Predicting plant species richness with satellite images in the largest dry forest nucleus in South America

Biodiversity assessment is considered an important indicator of ecosystem health by various initiatives worldwide. Satellite remote sensing (SRS) has allowed the development of tools that can assist with the practical search of information related to species richness. The aim of this study was to te...

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Bibliographic Details
Published in:Journal of arid environments 2019-07, Vol.166, p.43-50
Main Authors: Samara e Silva Medeiros, Edna, Machado, Célia Cristina Clemente, Galvíncio, Josiclêda Domiciano, de Moura, Magna Soelma Beserra, de Araujo, Helder Farias Pereira
Format: Article
Language:English
Subjects:
Biodiversity
Caatinga
Landsat
Remote sensing
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Summary:Biodiversity assessment is considered an important indicator of ecosystem health by various initiatives worldwide. Satellite remote sensing (SRS) has allowed the development of tools that can assist with the practical search of information related to species richness. The aim of this study was to test whether Landsat satellite spectral variables could be used as indicators of plant species diversity in the Caatinga, the largest nucleus of dry forest in South America. To obtain plant diversity data (richness and Shannon's index), an exhaustive search of plant phytosociological studies carried out in Caatinga was conducted. Pearson's correlation and PCA analysis was used to test the association between spectral variables and plant diversity. Regressions were used to test the models that best explain species richness. The results indicate that a positive correlation exists between richness and the near-infrared (NIR) spectral band (r = 0.744; p 
ISSN:0140-1963
1095-922X
DOI:10.1016/j.jaridenv.2019.03.001