Please use this identifier to cite or link to this item:
Title: UAV Detection of Sinapis arvensis Infestation in Alfalfa Plots Using Simple Vegetation Indices from Conventional Digital Cameras
Authors: Sánchez Sastre, Luis Fernando
Casterad Seral, María Auxiliadora
Guillén Castillo, Mónica
Ruiz Potosme, Norlan Miguel
Alte da Veiga, Nuno M.S.
Navas García, Luis Manuel
Martín Ramos, Pablo
Issue Date: 2020
Citation: AgriEngineering, vol. 2, num. 2, pp. 206-212, (2020)
Abstract: 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.
Related document:
Appears in Collections:[DOCIART] Artículos científicos, técnicos y divulgativos

Files in This Item:
File Description SizeFormat 
2020_087.pdf1,54 MBAdobe PDFThumbnail

This item is licensed under a Creative Commons License Creative Commons

La información de este repositorio es indexada en: