Índice de cobertura verde para imagens de altíssima resolução.

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.

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Main Authors: NEVES, M. C., NEVES JÚNIOR, O. R., LUIZ, A. J. B., SANCHES, I. D.
Other Authors: MARCOS CORREA NEVES, CNPMA; OTHON DA ROCHA NEVES JUNIOR, UFSC; ALFREDO JOSE BARRETO LUIZ, CNPMA; IEDA DEL'ARCO SANCHES, INPE.
Format: Anais e Proceedings de eventos biblioteca
Language:pt_BR
por
Published: 2018-01-08
Subjects:Image processing, Processamento de imagem, Visão computacional, Índice de área foliar, Imagem de satélite., Sensoriamento remoto, Agricultura., Remote sensing, Image analysis, Computer vision, Agriculture, Leaf area index,
Online Access:http://www.alice.cnptia.embrapa.br/alice/handle/doc/1084549
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spelling dig-alice-doc-10845492018-01-08T23:20:19Z Índice de cobertura verde para imagens de altíssima resolução. NEVES, M. C. NEVES JÚNIOR, O. R. LUIZ, A. J. B. SANCHES, I. D. MARCOS CORREA NEVES, CNPMA; OTHON DA ROCHA NEVES JUNIOR, UFSC; ALFREDO JOSE BARRETO LUIZ, CNPMA; IEDA DEL'ARCO SANCHES, INPE. Image processing Processamento de imagem Visão computacional Índice de área foliar Imagem de satélite. Sensoriamento remoto Agricultura. Remote sensing Image analysis Computer vision Agriculture Leaf area index 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. 2018-01-08T23:20:12Z 2018-01-08T23:20:12Z 2018-01-08 2017 2018-03-12T11:11:11Z Anais e Proceedings de eventos In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 18., 2017, Santos. Anais... Santos: Inpe, 2017. Trabalho 59957. http://www.alice.cnptia.embrapa.br/alice/handle/doc/1084549 pt_BR por openAccess p. 1273-1280.
institution EMBRAPA
collection DSpace
country Brasil
countrycode BR
component Bibliográfico
access En linea
databasecode dig-alice
tag biblioteca
region America del Sur
libraryname Sistema de bibliotecas de EMBRAPA
language pt_BR
por
topic Image processing
Processamento de imagem
Visão computacional
Índice de área foliar
Imagem de satélite.
Sensoriamento remoto
Agricultura.
Remote sensing
Image analysis
Computer vision
Agriculture
Leaf area index
Image processing
Processamento de imagem
Visão computacional
Índice de área foliar
Imagem de satélite.
Sensoriamento remoto
Agricultura.
Remote sensing
Image analysis
Computer vision
Agriculture
Leaf area index
spellingShingle Image processing
Processamento de imagem
Visão computacional
Índice de área foliar
Imagem de satélite.
Sensoriamento remoto
Agricultura.
Remote sensing
Image analysis
Computer vision
Agriculture
Leaf area index
Image processing
Processamento de imagem
Visão computacional
Índice de área foliar
Imagem de satélite.
Sensoriamento remoto
Agricultura.
Remote sensing
Image analysis
Computer vision
Agriculture
Leaf area index
NEVES, M. C.
NEVES JÚNIOR, O. R.
LUIZ, A. J. B.
SANCHES, I. D.
Índice de cobertura verde para imagens de altíssima resolução.
description 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.
author2 MARCOS CORREA NEVES, CNPMA; OTHON DA ROCHA NEVES JUNIOR, UFSC; ALFREDO JOSE BARRETO LUIZ, CNPMA; IEDA DEL'ARCO SANCHES, INPE.
author_facet MARCOS CORREA NEVES, CNPMA; OTHON DA ROCHA NEVES JUNIOR, UFSC; ALFREDO JOSE BARRETO LUIZ, CNPMA; IEDA DEL'ARCO SANCHES, INPE.
NEVES, M. C.
NEVES JÚNIOR, O. R.
LUIZ, A. J. B.
SANCHES, I. D.
format Anais e Proceedings de eventos
topic_facet Image processing
Processamento de imagem
Visão computacional
Índice de área foliar
Imagem de satélite.
Sensoriamento remoto
Agricultura.
Remote sensing
Image analysis
Computer vision
Agriculture
Leaf area index
author NEVES, M. C.
NEVES JÚNIOR, O. R.
LUIZ, A. J. B.
SANCHES, I. D.
author_sort NEVES, M. C.
title Índice de cobertura verde para imagens de altíssima resolução.
title_short Índice de cobertura verde para imagens de altíssima resolução.
title_full Índice de cobertura verde para imagens de altíssima resolução.
title_fullStr Índice de cobertura verde para imagens de altíssima resolução.
title_full_unstemmed Índice de cobertura verde para imagens de altíssima resolução.
title_sort índice de cobertura verde para imagens de altíssima resolução.
publishDate 2018-01-08
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1084549
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AT nevesjunioror indicedecoberturaverdeparaimagensdealtissimaresolucao
AT luizajb indicedecoberturaverdeparaimagensdealtissimaresolucao
AT sanchesid indicedecoberturaverdeparaimagensdealtissimaresolucao
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