Texture descriptors and machine learning algorithms for mistletoe detection in urban forests using multispectral imagery

Paola Andrea Mejia-Zuluaga; Juan C. Valdiviezo-N; León Dozal

doi:10.1117/12.2684136

17 October 2023 Texture descriptors and machine learning algorithms for mistletoe detection in urban forests using multispectral imagery

Paola Andrea Mejia-Zuluaga, Juan C. Valdiviezo-N, León Dozal

Author Affiliations +

Proceedings Volume 12727, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXV; 127270R (2023) https://doi.org/10.1117/12.2684136
Event: SPIE Remote Sensing, 2023, Amsterdam, Netherlands

Abstract

In this study, we compare the performance of texture descriptors and spectral vegetation indices for the classification of a hemiparasitic plant that grows on host trees, known as mistletoe. For this purpose, we computed 180 image features, including GLCM, Gabor, and LBPs, as well as spectral vegetation indices, from multispectral aerial image sets. Our image feature database is then classified using Support Vector Machines, with optimized hyperparameters, and accuracy metrics are reported in order to evaluate the contribution of specific feature sets for our application. In addition, we make use of feature selection algorithms in order to determine which combination of descriptors improves the classification process. The study has important implications for the remote sensing community, as it can provide insights into the use of texture and spectral descriptors for classification of the mistletoe species known as Struthanthus Interruptus. The results of the study can be used to develop more effective tools to monitor the spread of the pest in urban parks, which can help to preserve trees and ensure their long-term health. Overall, the study contributes to the growing body of research on the use of remote sensing technologies, in conjunction with artificial intelligence techniques, to monitor urban environments.

Conference Presentation

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Paola Andrea Mejia-Zuluaga, Juan C. Valdiviezo-N, and León Dozal "Texture descriptors and machine learning algorithms for mistletoe detection in urban forests using multispectral imagery", Proc. SPIE 12727, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXV, 127270R (17 October 2023); https://doi.org/10.1117/12.2684136

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

Includes PDF, HTML & Video, when available