UAV detection of Sinapis arvensis infestation in alfalfa plots using simple vegetation indices from conventional digital cameras

Sánchez-Sastre, Luis Fernando ; Casterad, M. Auxiliadora ; Guillén, Mónica ; Ruiz-Potosme, Norlan Miguel ; Alte da Veiga, Nuno M.S. ; Navas-Gracia, Luis Manuel ; Martín-Ramos, Pablo (Universidad de Zaragoza)

Resumen: 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.

Idioma: Inglés

DOI: 10.3390/agriengineering2020012

Año: 2020

Publicado en: AgriEngineering 2, 2 (2020), 206-212
ISSN: 2624-7402

Originalmente disponible en: Texto completo de la revista

Financiación: info:eu-repo/grantAgreement/EUR/LIFE/CO2 Operation-LIFE11 ENV/ES-000535

Tipo y forma: Artículo (Versión definitiva)

Área (Departamento): Area Ingeniería Agroforestal (Dpto. CC.Agrar.y Medio Natural)