Data/hora: 25/06/2024 11:34:38

Biblioteca(s): 	Embrapa Semiárido.	
Data corrente: 	17/12/2013	
Data da última atualização: 	17/12/2013	
Autoria: 	GALVÍNCIO, J. D.; MOURA, M. S. B. de; SILVA, T. G. F da; SILVA, B. B. da; NAUE, C. R.	
Afiliação: 	JOSICLÊDA DOMICIANO GALVÍNCIO; MAGNA SOELMA BESERRA DE MOURA, CPATSA; THIERES GEORGE FREIRE DA SILVA; BERNARDO BARBOSA DA SILVA; CARINE ROSA NAUE.	
Título: 	Relationship between canopy and leaf spectral response in Savanna.	
Ano de publicação: 	2013	
Fonte/Imprenta: 	Revista Brasileira de Geografia Física, Recife, v. 6, n. 2, p. 341-355, 2013.	
ISSN: 	1984-2295	
Idioma: 	Inglês	
Conteúdo: 	Remote sensing and digital images are techniques that have the potential to assist in the analysis of terrestrial ecosystems in spatial scale. It is known that a forest monitoring is more accurate when you know the ecosystem features at different spatial scales. Relate measurements with remote sensing and obtained in the field (scales of detail) is challenging since several physical interference (biotic and abiotic) can provide errors in these relationships. One of the difficulties in obtaining estimates of parameters and vegetation biophysical variables with remote sensing are the spatial resolution is often low and this complicates the relationship between the regional data, location and detail. Thus, this study aims to evaluate the similarity and the correlation between canopy reflectance and leaf and propose a model that improves the estimates in leaf scale. We used cluster analysis, t-test, Pearson correlation and regression to analyze the similarity between samples, the degree of correlation and regression finally adopted for the model. The results were quite satisfactory and showed that there are significant differences between the reflectance in the leaf and canopy in Savannah for a significance level of 0.01. The model developed here can be using with high significance for high spatial resolution images such as IKONOS.	
Palavras-Chave: 	Analise de cluster; Floresta seca; Imagens digitais; Interação folha dossel; Natural resource; Regressão.	
Thesagro: 	Ecossistema; Recurso natural; Sensoriamento remoto.	
Categoria do assunto: 	P Recursos Naturais, Ciências Ambientais e da Terra	
URL: 	http://ainfo.cnptia.embrapa.br/digital/bitstream/item/94201/1/Magna-4.pdf	
Registro original: 	Embrapa Semiárido (CPATSA)	
Exemplares: 	CPATSA - (51357-1) - UPC - AP - DD -  -  -  - DIS