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Determination of vegetation cover index under different soil management systems of cover plants by using an unmanned aerial vehicle with an onboard digital photographic camera

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Determination of vegetation cover index under different soil management systems of cover plants by using an unmanned aerial vehicle with an onboard digital photographic camera. / Beniaich, Adnane; Naves Silva, Marx Leandro; Avalos, Fabio Arnaldo Pomar; Menezes, Michele Duarte; Candido, Bernardo M.

In: Semina-Ciencias Agrarias, Vol. 40, No. 1, 01.2019, p. 49-66.

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@article{13fd667723ef4bd68ee7bd0f756eae89,
title = "Determination of vegetation cover index under different soil management systems of cover plants by using an unmanned aerial vehicle with an onboard digital photographic camera",
abstract = "The permanent monitoring of vegetation cover is important to guarantee a sustainable management of agricultural activities, with a relevant role in the reduction of water erosion. This monitoring can be carried out through different indicators such as vegetation cover indices. In this study, the vegetation cover index was obtained using uncalibrated RGB images generated from a digital photographic camera on an unmanned aerial vehicle (UAV). In addition, a comparative study with 11 vegetation indices was carried out. The vegetation indices CIVE and EXG presented a better performance and the index WI presented the worst performance in the vegetation classification during the cycles of jack bean and millet, according to the overall accuracy and Kappa coefficient. Vegetation indices were effective tools in obtaining soil cover index when compared to the standard Stocking method, except for the index WI. Architecture and cycle of millet and jack bean influenced the behavior of the studied vegetation indices. Vegetation indices generated from RGB images obtained by UAV were more practical and efficient, allowing a more frequent monitoring and in a wider area during the crop cycle.",
keywords = "vegetation cover index, RGB image, vegetation index, unmanned aerial vehicle",
author = "Adnane Beniaich and {Naves Silva}, {Marx Leandro} and Avalos, {Fabio Arnaldo Pomar} and Menezes, {Michele Duarte} and Candido, {Bernardo M}",
year = "2019",
month = jan,
doi = "10.5433/1679-0359.2019v40n1p49",
language = "English",
volume = "40",
pages = "49--66",
journal = "Semina-Ciencias Agrarias",
issn = "1676-546X",
publisher = "Universidade Estadual de Londrina",
number = "1",

}

RIS

TY - JOUR

T1 - Determination of vegetation cover index under different soil management systems of cover plants by using an unmanned aerial vehicle with an onboard digital photographic camera

AU - Beniaich, Adnane

AU - Naves Silva, Marx Leandro

AU - Avalos, Fabio Arnaldo Pomar

AU - Menezes, Michele Duarte

AU - Candido, Bernardo M

PY - 2019/1

Y1 - 2019/1

N2 - The permanent monitoring of vegetation cover is important to guarantee a sustainable management of agricultural activities, with a relevant role in the reduction of water erosion. This monitoring can be carried out through different indicators such as vegetation cover indices. In this study, the vegetation cover index was obtained using uncalibrated RGB images generated from a digital photographic camera on an unmanned aerial vehicle (UAV). In addition, a comparative study with 11 vegetation indices was carried out. The vegetation indices CIVE and EXG presented a better performance and the index WI presented the worst performance in the vegetation classification during the cycles of jack bean and millet, according to the overall accuracy and Kappa coefficient. Vegetation indices were effective tools in obtaining soil cover index when compared to the standard Stocking method, except for the index WI. Architecture and cycle of millet and jack bean influenced the behavior of the studied vegetation indices. Vegetation indices generated from RGB images obtained by UAV were more practical and efficient, allowing a more frequent monitoring and in a wider area during the crop cycle.

AB - The permanent monitoring of vegetation cover is important to guarantee a sustainable management of agricultural activities, with a relevant role in the reduction of water erosion. This monitoring can be carried out through different indicators such as vegetation cover indices. In this study, the vegetation cover index was obtained using uncalibrated RGB images generated from a digital photographic camera on an unmanned aerial vehicle (UAV). In addition, a comparative study with 11 vegetation indices was carried out. The vegetation indices CIVE and EXG presented a better performance and the index WI presented the worst performance in the vegetation classification during the cycles of jack bean and millet, according to the overall accuracy and Kappa coefficient. Vegetation indices were effective tools in obtaining soil cover index when compared to the standard Stocking method, except for the index WI. Architecture and cycle of millet and jack bean influenced the behavior of the studied vegetation indices. Vegetation indices generated from RGB images obtained by UAV were more practical and efficient, allowing a more frequent monitoring and in a wider area during the crop cycle.

KW - vegetation cover index

KW - RGB image

KW - vegetation index

KW - unmanned aerial vehicle

U2 - 10.5433/1679-0359.2019v40n1p49

DO - 10.5433/1679-0359.2019v40n1p49

M3 - Journal article

VL - 40

SP - 49

EP - 66

JO - Semina-Ciencias Agrarias

JF - Semina-Ciencias Agrarias

SN - 1676-546X

IS - 1

ER -