2024-04-10T21:36:41Zhttps://uvadoc.uva.es/oai/requestoai:uvadoc.uva.es:10324/525792022-04-06T09:12:31Zcom_10324_1136com_10324_931com_10324_894col_10324_1218
UAV Detection of sinapis arvensis infestation in alfalfa plots using simple vegetation indices from conventional digital cameras
Sánchez Sastre, Luis Fernando
Casterad, María Auxiliadora
Guillén, Mónica
Ruiz Potosme, Norlan Miguel
Alte da Veiga, Nuno M. S.
Navas Gracia, Luis Manuel
Martín Ramos, Pablo
Precision agriculture
Agricultura de precisión
Sinapis arvensis
Unmanned aerial vehicles
Vehículos aéreos no tripulados
Producción Científica
Unmanned Aerial Vehicles (UAVs) offer excellent survey capabilities at low cost to provide farmers with information about the type and distribution of weeds in their fields. In this study, the problem of detecting the infestation of a typical weed (charlock mustard) in an alfalfa crop has been addressed using conventional digital cameras installed on a lightweight UAV to compare RGB-based indices with the widely used Normalized Difference Vegetation Index (NDVI) index. The simple (R−B)/(R+B) and (R−B)/(R+B+G) vegetation indices allowed one to easily discern the yellow weed from the green crop. Moreover, they avoided the potential confusion of weeds with soil observed for the NDVI index. The small overestimation detected in the weed identification when the RGB indices were used could be easily reduced by using them in conjunction with NDVI. The proposed methodology may be used in the generation of weed cover maps for alfalfa, which may then be translated into site-specific herbicide treatment maps.
Unión Europea (project LIFE11 ENV/ES/000535)
2022-03-22T12:31:33Z
2022-03-22T12:31:33Z
2020
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
AgriEngineering, 2020, vol. 2, n. 2, p. 206-212
2624-7402
https://uvadoc.uva.es/handle/10324/52579
10.3390/agriengineering2020012
eng
https://www.mdpi.com/2624-7402/2/2/12
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Atribución 4.0 Internacional
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
© 2020 The Authors
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MDPI
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TEXT
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UVaDOC. Repositorio Documental de la Universidad de Valladolid
https://uvadoc.uva.es/handle/10324/52579