Detection of the vegetation index using biophysical parameters using UAVs

Jesus A. Alvarez-Cedillo; Teodoro Alvarez-Sanchez; Roberto Herrera-Charles

doi:10.1117/12.3028350

30 September 2024 Detection of the vegetation index using biophysical parameters using UAVs

Jesus A. Alvarez-Cedillo, Teodoro Alvarez-Sanchez, Roberto Herrera-Charles

Author Affiliations +

Proceedings Volume 13137, Applications of Digital Image Processing XLVII; 131370E (2024) https://doi.org/10.1117/12.3028350
Event: Optical Engineering + Applications, 2024, San Diego, California, United States

Abstract

The problem of detecting the vegetation index utilizing UAVs has been addressed in multiple articles in the literature, in which many special hardware and thermal or infrared cameras are adapted to improve its detection. The Vegetation Index is determined as a parameter calculated from the reflectance values at different wavelengths of the vegetation and is particularly sensitive to the vegetation cover. This article seeks to identify the vegetation index from its biophysical parameters. We help ourselves with artificial intelligence algorithms and machine learning algorithms. A semi-physical model was designed to estimate the ecosystem and establish the vegetation index correctly. The results will be validated by remote sensing. Finally, an ecological model will be developed to simulate the environmental impact on vegetation patterns and geographic plains. The proposed model successfully imitated the urban effect. Given these results, it was possible to predict better the impact of changing seasons in a defined geographic area.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jesus A. Alvarez-Cedillo, Teodoro Alvarez-Sanchez, and Roberto Herrera-Charles "Detection of the vegetation index using biophysical parameters using UAVs", Proc. SPIE 13137, Applications of Digital Image Processing XLVII, 131370E (30 September 2024); https://doi.org/10.1117/12.3028350

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE