Data/hora: 05/06/2024 06:44:54

Biblioteca(s): 	Embrapa Algodão.	
Data corrente: 	22/08/2023	
Data da última atualização: 	22/08/2023	
Autoria: 	BRITO FILHO, A. L. de; CARNEIRO, F. M.; RONTANI, F.; SILVA, R. P. da; BRANDÃO, Z. N.; SILVA JUNIOR, C. A. da; SHIRATSUCHI, L. S.	
Afiliação: 	ARMANDO LOPES DE BRITO FILHO, UNESP; FRANCIELE MORLIN CARNEIRO, UTFPR; FAGNER RONTANI, LOUISIANA STATE UNIVERSITY; ROVERSON PEREIRA DA SILVA, UNESP; ZIANY NEIVA BRANDÃO, CNPA; CARLOS ANTÔNIO DA SILVA JUNIOR, UNEMAT; LUCIANO SHOZO SHIRATSUCHI, LOUISIANA STATE UNIVERSITY.	
Título: 	Comparison between active and passive optics sensors to monitor spectral behavior during rice growth stages.	
Ano de publicação: 	2023	
Fonte/Imprenta: 	In: SILVA-MATOS, R. R. S. da; DOIHARA, I. P.; LINHARES, S. C. (org.). Medio ambiente: Agricultura, desarrollo y sustentabilidad 2. Ponta Grossa, PR: Atena, 2023. c. 1.	
Páginas: 	p. 1-9.	
ISBN: 	978-65-258-1530-5	
DOI: 	https://doi.org/10.22533/at.ed.3052302081	
Idioma: 	Inglês	
Conteúdo: 	The use of existing technologies within the science of remote sensing has increasingly contributed to the development of agriculture. Thus, our objective with this research was to compare performance to quality read between active and passive optics sensors are considerably greater to monitor spectral behavior of rice at different dates during their growth stages. This project will present correlations between active optical sensors with Sentinel 2 (S-2) satellite spectral bands. The vegetation indices to be used were: NDVI and CIRE. All the data simple linear regression and Pearson correlations were performed to compare active and passive sensors (satellite imageries data) with active crop canopy sensor technology. The averaged data were used along rice phenology to illustrate the dynamic of both sensors during the entire rice season. The active sensor presented better results than the passive sensor due to its being more stable for data collection under some different weather conditions.	
Palavras-Chave: 	Análise de regressão; Arroz de Louisiana; Correlação de Pearsons; Emissão de saturação; Imagens de satélite; Louisiana rice; Pearsons correlations; Satellite imageries; Saturation issue.	
Thesagro: 	Agricultura; Arroz; Desenvolvimento Sustentável; Meio Ambiente; Sensoriamento Remoto.	
Thesaurus Nal: 	Agriculture; Environment; Regression analysis; Remote sensing; Sustainable agriculture; Sustainable development.	
Categoria do assunto: 	P Recursos Naturais, Ciências Ambientais e da Terra	
Registro original: 	Embrapa Algodão (CNPA)	
Exemplares: 	CNPA - (29081-1) - ADD - PL - DD -  -  -  - DIS