2026-04-26T21:59:15Zhttps://uvadoc.uva.es/oai/request

oai:uvadoc.uva.es:10324/525792025-02-06T11:07:17Zcom_10324_1136com_10324_931com_10324_894col_10324_1218

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 2022-03-22T12:31:33Z 2022-03-22T12:31:33Z 2020 AgriEngineering, 2020, vol. 2, n. 2, p. 206-212 2624-7402 https://uvadoc.uva.es/handle/10324/52579 10.3390/agriengineering2020012 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) application/pdf eng MDPI info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ © 2020 The Authors Attribution-NonCommercial-NoDerivatives 4.0 Internacional Atribución 4.0 Internacional Precision agriculture Agricultura de precisión Sinapis arvensis Unmanned aerial vehicles Vehículos aéreos no tripulados UAV Detection of sinapis arvensis infestation in alfalfa plots using simple vegetation indices from conventional digital cameras info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion https://www.mdpi.com/2624-7402/2/2/12 SI