Data/hora: 12/05/2024 14:52:26

Biblioteca(s): 	Embrapa Territorial.	
Data corrente: 	17/02/2017	
Data da última atualização: 	03/05/2019	
Autoria: 	GREGO, C. R.; MANJOLIN, R. C.; NOGUEIRA, S. F.; RODRIGUES, C. A. G.; SILVA, G. B. S. da; CONCEIÇÃO, M. P. C.; HERLING, V. R.	
Afiliação: 	CELIA REGINA GREGO, CNPM; Rodolfo Correa Manjolin, PIBIC-CNPq / CNPM; SANDRA FURLAN NOGUEIRA, CNPM; CRISTINA APARECIDA G RODRIGUES, CNPM; GUSTAVO BAYMA SIQUEIRA DA SILVA, CNPM; Maurício P. C. Conceição, PIBIC/CNPq / CNPM; Valdo Rodrigues Herling, Universidade de São Paulo.	
Título: 	Geostatistical Analysis of NDVI in rotational and continuous grazing pastures	
Ano de publicação: 	2016	
Fonte/Imprenta: 	In: INTERNATIONAL SYMPOSIUM ON GREENHOUSE GASES IN AGRICULTURE, 2., 2016, Campo Grande, MS. Proceedings... Brasília, DF: Embrapa, 2016.	
Páginas: 	p. 121-125.	
Série: 	(Embrapa Gado de Corte. Documentos, 216).	
ISSN: 	1983-974X	
Idioma: 	Inglês	
Conteúdo: 	Livestock rearing is an important economical activity in Brazil, and its production is affected by pasture management methods. In this context, the use of geostatistics to analyze the spatial variability of the pastures? vegetation indices is valuable for understanding how management methods influence livestock production. Geostatistics is a tool that considers spatial dependency to interpolate data with no tendency and with minimum variance, which enables the production of precise maps using interpolated values at places that were not sampled (Vieira, 2000). The spatialization of vegetation indices such as the Normalized Difference Vegetation Index (NDVI) helps to evaluate the quality of pastures and to identify areas which may undergo a degradation process. In this study we intended to spatially evaluate two pasture management methods, rotational grazing and continuous grazing, using geostatistics and the NDVI as an indicator obtained from Landsat images of an area located in Pirassununga, São Paulo, Brazil, taken in 2011.	
Thesaurus Nal: 	Geostatistics; Landsat; Normalized difference vegetation index; Remote sensing.	
Categoria do assunto: 	P Recursos Naturais, Ciências Ambientais e da Terra	
URL: 	http://ainfo.cnptia.embrapa.br/digital/bitstream/item/156046/1/Grego-Manjolin-Nogueira-Rodrigues-Bayma-Conceicao-SIGEE2016-p121a125.pdf	
Registro original: 	Embrapa Territorial (CNPM)	
Exemplares: 	CNPM - (4797-1) - UPC - AA - DD - 16/061 - AA - 2016.061 - DIS