Automatic ordinal classification of olive plantations using deep learning and LiDAR data fusion

Authors

Alejandro Morales-Martín

F.J. Mesas-Carrascosa

J. Muñoz-Lorite

S. Cantón-Martínez

F.J. Pérez-Porras

Víctor Manuel Vargas-Yun

Pedro Antonio Gutiérrez

ISBN 9789004725232

Pages 538 - 545

Abstract

The growing demand for olive oil has driven the intensification of olive plantations in the Mediterranean Basin. In this context, monitoring and classifying parcels is essential to evaluate environmental and socioeconomic impacts and use of resources and agricultural inputs. This study introduces an innovative ordinal classification model to distinguish four olive plantation systems: traditional, low-density intensive, high-density intensive, and super intensive. Employing this methodology with public LiDAR-PNOA data, the model achieved 85% accuracy, demonstrating its robustness and efficacy. These findings enrich the SIGPAC database, supporting the Spanish Government in developing decision-making models for future agricultural planning.

BibTex Citation

@inproceedings{Morales2025Automatic,
	author = {Morales-Mart{\' i}n, Alejandro and Mesas-Carrascosa, F.J. and Mu{\~ n}oz-Lorite, J. and Cant{\' o}n-Mart{\' i}nez, S. and P{\' e}rez-Porras, F.J. and Vargas-Yun, V{\' i}ctor Manuel and Guti{\' e}rrez, Pedro Antonio},
	doi = {10.1163/9789004725232_070},
	year = {2025},
	pages = {538 -- 545},
	organization = {Wageningen Academic},
	title = {Automatic ordinal classification of olive plantations using deep learning and {LiDAR} data fusion},
	url = {https://brill.com/view/book/9789004725232/BP000070.xml},
}

BibTex Unicode Citation

@inproceedings{Morales2025Automatic,
	author = {Morales-Martín, Alejandro and Mesas-Carrascosa, F.J. and Muñoz-Lorite, J. and Cantón-Martínez, S. and Pérez-Porras, F.J. and Vargas-Yun, Víctor Manuel and Gutiérrez, Pedro Antonio},
	doi = {10.1163/9789004725232_070},
	year = {2025},
	pages = {538 -- 545},
	organization = {Wageningen Academic},
	title = {Automatic ordinal classification of olive plantations using deep learning and {LiDAR} data fusion},
	url = {https://brill.com/view/book/9789004725232/BP000070.xml},
}

APA Citation

Morales-Martín, A., Mesas-Carrascosa, F. J., Muñoz-Lorite, J., Cantón-Martínez, S., Pérez-Porras, F. J., Vargas-Yun, V. M., & Gutiérrez, P. A. (2025). Automatic ordinal classification of olive plantations using deep learning and LiDAR data fusion. 538–545. https://doi.org/10.1163/9789004725232_070

RIS Citation

TY  - CONF
AU  - Morales-Martín, Alejandro
AU  - Mesas-Carrascosa, F.J.
AU  - Muñoz-Lorite, J.
AU  - Cantón-Martínez, S.
AU  - Pérez-Porras, F.J.
AU  - Vargas-Yun, Víctor Manuel
AU  - Gutiérrez, Pedro Antonio
DA  - 2025///
C2  - 2025
DO  - 10.1163/9789004725232_070
ID  - temp_id_524718618654
PB  - Wageningen Academic
SP  - 538 - 545
TI  - Automatic ordinal classification of olive plantations using deep learn
ing and LiDAR data fusion
UR  - https://brill.com/view/book/9789004725232/BP000070.xml
ER  -

CV Citation

A. Morales-Martín (CA), F. Mesas-Carrascosa, J. Muñoz-Lorite, S. Cantón-Martínez, F. Pérez-Porras, V.M. Vargas-Yun, P.A. Gutiérrez (6/7). "Automatic ordinal classification of olive plantations using deep learning and LiDAR data fusion". pp. 538 - 545, 2025.