Impact of Radiometric Variability on Ultra-High Resolution Hyperspectral Imagery Over Aquatic Vegetation: Preliminary Results

Over the last two decades, advancements in airborne imaging spectroscopy have prompted the exploitation of lightweight drones for detailed vegetation assessment at unprecedented resolutions. Yet, surface reflectance anisotropy and view-illumination effects may bias spectra extracted from push-broom scanners and derived spectral indices (SIs), particularly over aquatic vegetation, thus impacting the retrieval of biophysical and biochemical vegetation parameters. In this study, the impact of illumination conditions (overcast versus clear sky) and angular configurations (i.e., solar and viewing angles) on radiometric variability of centimetric resolution drone data was empirically investigated over four different aquatic plant species, representing different growth forms and canopy structures. Nadir-normalized reflectance spectra, broadband SIs, and the spectral angle distance to proximal leaf reflectance were used for characterizing and quantifying radiometric variability at canopy and leaf levels. Our findings demonstrated a decrement in reflectance under diffuse light conditions, especially in highly reflective domains within Green (520-580 nm) and Near-Infrared (700-850 nm) ranges, and a marked angular reflectance anisotropy in high absorption spectral regions (i.e., 450-500 nm and 630-700 nm) for aquatic vegetation. The normalized difference vegetation index (NDVI) showed overall lower sensitivity to incoming light variability and angular configurations compared to other tested SIs, whereas the water adjusted vegetation index (WAVI), suitably designed for aquatic vegetation, was less affected by angular anisotropy in floating plants. Indeed, radiometric variability exhibited a dependence on aquatic plant features, i.e., leaf orientation, canopy structure, and affinity with water (as canopy background)

Non-exclusivity and adverse selection: An application to the annuity market

Dipartimento Scienze Economich

On common agency models of moral hazard

We consider Common Agency games of moral hazard and we suggest that there is only a very weak support for the standard restriction to take-it or leave-it contracts

Rôle représenté et rôle joué : l’activité des techniciens conseils

Afin de mieux comprendre l’activité de Techniciens Conseil (TC) à la CNAV (Caisse Nationale d’Assurance Vieillesse), nous proposons d’utiliser la notion de rôle qui permet de saisir l’activité de travail à travers des représentations et des constructions discursives : nous observons le rôle tel qu’il est mis en mots par le discours institutionnel (prescriptions et conduites attendues), par les acteurs eux-mêmes (conception subjective interprétant le discours prescrit par l’institution et l’expérience vécue), ou actualisé (Goffman, 1973) dans l’interaction. L’analyse des corpus confronte les « discours sur soi » recueillis par les chercheurs auprès des TC, les discours au travail entre assurés et TC, ainsi que les discours prescriptifs relatifs à cette profession. Elle souligne l’intérêt de ce croisement des matériaux discursif pour mieux comprendre l’activité.ouinonouirechercheNationa

Assessing PROSPECT performance on aquatic plant leaves

PROSPECT is the most widely used optical leaf model for a wide range of remote sensing applications on vegetation and has been developed and parameterised based on empirical data measured almost exclusively on terrestrial plant leaves. As aquatic plants differ substantially from terrestrial plants in leaf morphology and physiology, the validity of the relationships underlying PROSPECT in aquatic plants needs to be verified empirically. To this end, we compiled a comprehensive dataset of leaf spectra and biochemical-structural parameters sampled along a water affinity gradient, including floating and emergent hydrophytes, helophytes and riparian species, and terrestrial plants. In parallel, we designed a multidimensional experiment to explore the performance of PROSPECT across different groups and to characterise sources of modelling error, focusing on aquatic plants. Our results showed that estimates of most leaf parameters from PROSPECT inversions diverged increasingly from measured traits when moving from terrestrial to aquatic species. The suboptimal performance of PROSPECT on aquatic plants appears to be driven by three main factors: difficulties in disentangling leaf dry matter components (particularly proteins), unresolved issues related to the overlap of primary and secondary pigment mixtures and absorption, and the peculiarities of internal leaf structure (i.e. the presence of 'aerenchyma'). These findings highlight the need for careful preliminary evaluation of the applicability and limitations of PROSPECT when applied to vegetation types that differ significantly from the typical terrestrial trees and grasses used for model calibration, including aquatic plants. Such evaluation should be preferably based on empirical data covering natural heterogeneity, so that future applications of remote sensing for mapping aquatic and wetland vegetation characteristics can be improved in terms of robustness and transferability

A burned area mapping algorithm for sentinel-2 data based on approximate reasoning and region growing

Sentinel-2 (S2) multi-spectral instrument (MSI) images are used in an automated approach built on fuzzy set theory and a region growing (RG) algorithm to identify areas affected by fires in Mediterranean regions. S2 spectral bands and their post- and pre-fire date (Delta(post-pre)) difference are interpreted as evidence of burn through soft constraints of membership functions defined from statistics of burned/unburned training regions; evidence of burn brought by the S2 spectral bands (partial evidence) is integrated using ordered weighted averaging (OWA) operators that provide synthetic score layers of likelihood of burn (global evidence of burn) that are combined in an RG algorithm. The algorithm is defined over a training site located in Italy, Vesuvius National Park, where membership functions are defined and OWA and RG algorithms are first tested. Over this site, validation is carried out by comparison with reference fire perimeters derived from supervised classification of very high-resolution (VHR) PlanetScope images leading to more than satisfactory results with Dice coefficient > 0.84, commission error < 0.22 and omission error < 0.15. The algorithm is tested for exportability over five sites in Portugal (1), Spain (2) and Greece (2) to evaluate the performance by comparison with fire reference perimeters derived from the Copernicus Emergency Management Service (EMS) database. In these sites, we estimate commission error < 0.15, omission error < 0.1 and Dice coefficient > 0.9 with accuracy in some cases greater than values obtained in the training site. Regression analysis confirmed the satisfactory accuracy levels achieved over all sites. The algorithm proposed offers the advantages of being least dependent on a priori/supervised selection for input bands (by building on the integration of redundant partial burn evidence) and for criteria/threshold to obtain segmentation into burned/unburned areas

Impact of Radiometric Variability on Ultra-High Resolution Hyperspectral Imagery Over Aquatic Vegetation: Preliminary Results

Over the last two decades, advancements in airborne imaging spectroscopy have prompted the exploitation of lightweight drones for detailed vegetation assessment at unprecedented resolutions. Yet, surface reflectance anisotropy and view-illumination effects may bias spectra extracted from push-broom scanners and derived spectral indices (SIs), particularly over aquatic vegetation, thus impacting the retrieval of biophysical and biochemical vegetation parameters. In this study, the impact of illumination conditions (overcast versus clear sky) and angular configurations (i.e., solar and viewing angles) on radiometric variability of centimetric resolution drone data was empirically investigated over four different aquatic plant species, representing different growth forms and canopy structures. Nadir-normalized reflectance spectra, broadband SIs, and the spectral angle distance to proximal leaf reflectance were used for characterizing and quantifying radiometric variability at canopy and leaf levels. Our findings demonstrated a decrement in reflectance under diffuse light conditions, especially in highly reflective domains within Green (520-580 nm) and Near-Infrared (700-850 nm) ranges, and a marked angular reflectance anisotropy in high absorption spectral regions (i.e., 450-500 nm and 630-700 nm) for aquatic vegetation. The normalized difference vegetation index (NDVI) showed overall lower sensitivity to incoming light variability and angular configurations compared to other tested SIs, whereas the water adjusted vegetation index (WAVI), suitably designed for aquatic vegetation, was less affected by angular anisotropy in floating plants. Indeed, radiometric variability exhibited a dependence on aquatic plant features, i.e., leaf orientation, canopy structure, and affinity with water (as canopy background)