Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1110528
Título: Predicting plant species richness with satellite images in the largest dry forest nucleus in South America.
Autoria: MEDEIROS, E. S. e S.
MACHADO, C. C. C.
GALVÍNCIO, J. D.
MOURA, M. S. B. de
ARAÚJO, H. F. P. de
Afiliação: Edna Samara e Silva Medeiros; Célia Cristina Clemente Machado; Josiclêda Domiciano Galvíncio; MAGNA SOELMA BESERRA DE MOURA, CPATSA; Helder Farias Pereira de Araujo.
Ano de publicação: 2019
Referência: Journal of Arid Environments, v. 166, p. 43-50, 2019.
Conteúdo: Biodiversity assessment is considered an important indicator of ecosystem health by various initiatives world-wide. Satellite remote sensing (SRS) has allowed the development of tools that can assist with the practicalsearch of information related to species richness. The aim of this study was to test whether Landsat satellitespectral variables could be used as indicators of plant species diversity in the Caatinga, the largest nucleus of dryforest in South America. To obtain plant diversity data (richness and Shannon's index), an exhaustive search ofplant phytosociological studies carried out in Caatinga was conducted. Pearson's correlation and PCA analysiswas used to test the association between spectral variables and plant diversity. Regressions were used to test themodels that best explain species richness. The results indicate that a positive correlation exists between richnessand the near-infrared (NIR) spectral band (r = 0.744; p < 0.001). This spectral band was also responsible forexplaining better the variation of leaf level reflectance among eight species that occur in the region (df = 7;F = 26317.55; p < 0.001). Therefore, the NIR band variable can be used as an indicator of species richnessusing power and quadratic regression models, because they were one of the bestfit association recorded betweenspectral variable and plant diversity index, when compared to other studies in natural environments. Thus, weprovide important information about biodiversity that can be used in different researches, from ecological modeling for theoretical approaches to practical applications in Caatinga. The potential use of Landsat satelliteimagery to estimate species richness makes biodiversity assessments easier and provides a continuous source ofdata for monitoring in Brazilian semiarid region
Thesagro: Caatinga
Biodiversidade
Sensoriamento Remoto
Satélite
NAL Thesaurus: Biodiversity
Landsat
Remote sensing
Palavras-chave: Plantas da Caatinga
Floresta seca
América do Sul
Monitoramento
Digital Object Identifier: 10.1016/j.jaridenv.2019.03.001
Tipo do material: Artigo de periódico
Acesso: openAccess
Aparece nas coleções:Artigo em periódico indexado (CPATSA)

Arquivos associados a este item:
Arquivo Descrição TamanhoFormato 
Magna2.pdf5,92 MBAdobe PDFThumbnail
Visualizar/Abrir

FacebookTwitterDeliciousLinkedInGoogle BookmarksMySpace