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https://repositorio.inpa.gov.br/handle/1/16831
Título: | Recognizing Amazonian tree species in the field using bark tissues spectra |
Autor: | Hadlich, Hilana Louise Durgante, Flávia Machado Santos, Joaquim dos Higuchi, Niro Chambers, Jeffrey Quintin Vicentini, Alberto |
Palavras-chave: | Histology Infrared Devices Near Infrared Spectroscopy Reflection Spectrometers Tissue Inner Bark Outer Bark Reflectance Data Species Identification Vis-nirs Forestry Bark Cell Forest Management Herbarium Infrared Spectroscopy Spectral Reflectance Spectrometer Tree Tropical Forest Wavelength Histology Phloem Reflection Species Identification Spectrometers Tissue Amazonia |
Data do documento: | 2018 |
Revista: | Forest Ecology and Management |
É parte de: | Volume 427, Pags. 296-304 |
Abstract: | The identification of tree species in the field is often a subjective process and misidentifications cause many problems for forest management in the Amazon Forest. Near infrared spectra from dried leaves of herbarium specimens are able to distinguish species in tropical forests. However, toolsto improve species identification directly in the field are needed. In this study, we tested whether spectral reflectance of bark tissues (rhytidome and phloem) collected with a portable spectrometer in the field can be used for the discrimination of tree species. Spectral data was collected for 254 trees of 8 families, 10 genera and 11 species from terra firme forests in Central Amazon with an ASD field spectrometer. Data consisted of reflectance values within 350–2500 nm wavelengths. We compared the rate of correct species recognition for different datasets using linear discriminant models. The rate of correct species assignment using this technique was 98% when using spectra from the inner bark (phloem) and 94% with outer bark (rhytidome) spectra. We suggest that the application of this technique can improve the quality of species identification directly during field inventories, fostering better forest management practices. © 2018 Elsevier B.V. |
DOI: | 10.1016/j.foreco.2018.06.002 |
Aparece nas coleções: | Artigos |
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