A strong positive correlation between vegetation canopy bidirectional reflectance factor (BRF) in the near infrared (NIR) spectral region and foliar mass-based nitrogen concentration (%N) has been reported in some temperate and boreal forests. This relationship, if true, would indicate an additional role for nitrogen in the climate system via its influence on surface albedo and may offer a simple approach for monitoring foliar nitrogen using satellite data. We report, however, that the previously reported correlation is an artifact—it is a consequence of variations in canopy structure, rather than of %N. The data underlying this relationship were collected at sites with varying proportions of foliar nitrogen-poor needleleaf and nitrogen-rich broadleaf species, whose canopy structure differs considerably. When the BRF data are corrected for canopy-structure effects, the residual reflectance variations are negatively related to %N at all wavelengths in the interval 423–855 nm. This suggests that the observed positive correlation between BRF and %N conveys no information about %N. We find that to infer leaf biochemical constituents, e.g., N content, from remotely sensed data, BRF spectra in the interval 710–790 nm provide critical information for correction of structural influences. Our analysis also suggests that surface characteristics of leaves impact remote sensing of its internal constituents. This further decreases the ability to remotely sense canopy foliar nitrogen. Finally, the analysis presented here is generic to the problem of remote sensing of leaf-tissue constituents and is therefore not a specific critique of articles espousing remote sensing of foliar %N.

Image acquisition technology is improving very fast from a performance point of view. However, there are physical restrictions that can only be solved using software processing strategies. This is particularly true in the case of super resolution (SR) methodologies. SR techniques have found a fertile application field in airborne and space optical acquisition platforms. Single-frame SR methods may be advantageous for some remote-sensing platforms and acquisition time conditions. The contributions of this article are basically two: (1) to present an overview of single-frame SR methods, making a comparative analysis of their performance in different and challenging remote-sensing scenarios, and (2) to propose a new single-frame SR taxonomy, and a common validation strategy. Finally, we should emphasize that, on the one hand, this is the first time, to the best of our knowledge, that such a review and analysis of single SR methods is made in the framework of remote sensing, and, on the other hand, that the new single-frame SR taxonomy is aimed at shedding some light when classifying some types of single-frame SR methods.

In this study we have determined whether Raman and infrared spectroscopy of blood plasma differentiates Alzheimer's disease (AD) from normal aging of healthy controls. Spectroscopic analysis was conducted on blood plasma samples from 8 mild AD, 16 moderate AD, 11 severe AD, and 12 normal elderly control persons using Fourier transform spectrometers and a near-infrared laser beam as excitation source for Raman spectroscopy. Spectra were processed employing discriminant analysis to determine whether band areas and frequency-intensity relationships might reveal biochemical differences associated with AD. Seven spectral biomarkers were identified in the Raman regions of 1700–1600 cm ⁻¹ (protein secondary structure), 980–910 cm ⁻¹ (protein α-helices), 790–730 cm ⁻¹ (protein tertiary structure), and 440–390 cm ⁻¹ (protein backbone) and in the infrared regions of 1700–1600 cm ⁻¹ (protein secondary structure) and 1150–1000 cm ⁻¹ (oxidative stress). This discriminant analysis model differentiated AD from normal aging of elderly control persons with a sensitivity of 89% and specificity of 92%. Moreover, specificity increases to 100% for the detection of mild AD. In summary, our results open the possibility of using this spectroscopic approach as a non-invasive, rapid, and relatively inexpensive procedure for early accurate diagnosis of AD.