Measuring the Effectiveness of Photoresponsive Nanocomposite Coatings on Aircraft Windshields to Mitigate Laser Intensity

In 2004, pilots reported 46 laser illumination events to the Federal Aviation Administration (FAA), with the number increasing to approximately 3,600 in 2011. Since that time, the number of reported laser incidents has ranged from 3,500 to 4,000. Previous studies indicate the potential for flight crewmember distraction from bright laser light being introduced to the cockpit. Compositional variations of the photoresponsive nanocomposite coatings were applied to an aircraft windscreen using a modified liquid dispersion/heating curing process. The attenuating effects of the deposited films on laser light intensity were evaluated using an optical power meter and the resultant laser intensity data through treated and untreated windscreens was collected. Data revealed a reduction in laser intensity (36–88%) in the presence of the engineered photoresponsive nanocomposite films. Results lend support of the view that the addition of transparent laser attenuating films applied to aircraft windscreens may improve flight safety, and reduce the risk from distraction or disruption of flight crewmembers’ vision

Exploring subtle land use and land cover changes: a framework for future landscape studies

UMR AMAP, équipe 3International audienceLand cover and land use changes can have a wide variety of ecological effects, including significant impacts on soils and water quality. In rural areas, even subtle changes in farming practices can affect landscape features and functions, and consequently the environment. Fine-scale analyses have to be performed to better understand the land cover change processes. At the same time, models of land cover change have to be developed in order to anticipate where changes are more likely to occur next. Such predictive information is essential to propose and implement sustainable and efficient environmental policies. Future landscape studies can provide a framework to forecast how land use and land cover changes is likely to react differently to subtle changes. This paper proposes a four step framework to forecast landscape futures at fine scales by coupling scenarios and landscape modelling approaches. This methodology has been tested on two contrasting agricultural landscapes located in the United States and France, to identify possible landscape changes based on forecasting and backcasting agriculture intensification scenarios. Both examples demonstrate that relatively subtle land cover and land use changes can have a large impact on future landscapes. Results highlight how such subtle changes have to be considered in term of quantity, location, and frequency of land use and land cover to appropriately assess environmental impacts on water pollution (France) and soil erosion (US). The results highlight opportunities for improvements in landscape modelling

Rétablir des corridors écologiques

[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIENational audienceLe projet national Trame verte et bleue prévoit l'établissement, dans chaque région, d'une cartographie au 1/100.000 des corridors écologiques. L'article présente des contributions potentielles de l’imagerie satellitaire à cette cartographie

Classification of Hyperspectral Images with Nonlinear Filtering and Support Vector Machines

Support Vector Machines, recently introduced in hyperspectral imagery, are applied to classify land cover on images from the airborne CASI sensor with a small training set. A smoothing preprocessing step is achieved, based on a vectorial extension of the anisotropic diffusion nonlinear filtering process. It allows the separability of the classes to be increased as well as homogeneous areas to be smoothed. It comes to take into consideration the spatial context before the classification, leading to improve the classification rate and to produce noiselessy classification maps with support vector machines

Nonlinear Filtering of Hyperspectral Images with Anisotropic Diffusion

A vectorial extension of the scalar anisotropic diffusion nonlinear filtering process applied on hyperspectral images is presented. In a first step, data are projected in a transformed space with a Maximum Noise Fraction transform, allowing the new components to be sorted in order of signal to noise ratio. The filtering is adapted to the signal to noise ratio of each component and a spectral dissimilarity vectorial measure is used in the filtering process. The inverse transform allows the filtered data to be reprojected in the original space. This process is useful for denoising hyperspectral images and for reducing spatial and spectral variability in each class of interest, leading to increase the performance of further segmentation or classification algorithms

Contribution of radar images for grassland management identification

International audienceCet article de la revue Fourrages, est édité par l'Association Francophone pour les Prairies et les Fourrages Pour toute recherche dans la base de données et pour vous abonner : www.afpf-asso.fr AFPF-Maison Nationale des Eleveurs-149 rue de Bercy-75595 Paris Cedex 1