Data of plant diversity, spectral reflectance at specie level and satellite spectral variables from the largest dry forest nucleus in South America

The use of satellite remote sensing makes it possible to acquire useful information about the environment, since it presents tools capable of assisting the practical search of information related to species richness. Here we present data on richness and Shannon index from phytosociological researches, vegetation indices and individual bands spectral reflectance from satellite images and leaf-level spectral reflectance from eight Caatinga species. For further interpretation of the data presented in this article, please see the research article ?Predicting plant species richness with satellite images in the largest dry forest nucleus in South America?

Saved in:
Bibliographic Details
Main Authors: MEDEIROS, E. S. e S, MACHADO, C. C. C., GALVÍNCIO, J. D., MOURA, M. S. B. de, ARAÚJO, H. F. P. de
Other Authors: Edna Samara e Silva Medeiros; Célia Cristina Clemente Machado; Josiclêda Domiciano Galvíncio; MAGNA SOELMA BESERRA DE MOURA, CPATSA; Helder Farias Pereira de Araujo.
Format: Artigo de periódico biblioteca
Language:English
eng
Published: 2019-10-30
Subjects:Imagem de satelite, Reflectância, Sensoriamento Remoto, Vegetação Nativa, Biodiversidade, Clima, Remote sensing, Climatic zones,
Online Access:http://www.alice.cnptia.embrapa.br/alice/handle/doc/1113640
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The use of satellite remote sensing makes it possible to acquire useful information about the environment, since it presents tools capable of assisting the practical search of information related to species richness. Here we present data on richness and Shannon index from phytosociological researches, vegetation indices and individual bands spectral reflectance from satellite images and leaf-level spectral reflectance from eight Caatinga species. For further interpretation of the data presented in this article, please see the research article ?Predicting plant species richness with satellite images in the largest dry forest nucleus in South America?