RT info:eu-repo/semantics/article
T1 UAV Detection of sinapis arvensis infestation in alfalfa plots using simple vegetation indices from conventional digital cameras
A1 Sánchez Sastre, Luis Fernando
A1 Casterad, María Auxiliadora
A1 Guillén, Mónica
A1 Ruiz Potosme, Norlan Miguel
A1 Alte da Veiga, Nuno M. S.
A1 Navas Gracia, Luis Manuel
A1 Martín Ramos, Pablo
K1 Precision agriculture
K1 Agricultura de precisión
K1 Sinapis arvensis
K1 Unmanned aerial vehicles
K1 Vehículos aéreos no tripulados
AB 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.
PB MDPI
SN 2624-7402
YR 2020
FD 2020
LK https://uvadoc.uva.es/handle/10324/52579
UL https://uvadoc.uva.es/handle/10324/52579
LA eng
NO AgriEngineering, 2020, vol. 2, n. 2, p. 206-212
NO Producción Científica
DS UVaDOC
RD 24-nov-2024