Design and verification of the Far Ultraviolet Spectrographic Imager (FUV-SI) for the IMAGE mission

peer reviewedThe IMAGE FUV-SI is simultaneously imaging auroras at 121.8 nm and 135.8 nm. The spectrograph design challenge is the efficient rejection of the intense Lyman-alpha emission at 121.6 nm while passing its Doppler-shifted component at 121.8 nm. The FUV-SI opto-mechanical design, analysis integration, and verification of performances against environment are discussed in this paper. In absence of STM environmental constraints at subsystem levels are derived analytically from F.E.M. and used for pre-qualifying optical subsystems

Crop Phenology Modelling Using Proximal and Satellite Sensor Data

peer reviewedUnderstanding crop phenology is crucial for predicting crop yields and identifying potential risks to food security. The objective was to investigate the effectiveness of satellite sensor data, compared to field observations and proximal sensing, in detecting crop phenological stages. Time series data from 122 winter wheat, 99 silage maize, and 77 late potato fields were analyzed during 2015–2017. The spectral signals derived from Digital Hemispherical Photographs (DHP), Disaster Monitoring Constellation (DMC), and Sentinel-2 (S2) were crop-specific and sensor-independent. Models fitted to sensor-derived fAPAR (fraction of absorbed photosynthetically active radiation) demonstrated a higher goodness of fit as compared to fCover (fraction of vegetation cover), with the best model fits obtained for maize, followed by wheat and potato. S2-derived fAPAR showed decreasing variability as the growing season progressed. The use of a double sigmoid model fit allowed defining inflection points corresponding to stem elongation (upward sigmoid) and senescence (downward sigmoid), while the upward endpoint corresponded to canopy closure and the maximum values to flowering and fruit development. Furthermore, increasing the frequency of sensor revisits is beneficial for detecting short-duration crop phenological stages. The results have implications for data assimilation to improve crop yield forecasting and agri-environmental modeling

Bulletin agrométéorologique - Août 2006

L’année 2006 restera dans les annales comme étant une année exceptionnelle au niveau météorologique tant par son printemps froid que par son mois de juillet très sec et son mois d’août particulièrement pluvieux. Ces conditions exceptionnelles rendent très délicates les prévisions de rendement. Il faut signaler que les rendements estimés sont ceux sur pieds et ils ne prennent pas en considération les pertes dues aux mauvaises conditions de récolte. Les rendements prévus pour les principales cultures de printemps restent très proches des moyennes calculées sur les 5 dernières années