalyc.org/journal/911/91164537003/movil |