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Rosamaria Salvatori

Researcher at National Research Council

Publications -  49
Citations -  673

Rosamaria Salvatori is an academic researcher from National Research Council. The author has contributed to research in topics: Snow & Arctic. The author has an hindex of 12, co-authored 43 publications receiving 551 citations.

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Correlation between the specific surface area and the short wave infrared (SWIR) reflectance of snow

TL;DR: In this article, the specific surface area (SSA) of snow samples was measured using CH4 adsorption at 77 K, and a good correlation between the SSA and the snow spectral albedo in the short wave infrared (SWIR) was found.
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Associated changes in physiological parameters and spectral reflectance indices in olive (Olea europaea L.) leaves in response to different levels of water stress

TL;DR: In this paper, the spectral reflectance of olive leaves in response to different degrees of drought was measured using 16 reference wavelengths, from visible to SWIR regions, which are sensitive to both fast-developing and slow developing stresses and were used to develop an algorithm, the Relative Reflectance Increment (RRI), that was linearly related to changes in relative water content.
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Mediterranean vegetation analysis by multi-temporal satellite sensor data

TL;DR: In this article, a Mediterranean vegetated coastal area has been classified on the basis of multi-temporal TM images and accurate field data, and a major improvement in the spatial resolution of spectral data was obtained by merging TM and SPOT-P by a RGB-IHS transformation that allowed an overall accuracy in the classification of 85 per cent to be achieved.
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Snow cover monitoring with images from digital camera systems

TL;DR: The Snow-noSnow software, designed to automatically detect the extension of snow cover from webcam images, was tested on images collected on Alps (ARPAV webcam network) and on Apennine in a pilot station properly equipped for this project by CNR-IIA.
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Spectral properties of volcanic materials from hyperspectral field and satellite data compared with LiDAR data at Mt. Etna

TL;DR: The spectral analysis shows that air-fall deposits are characterized by low reflectance values besides variations in grain size, which distinguishes them from other surface materials, and represents a potentially powerful tool for the exploration of extraterrestrial volcanic surfaces.