Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1084549
Título: Índice de cobertura verde para imagens de altíssima resolução.
Autoria: NEVES, M. C.
NEVES JÚNIOR, O. R.
LUIZ, A. J. B.
SANCHES, I. D.
Afiliação: MARCOS CORREA NEVES, CNPMA; OTHON DA ROCHA NEVES JUNIOR, UFSC; ALFREDO JOSE BARRETO LUIZ, CNPMA; IEDA DEL'ARCO SANCHES, INPE.
Ano de publicação: 2017
Referência: In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 18., 2017, Santos. Anais... Santos: Inpe, 2017. Trabalho 59957.
Páginas: p. 1273-1280.
Conteúdo: The low altitude aerial images are becoming more common every day due to low cost and ease of use of platforms such as remotely piloted aircraft. The potential application of this type of data is very high. One example is the precision agriculture, a farming management concept based on observing, measuring and responding to inter and intra-field variability in crops, an activity than can greatly benefit from this technology. The low altitude of image acquisition allows very high level of scene details but aggravates problems such as lighting variation and image deformation. In addition, often common cameras are used in different situations altitude, inclination, lighting and camera setup. These specific characteristics in relation to the orbital data require development of new methods and approaches to exploit the potential of data and to mitigate problems and limitations. In this work, we present a proposal for a method that provides a green coverage index. It reflects the green pixels density in an area. The proposed index has similar applicability to vegetation indices but does not require near-infrared data, not available in common cameras. We show problems especially related to agriculture applications, present initial test results discuss the possibilities and limitations of the method.
Thesagro: Sensoriamento remoto
Agricultura
NAL Thesaurus: Remote sensing
Image analysis
Computer vision
Agriculture
Leaf area index
Palavras-chave: Image processing
Processamento de imagem
Visão computacional
Índice de área foliar
Imagem de satélite
Tipo do material: Artigo em anais e proceedings
Acesso: openAccess
Aparece nas coleções:Artigo em anais de congresso (CNPMA)

Arquivos associados a este item:
Arquivo Descrição TamanhoFormato 
2017AA30.pdf4,05 MBAdobe PDFThumbnail
Visualizar/Abrir

FacebookTwitterDeliciousLinkedInGoogle BookmarksMySpace