Data/hora: 24/09/2024 09:43:56

Biblioteca(s): 	Embrapa Agricultura Digital.	
Data corrente: 	04/12/2014	
Data da última atualização: 	08/01/2020	
Autoria: 	GONÇALVES, R. R. V.; ZULLO JÚNIOR, J.; AMARAL, B. F.; COLTRI, P. P.; SOUSA, E. P. M.; ROMANI, L. A. S.	
Afiliação: 	RENATA RIBEIRO DO VALLE GONÇALVES, Cepagri/Unicamp; JURANDIR ZULLO JÚNIOR, Cepagri/Unicamp; BRUNO FERRAZ DO AMARAL, ICMC/USP; PRISCILA PEREIRA COLTRI, Cepagri/Unicamp; ELAINE PARROS MACHADO DE SOUSA, ICMC/USP; LUCIANA ALVIM SANTOS ROMANI, CNPTIA.	
Título: 	Land use temporal analysis through clustering techniques on satellite image time series.	
Ano de publicação: 	2014	
Fonte/Imprenta: 	In: INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM; CANADIAN SYMPOSIUM ON REMOTE SENSING, 35., 2014, Québec. Energy and our changing planet: proceedings. [S.l.]: IEEE, 2014.	
Páginas: 	p. 2173-2176.	
Idioma: 	Inglês	
Notas: 	IGARSS 2014.	
Conteúdo: 	Satellite images time series have been used to study land surface, such as identification of forest, water, urban areas, as well as for meteorological applications. However, for knowledge discovery in large remote sensing databases can be use clustering techniques in multivariate time series. The clustering technique on three-dimensional time series of NDVI, albedo and surface temperature from AVHRR/NOAA satellite images was used, in this study, to map the variability of land use. This approach was suitable to accomplish the temporal analysis of land use. Additionally, this technique can be used to identify and analyze dynamics of land use and cover being useful to support researches in agriculture, even considering low spatial resolution satellite images. The possibility of extracting time series from satellite images, analyzing them through data mining techniques, such as clustering, and visualizing results in geospatial way is an important advance and support to agricultural monitoring tasks.	
Palavras-Chave: 	Albedo; Índice de vegetação; K-means; Séries temporais; Temperatura da superfície.	
Thesaurus Nal: 	surface temperature; Time series analysis; Vegetation index.	
Categoria do assunto: 	X Pesquisa, Tecnologia e Engenharia	
Registro original: 	Embrapa Agricultura Digital (CNPTIA)	
Exemplares: 	CNPTIA - (18081-1) - UPC - AA - DD -  -  -  - DIS