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Early Monitoring of Health Status of Plantation-Grown Eucalyptus pellita at Large Spatial Scale via Visible Spectrum Imaging of Canopy Foliage Using Unmanned Aerial Vehicles3.84 MB
Published VersionCC BY V4.0, Open Access
Journal article
Early Monitoring of Health Status of Plantation-Grown Eucalyptus pellita at Large Spatial Scale via Visible Spectrum Imaging of Canopy Foliage Using Unmanned Aerial Vehicles
Forests, Vol.12(10), pp.1-19
2021
Abstract
Eucalyptus is a diverse genus from which several species are often deployed for commercial industrial tree plantation due to their desirable wood properties for utilization in both solid wood and fiber products, as well as their growth and productivity in many environments. In this study, a method for monitoring the health status of a 22.78 ha Eucalyptus pellita plantation stand was developed using the red-green-blue channels captured using an unmanned aerial vehicle. The ortho-image was generated, and visual atmospheric resistance index (VARI) indices were developed. Herein, four classification levels of pest and disease were generated using the VARI-green algorithm. The range of normalized VARI-green indices was between −2.0 and 2.0. The results identified seven dead trees (VARI-green index −2 to 0), five trees that were severely infected (VARI-green index 0 to 0.05), 967 trees that were mildly infected (VARI-green index 0.06 to 0.16), and 10,090 trees that were considered healthy (VARI-green index 0.17 to 2.00). The VARI-green indices were verified by manual ground-truthing and by comparison with normalized difference vegetation index which showed a mean correlation of 0.73. This study has shown practical application of aerial survey of a large-scale operational area of industrial tree plantation via low-cost UAV and RGB camera, to analyze VARI-green images in the detection of pest and disease.
Details
- Title
- Early Monitoring of Health Status of Plantation-Grown Eucalyptus pellita at Large Spatial Scale via Visible Spectrum Imaging of Canopy Foliage Using Unmanned Aerial Vehicles
- Authors
- Megat Najib Megat Mohamed Nazir (Author) - Universiti Putra MalaysiaRazak Terhem (Author) - Universiti Putra MalaysiaAhmad R Norhisham (Author) - Universiti Putra MalaysiaSheriza Mohd Razali (Author) - Universiti Putra MalaysiaRoger Meder (Author) - University of the Sunshine Coast, Queensland, Forest Industries Research Centre
- Publication details
- Forests, Vol.12(10), pp.1-19
- Publisher
- MDPI AG
- Date published
- 2021
- DOI
- 10.3390/f12101393
- ISSN
- 1999-4907
- Copyright note
- Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
- Organisation Unit
- University of the Sunshine Coast, Queensland; Forest Industries Research Centre
- Language
- English
- Record Identifier
- 99578905202621
- Output Type
- Journal article
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