Spectral discrimination of Ridolfia segetum and sunflower as affected by phenological stage

Ridolfia segetum is an umbelliferous weed frequent and abundant in sunflower crops in the Mediterranean basin. Field research was conducted to evaluate the potential of hyperspectral and multispectral reflectance and five vegetation indices in the visible to near infrared spectral range, for discriminating bare soil, sunflower and R. segetum at different phenological stages. This was a preliminary step for mapping R. segetum patches in sunflower using remote sensing for herbicide application decisions. Reflectance data were collected at three sampling dates (mid-May, mid-June and mid-July, corresponding to vegetative-early reproductive, flowering and senescent phenological stages respectively) using a handheld field spectroradiometer. Differences observed in hyperspectral reflectance curves were statistically significant within and between crop and weed phenological stages depending on sampling date, which facilitates their discrimination. Statistically significant differences in the multispectral and vegetation indices analysis showed that it is also possible to distinguish any of the classes studied. Our study provides some information for constructing the spectral libraries of sunflower and R. segetum in which the different phenological stages co-existing in the field were considered. Hyperspectral and multispectral results suggest that mapping R. segetum patches in sunflower is feasible using airborne hyperspectral sensors, and high-resolution satellite imagery or aerial photography, respectively, taking into account specific timeframes.

Bibliographic Details

Main Authors:	Peña Barragán, José Manuel, López Granados, Francisca, Jurado-Expósito, Montserrat, García Torres, Luis
Format:	artículo biblioteca
Language:	English
Published:	Wiley-Blackwell 2006
Subjects:	Hyperspectral, Multispectral, Precision agriculture, Remote weed detection, Spectral library, Vegetation index,
Online Access:	http://hdl.handle.net/10261/27215
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