Applying the NDVI from satellite images in delimiting management zones for annual crops
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,...
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| Published in: | Scientia agricola Vol. 77; no. 1 |
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| Format: | Journal Article |
| Language: | English |
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Escola Superior de Agricultura "Luiz de Queiroz"
2020
Universidade de São Paulo |
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| Abstract | 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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| AbstractList | 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. |
| Author | Fornari, Ezequiel Zibetti Pias, Osmar Henrique de Castro Fonseca, Alencar Zachi da Santi, Antônio Luis Cherubin, Maurício Roberto Damian, Júnior Melo |
| AuthorAffiliation | Universidade de São Paulo Universidade Federal do Rio Grande do Sul Universidade Federal de Santa Maria |
| AuthorAffiliation_xml | – name: Universidade de São Paulo – name: Universidade Federal do Rio Grande do Sul – name: Universidade Federal de Santa Maria |
| Author_xml | – sequence: 1 givenname: Júnior Melo orcidid: 0000-0002-1692-6751 surname: Damian fullname: Damian, Júnior Melo organization: Universidade de São Paulo, Brasil – sequence: 2 givenname: Osmar Henrique de Castro orcidid: 0000-0003-0325-3452 surname: Pias fullname: Pias, Osmar Henrique de Castro organization: Universidade Federal de Rio Grande do Sul, Brasil – sequence: 3 givenname: Maurício Roberto orcidid: 0000-0001-7920-8362 surname: Cherubin fullname: Cherubin, Maurício Roberto organization: Universidade de São Paulo, Brasil – sequence: 4 givenname: Alencar Zachi da orcidid: 0000-0002-6678-5037 surname: Fonseca fullname: Fonseca, Alencar Zachi da organization: Universidade Federal de Santa Maria, Brasil – sequence: 5 givenname: Ezequiel Zibetti orcidid: 0000-0002-0513-2120 surname: Fornari fullname: Fornari, Ezequiel Zibetti organization: Universidade Federal de Santa Maria, Brasil – sequence: 6 givenname: Antônio Luis orcidid: 0000-0002-4773-4912 surname: Santi fullname: Santi, Antônio Luis organization: Universidade Federal de Santa Maria, Brasil |
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| Keywords | vegetation index fuzzy c-means clustering aerial images productivity data |
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| Title | Applying the NDVI from satellite images in delimiting management zones for annual crops |
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