2020-01-162020-01-162008-04-08ALMEIDA, Arthur da Costa. Metodologia integrada utilizando sensoriamento remoto em redes neurais artificiais na quantificação do potencial de Biomassa florestal na Amazônia. Orientadora: Brigida Ramati Pereira da Rocha. 2008. 135 f. Tese (Doutorado em Engenharia Elétrica). Instituto de Tecnológia, Universidade Federal do Pará, Belém, 2008. Disponível em: http://repositorio.ufpa.br/jspui/handle/2011/12165. Acesso em:.https://repositorio.ufpa.br/handle/2011/12165Pattern recognition and pattern classification in digital images is a very important skill, today. With them, it is possible to recognize and identify target objects in those images. This work proposes an integrated methodology for pattern recognition related to biomass in the Amazon tropical rainforest to extract information about bioenergetics potential for electric energy production for use with isolated Amazonian communities. To achieve this aim, information gathered about forest inventory was mixed with pattern classification and recognition in medium resolution satellite imagery such as those from LANDSAT and CBERS. The approach used in this work comes from the computational intelligence area, using artificial neural networks equipped with radial basis functions and Kohonen´s self organizing maps. The results serve as input to a geographical information system application which creates and manages a geographical database for energetic planning with renewable energy resources applicable to isolated Amazonian communities.Acesso AbertoBiomassaEnergia renovávelReconhecimento de padrõesRedes neurais artificiaisSistemas de informações geográficasBiomassRenewable energyPattern recognitionGeographical information systemsArtificial neural networksTeseCNPQ::ENGENHARIAS::ENGENHARIA ELETRICAFONTES RENOVÁVEISSISTEMAS DE ENERGIA ELÉTRICA