Clasificación supervisada, evaluación multicriterio y modelos de localización-asignación para instalaciones de destilación de aceite esencial de Cistus ladanifer

Carlos Pérez-Izquierdo; Fernando Pulido

doi:10.4995/raet.2024.21700

Authors

Carlos Pérez-Izquierdo Universidad de Extremadura
Fernando Pulido Universidad de Extremadura https://orcid.org/0000-0001-5620-1918

DOI:

https://doi.org/10.4995/raet.2024.21700

Keywords:

Cistus ladanifer, essential oil, supervised classification, multi-criteria evaluation, location-allocation

Abstract

Cistus ladanifer L. (rockrose) is a shrub species widespread in the Mediterranean region and highly valuable for the cosmetic, pharmacological and agri-food industries. Despite its value, this resource remains under-exploited and presents great spatial variability and heterogeneous extraction conditions. This study aims to develop a methodology to locate optimal areas for the installation of C. ladanifer essential oil distillation plants that will allow its extraction in an efficient and profitable way. Remote sensing techniques based on supervised classifications of pixels and objects have been applied to determine the distribution and surface of this resource. The classification was conducted using 2018 Sentinel-2 imagery, digital elevation models and the following six classification algorithms: minimum distance, Mahalanobis distance, maximum likelihood, Spectral Angle Mapper, support vector machines and neural networks. GIS tools such as multi-criteria evaluation analysis and location- allocation models allowed us to obtain and connect the supply points with the highest resource suitability and the ideal demand sites for the facilities. Maximum likelihood, support vector machines and neural networks classifiers achieved classification accuracies above 90 % in overall accuracy and Kappa coefficient. The total area of potentially exploitable rockrose obtained in the classification was 20 889 ha, from which 15 241 ha (72.96 %) were viable for harvesting. The installation of two distillation plants showed an efficient spatial coverage distribution to exploit this resource in the study area. The methodology is considered a valuable tool to efficiently and sustainably determine the optimal location of distillation plants.

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Author Biographies

Carlos Pérez-Izquierdo, Universidad de Extremadura

Instituto de Investigación de la Dehesa (INDEHESA)

Fernando Pulido, Universidad de Extremadura

Instituto de Investigación de la Dehesa (INDEHESA)

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