Abstract

ALZATE-MARIN, Estefany Johana; TORO-RESTREPO, Luis Jairo  and  SUAREZ-GOMEZ, July Andrea. Leaf spectrum analysis of three tropical timber species: Diomate ( Astronium graveolens), Choibá (Dipteryx oleifera), and Algarrobo (Hymenaea courbaril). Rev. Fac. Nac. Agron. Medellín [online]. 2024, vol.77, n.3, pp.10907-10919.  Epub Sep 30, 2024. ISSN 0304-2847.  https://doi.org/10.15446/rfnam.v77n3.112180.

This study analyzed the leaf spectral response of three native timber forest species in the tropical dry forest: Diomate (Astronium graveolens Jacq.), Choibá (Dipteryx oleifera Benth.), and Algarrobo (Hymenaea courbaril L.). The study was conducted at the León Morales Soto Arboretum and Palmetum, at the Universidad Nacional de Colombia in Medellín, Antioquia, Colombia. Spectral data from the leaves were collected in situ using the portable spectroradiometer ASD FieldSpec HandHeld-2, which operates with a spectral resolution of 1 nm (resampled to 10 nm) and covers a spectral range between 325 and 1,075 nm (limited to 400-900 nm). Based on the measurements, the behavior and spectral variability of the species were evaluated. One-factor Analysis of Variance and Mann-Whitney-Wilcoxon U-test were implemented in reflectance spectra to select the optimal narrow bands for species discrimination. The classification capacity of the selected narrow bands was assessed using the K-nearest neighbors' algorithm. It was found that A. graveolens and H. courbaril exhibited spectral signatures typical of healthy vegetation, while D. oleifera showed spectral changes during the early stages of senescence. Regarding spectral separability, 23 narrow bands in the visible region and near-infrared region were identified as optimal for distinguishing the plant species. The supervised classification algorithm applied to these 23 narrow bands achieved an overall accuracy of 95.8%. In conclusion, these findings provide valuable insights into the spectral response of important tropical species and contribute to their conservation efforts by enhancing understanding of their unique spectral characteristics in diverse and heterogeneous ecosystems like tropical forests.

Keywords : Classification; Leaves; Separability; Spectral signature; Spectroradiometry; Tropical forest.

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