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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Format: | Anais e Proceedings de eventos biblioteca |
Language: | pt_BR por |
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2018-01-08
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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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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. |
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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 |
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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. |
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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 |
work_keys_str_mv |
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