The use of consumer digital cameras or webcams to characterize and monitor different features has become prevalent in various domains, especially in environmental applications. Despite some promising results, such digital camera systems generally suffer from signal aberrations due to the on-board image processing systems and thus offer limited quantitative data acquisition capability. The objective of this study was to test a series of radiometric corrections having the potential to reduce radiometric distortions linked to camera optics and environmental conditions, and to quantify the effects of these corrections on our ability to monitor crop variables. In 2007, we conducted a five-month experiment on sugarcane trial plots using original RGB and modified RGB (Red-Edge and NIR) cameras fitted onto a light aircraft. The camera settings were kept unchanged throughout the acquisition period and the images were recorded in JPEG and RAW formats. These images were corrected to eliminate the vignetting effect, and normalized between acquisition dates. Our results suggest that 1) the use of unprocessed image data did not improve the results of image analyses; 2) vignetting had a significant effect, especially for the modified camera, and 3) normalized vegetation indices calculated with vignetting-corrected images were sufficient to correct for scene illumination conditions. These results are discussed in the light of the experimental protocol and recommendations are made for the use of these versatile systems for quantitative remote sensing of terrestrial surfaces.

This work is aimed at deriving canopy component (soil and foliage) temperatures from remote sensing measurements. A simulation study above sparse, partial and dense vegetation canopies has been performed to improve the knowledge of the behaviour of the composite radiative temperature and emissivity. Canopy structural parameters have been introduced in the analytical parameterization of the directional canopy emissivity and directional canopy radiance:namely, the leaf area index (LAI), directional gap fraction and angular cavity effect coefficient. The parameterization has been physically defined allowing its extension to a wide range of Leaf Inclination Distribution Functions (LIDF). When single values are used as leaves and soil temperatures, they prove to be retrieved with insignificant errors from two directional measurements of the canopy radiance (namely at 0 and 55 from nadir), provided that the canopy structure parameters are known. A sensitivity study to the different parameters shows the great importance of the accuracy on LAI estimation (an accuracy of 10 per cent is required to retrieve the leaves temperature with an accuracy better than 0.5 degK, the same requirement being 5 per cent for the retrieval of soil temperature). The radiometric noise is important too, but its effects may be limited by using very different angles for the measurements: for 0 and 55, the effect of a Gaussian noise (NEDeltaT 0.05deg K) is lower than 0.5degK on the retrieved soil and foliage temperatures). Uncertainties on the leaf and soil emissivities (Delta epsilon 0.01) cause little errors in the retrieval (lower than 0.5degK). If the inclination dependence of the leaves temperature is considered, a 1 degK error is observed in the retrieved soil and foliage temperatures. This error is due to the fact that the effective foliage temperature varies with the view angle (a few 10 -1 deg K at 55 ), which implies errors in the inversion scheme. This effect may be corrected for by using an angular corrective term delta depending only on the off-nadir angle used.

Agronomy for Sustainable Development, An International Journal in Agriculture and Environment