Applying the NDVI from satellite images in delimiting management zones for annual crops
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Scientia Agrícola (Online) |
Texto Completo: | https://www.revistas.usp.br/sa/article/view/160711 |
Resumo: | The utilization of Normalized Difference Vegetation Index (NDVI) data obtained through satellite images can technically improve the process of delimiting management zones (MZ) for annual crops, resulting in socio-economic and environmental benefits. The aim of this study was to compare delimited MZ, using crop productivity data, with delimited MZ using the NDVI obtained from satellite images in areas under a no-tillage system. The study was carried out in three areas located in the state of Rio Grande do Sul, Brazil. Three crop productivity maps, from 2009 to 2015, were used for each area, whereby the NDVI was calculated for each crop productivity map using images from the Landsat series of satellites. Descriptive and geostatistical analysis were conducted to determine the productivity and NDVI data. The MZ were then delimited using the fuzzy c-means algorithm. Spearman’s correlation matrix was used to compare the methodologies used for delimiting the MZ. The MZ based on NDVI calculated from the satellite images correlated with the MZ based on crop productivity data (0.48 < r< 0.61), suggesting that the NDVI can replace or be complementary to productivity data in delimiting MZ for annual cropping systems. |
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USP-18 |
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Scientia Agrícola (Online) |
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Applying the NDVI from satellite images in delimiting management zones for annual cropsfuzzy c-means clusteringproductivity dataaerial imagesvegetation indexThe utilization of Normalized Difference Vegetation Index (NDVI) data obtained through satellite images can technically improve the process of delimiting management zones (MZ) for annual crops, resulting in socio-economic and environmental benefits. The aim of this study was to compare delimited MZ, using crop productivity data, with delimited MZ using the NDVI obtained from satellite images in areas under a no-tillage system. The study was carried out in three areas located in the state of Rio Grande do Sul, Brazil. Three crop productivity maps, from 2009 to 2015, were used for each area, whereby the NDVI was calculated for each crop productivity map using images from the Landsat series of satellites. Descriptive and geostatistical analysis were conducted to determine the productivity and NDVI data. The MZ were then delimited using the fuzzy c-means algorithm. Spearman’s correlation matrix was used to compare the methodologies used for delimiting the MZ. The MZ based on NDVI calculated from the satellite images correlated with the MZ based on crop productivity data (0.48 < r< 0.61), suggesting that the NDVI can replace or be complementary to productivity data in delimiting MZ for annual cropping systems.Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz2020-02-20info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/sa/article/view/16071110.1590/1678-992x-2018-0055Scientia Agricola; v. 77 n. 1 (2020); e20180055Scientia Agricola; Vol. 77 Núm. 1 (2020); e20180055Scientia Agricola; Vol. 77 No. 1 (2020); e201800551678-992X0103-9016reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/sa/article/view/160711/154963Copyright (c) 2020 Scientia Agricolainfo:eu-repo/semantics/openAccessDamian, Júnior MeloPias, Osmar Henrique de CastroCherubin, Maurício RobertoFonseca, Alencar Zachi daFornari, Ezequiel ZibettiSanti, Antônio Luis2019-08-05T18:27:37Zoai:revistas.usp.br:article/160711Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2019-08-05T18:27:37Scientia Agrícola (Online) - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
Applying the NDVI from satellite images in delimiting management zones for annual crops |
title |
Applying the NDVI from satellite images in delimiting management zones for annual crops |
spellingShingle |
Applying the NDVI from satellite images in delimiting management zones for annual crops Damian, Júnior Melo fuzzy c-means clustering productivity data aerial images vegetation index |
title_short |
Applying the NDVI from satellite images in delimiting management zones for annual crops |
title_full |
Applying the NDVI from satellite images in delimiting management zones for annual crops |
title_fullStr |
Applying the NDVI from satellite images in delimiting management zones for annual crops |
title_full_unstemmed |
Applying the NDVI from satellite images in delimiting management zones for annual crops |
title_sort |
Applying the NDVI from satellite images in delimiting management zones for annual crops |
author |
Damian, Júnior Melo |
author_facet |
Damian, Júnior Melo Pias, Osmar Henrique de Castro Cherubin, Maurício Roberto Fonseca, Alencar Zachi da Fornari, Ezequiel Zibetti Santi, Antônio Luis |
author_role |
author |
author2 |
Pias, Osmar Henrique de Castro Cherubin, Maurício Roberto Fonseca, Alencar Zachi da Fornari, Ezequiel Zibetti Santi, Antônio Luis |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Damian, Júnior Melo Pias, Osmar Henrique de Castro Cherubin, Maurício Roberto Fonseca, Alencar Zachi da Fornari, Ezequiel Zibetti Santi, Antônio Luis |
dc.subject.por.fl_str_mv |
fuzzy c-means clustering productivity data aerial images vegetation index |
topic |
fuzzy c-means clustering productivity data aerial images vegetation index |
description |
The utilization of Normalized Difference Vegetation Index (NDVI) data obtained through satellite images can technically improve the process of delimiting management zones (MZ) for annual crops, resulting in socio-economic and environmental benefits. The aim of this study was to compare delimited MZ, using crop productivity data, with delimited MZ using the NDVI obtained from satellite images in areas under a no-tillage system. The study was carried out in three areas located in the state of Rio Grande do Sul, Brazil. Three crop productivity maps, from 2009 to 2015, were used for each area, whereby the NDVI was calculated for each crop productivity map using images from the Landsat series of satellites. Descriptive and geostatistical analysis were conducted to determine the productivity and NDVI data. The MZ were then delimited using the fuzzy c-means algorithm. Spearman’s correlation matrix was used to compare the methodologies used for delimiting the MZ. The MZ based on NDVI calculated from the satellite images correlated with the MZ based on crop productivity data (0.48 < r< 0.61), suggesting that the NDVI can replace or be complementary to productivity data in delimiting MZ for annual cropping systems. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-02-20 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://www.revistas.usp.br/sa/article/view/160711 10.1590/1678-992x-2018-0055 |
url |
https://www.revistas.usp.br/sa/article/view/160711 |
identifier_str_mv |
10.1590/1678-992x-2018-0055 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://www.revistas.usp.br/sa/article/view/160711/154963 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2020 Scientia Agricola info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2020 Scientia Agricola |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz |
publisher.none.fl_str_mv |
Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz |
dc.source.none.fl_str_mv |
Scientia Agricola; v. 77 n. 1 (2020); e20180055 Scientia Agricola; Vol. 77 Núm. 1 (2020); e20180055 Scientia Agricola; Vol. 77 No. 1 (2020); e20180055 1678-992X 0103-9016 reponame:Scientia Agrícola (Online) instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Scientia Agrícola (Online) |
collection |
Scientia Agrícola (Online) |
repository.name.fl_str_mv |
Scientia Agrícola (Online) - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
scientia@usp.br||alleoni@usp.br |
_version_ |
1800222794021076992 |