Please use this identifier to cite or link to this item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/256494
Research center of Embrapa/Collection: Embrapa Informática Agropecuária - Artigo em anais de congresso (ALICE)
Date Issued: 2009
Type of Material: Artigo em anais de congresso (ALICE)
Authors: ROMANI, L. A. S.
TRAINA, A. J. M.
SOUSA, E. P. M. de
ZULLO JÚNIOR, J.
AVILA, A. M. H.
RODRIGUES JR. J. F.
TRAINA JÚNIOR. C.
Additional Information: LUCIANA ALVIM SANTOS ROMANI, CNPTIA; AGMA J. M. TRAINA, Ciência da Computação/USP São Carlos; ELAINE P. M. DE SOUSA, Ciência da Computação/USP São Carlos; JURANDIR ZULLO JÚNIOR, CEPAGRI/ UNICAMP; ANA M. H. AVILA, CEPAGRI/UNICAMP; JOSE FERNANDO RODRIGUES JR., UFSCAR; CAETANO TRAINA JÚNIOR, Ciência da Computação/USP São Carlos.
Title: Computational framework to analyze agrometeorological, climate and remote sensing data: challenges and perspectives.
Publisher: In: CONGRESSO DA SOCIEDADE BRASILEIRA DE COMPUTAÇÃO, 29., 2009, Bento Gonçalves. Anais... Rio Grande do SUL: Instituto de Informática UFRGS.
Pages: p. 323-337.
Language: en
Notes: CSBC 2009.
Keywords: Dados agrometeorológicos
Dados de sensoriamento remoto
Dados climáticos
Teoria dos fractais
Mineração de dados
Técnicas de visualização
Dados massivos
Séries temporais
Cana-de-açúcar
Data mining
Sugar cane.
Description: In the past few years, improvements in the data acquisition technology have decreased the time interval of data gathering. Consequently, institutions have stored huge amounts of data such as climate time series and remote sensing images. Computational models to filter, transform, merge and analyze data from many different areas are complex and challenging. The complexity increases even more when combining several knowledge domains. Examples are research in climatic changes, biofuel production and environmental problems. A possible solution to the problem is the association of several computational techniques. Accordingly, this paper presents a framework to analyze, monitor and visualize climate and remote sensing data by employing methods based on fractal theory, data mining and visualization techniques. Initial experiments showed that the information and knowledge discovered from this framework can be employed to monitor sugar cane crops, helping agricultural entrepreneurs to make decisions in order to become more productive. Sugar cane is the main source to ethanol production in Brazil, and has a strategic importance for the country economy and to guarantee the Brazilian self-sufficiency in this important, renewable source of energy.
Thesagro: Agricultura.
NAL Thesaurus: Remote sensing
Agriculture.
Data Created: 2009-08-06
Appears in Collections:Artigo em anais de congresso (CNPTIA)

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