| Issue |
EPJ Web Conf.
Volume 305, 2024
6th International Conference on Applications of Optics and Photonics (AOP2024)
|
|
|---|---|---|
| Article Number | 00005 | |
| Number of page(s) | 4 | |
| DOI | https://doi.org/10.1051/epjconf/202430500005 | |
| Published online | 15 October 2024 | |
https://doi.org/10.1051/epjconf/202430500005
Vegetation health evaluation using cost-effective aerial reflectance measurements
CICECO Aveiro Institute of Materials, Physics department, University of Aveiro, 3810-193 Aveiro, Portugal.
* Corresponding author: anaisalucena@ua.pt
Published online: 15 October 2024
With the increase of wildfires, posing a significant threat to ecosystems, human life, and infrastructure, early detection and management of vegetation becomes crucial. The Green-Red Vegetation Index (GRVI) and the Excess Green (ExG) index are often used as a health indicator for plants. While the ExG index excels in identifying vegetation, the GRVI can distinguish between healthy and dead vegetation by calculating the difference between reflected green and red light. This study utilized a cost-effective commercial-off-the-shelf (COTS) drone (DJI MAVIC 2 PRO) and in-house software to retrieve the forementioned GRVI and ExG indices. These enable the classification of vegetation in rural areas to identify biomass fuel that requires cleaning to prevent the spread of fires. Validation through comparison tests with field samples demonstrated that the drone and software can effectively identify and categorize vegetation types, as well as estimate biomass fuel.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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