Climate change is undeniably one of the most pressing and critical challenges facing humanity in the 21st century. In this context, monitoring the Earth’s Energy Imbalance (EEI) is fundamental in conjunction with greenhouse gases (GHGs) in order to comprehensively understand and address climate change. The French Uvsq-Sat NG pathfinder mission addresses this issue through the implementation of a Six-Unit CubeSat, which has dimensions of 111.3 × 36.6 × 38.8 cm in its unstowed configuration. Uvsq-Sat NG is a satellite mission spearheaded by the Laboratoire Atmosphères, Observations Spatiales (LATMOS), and supported by the International Satellite Program in Research and Education (INSPIRE). The launch of this mission is planned for 2025. One of the Uvsq-Sat NG objectives is to ensure the smooth continuity of the Earth Radiation Budget (ERB) initiated via the Uvsq-Sat and Inspire-Sat satellites. Uvsq-Sat NG seeks to achieve broadband ERB measurements using state-of-the-art yet straightforward technologies. Another goal of the Uvsq-Sat NG mission is to conduct precise and comprehensive monitoring of atmospheric gas concentrations (CO2 and CH4) on a global scale and to investigate its correlation with Earth’s Outgoing Longwave Radiation (OLR). Uvsq-Sat NG carries several payloads, including Earth Radiative Sensors (ERSs) for monitoring incoming solar radiation and outgoing terrestrial radiation. A Near-Infrared (NIR) Spectrometer is onboard to assess GHGs’ atmospheric concentrations through observations in the wavelength range of 1200 to 2000 nm. Uvsq-Sat NG also includes a high-definition camera (NanoCam) designed to capture images of the Earth in the visible range. The NanoCam will facilitate data post-processing acquired via the spectrometer by ensuring accurate geolocation of the observed scenes. It will also offer the capability of observing the Earth’s limb, thus providing the opportunity to roughly estimate the vertical temperature profile of the atmosphere. We present here the scientific objectives of the Uvsq-Sat NG mission, along with a comprehensive overview of the CubeSat platform’s concepts and payload properties as well as the mission’s current status. Furthermore, we also describe a method for the retrieval of atmospheric gas columns (CO2, CH4, O2, H2O) from the Uvsq-Sat NG NIR Spectrometer data. The retrieval is based on spectra simulated for a range of environmental conditions (surface pressure, surface reflectance, vertical temperature profile, mixing ratios of primary gases, water vapor, other trace gases, cloud and aerosol optical depth distributions) as well as spectrometer characteristics (Signal-to-Noise Ratio (SNR) and spectral resolution from 1 to 6 nm).

Embarqué sur la plateforme ENVISAT, le spectro-imageur MERIS développé par Thales Alenia Space a permis de mesurer, à partir de 1993 et jusqu’en 2012 les paramètres environnementaux notamment de la couleur de l’Océan au large et sur les zones côtières. Avec le programme Copernicus de l’Union Européenne s’est ouvert en 2014 une évolution vers des mesures opérationnelles grâce aux satellites Sentinel 3 dédiés aux océans et équipés d’une nouvelle génération de spectro-imageurs, OLCI, héritiers de MERIS; quatre satellites sont programmée afin d’assurer la continuité des mesures sur de longues séries temporelles. A l’horizon 2029, le programme Copernicus va se diversifier avec un satellite d’imagerie hyperspectrale confié à Thales Alenia Space, Sentinel-10 ou CHIME (Copernicus Hyperspectral Imaging Mission for the Environment). Cet ensemble de réalisations complété par le développement de sondeurs atmosphériques hyperspectraux comme IASI sur METOP et IRS sur METEOSAT, constituent une expertise technique de pointe, unique au monde.

Satellite remote sensing of coastal waters is important for understanding the functioning of these complex ecosystems. High satellite revisit frequency is required to permit a relevant monitoring of the strong dynamical processes involved in such areas, for example rivers discharge or tidal currents. One key parameter that is derived from satellite data is the suspended particulate matter (SPM) concentration. Knowledge of the variability of SPM could be used by sediment transport models for providing accurate predictions. Most of the current satellites that are dedicated to ocean color observations have a sun-synchronous orbit that performs a single daytime observation. The Visible Infrared Imaging Radiometer Suite (VIIRS) ocean color sensor (NASA/NOAA) is the only one that is equipped with a panchromatic spectral band, so-called Day-Night Band, which is able to measure extremely low level signals, typically of the order of magnitude of 10 −5 W m −2 sr −1 µm −1 . The objective of this paper is to investigate the potential of the panchromatic and radiometric specifications of the VIIRS sensor to detect SPM concentrations from nighttime satellite observations. Realistic radiative transfer simulations are performed to quantitatively determine the amplitude of the top of atmosphere radiances under various conditions such as various moon incident illuminations, observation geometries, atmospheric and oceanic turbidities. The simulations are compared with the minimum detectable radiance as specified for the VIIRS sensor. The results show that the detection of SPM is systematically feasible, including in clear waters, for any observation geometries in the case of a full moon illumination. The sensitivity of the results to the lunar phase (i.e., out of the full moon conditions), which is one of the originalities of the study, shows that the detection should also be feasible for a significant number of nights over the entire lunar cycle, typically from 5 to 15 nights depending on the water turbidity. Therefore, nighttime ocean color panchromatic measurements performed using a VIIRS-like sensor are a highly promising approach, especially if it is combined with daytime observations, for improving the monitoring of ocean dynamics.

The atmospheric correction of remote sensing data in the reflective domain is today very well controlled under clear sky conditions. However, cirrus clouds represent 2/3 of the global terrestrial cover, making several images unusable. Gao and Li [5] proposed an empirical method of thin cirrus correction. The method shows very good results on dark surfaces but presents bias higher than 0.02 when the surface becomes too reflective and the cirrus too thick. In addition, it only corrects for the upwelling path [7]. Simulations show that the presence of cirrus on the sun-to-ground path has a significant influence on the received signal and must also be corrected. This paper shows that considering the transmission term of the cirrus of the upwelling and downwelling paths improves the results in the red-edge but also the SWIR, with an RMSE divided by 2.

Open ocean and coastal area monitoring requires multispectral satellite images with a middle spatial resolution (~300 m) and a high temporal repeatability (~1 h). As no current satellite sensors have such features, the aim of this study is to propose a fusion method to merge images delivered by a low earth orbit (LEO) sensor with images delivered by a geostationary earth orbit (GEO) sensor. This fusion method, called spatial spectral temporal fusion (SSTF), is applied to the future sensors- Ocean and Land Color Instrument (OLCI) (on Sentinel-3) and Flexible Combined Imager (FCI) (on Meteosat Third Generation) whose images were simulated. The OLCI bands, acquired at t0, are divided by the oversampled corresponding FCI band acquired at t0 and multiplied by the FCI bands acquired at t1. The fusion product is used for the next fusion at t1 and so on. The high temporal resolution of FCI allows its signal-to-noise ratio (SNR) to be enhanced by the means of temporal filtering. The fusion quality indicator ERGAS computed between SSTF fusion products and reference images is around 0.75, once the FCI images are filtered from the noise and 1.08 before filtering. We also compared the estimation of chlorophyll (Chl), suspended particulate matter (SPM), and colored dissolved organic matter (CDOM) maps from the fusion products with the input simulation maps. The comparison shows an average relative errors on Chl, SPM, and CDOM, respectively, of 64.6%, 6.2%, and 9.5% with the SSTF method. The SSTF method was also compared with an existing fusion method called the spatial and temporal adaptive reflectance fusion model (STARFM).

This paper presents a kernel-based nonlinear mixing model for hyperspectral data, where the nonlinear function belongs to a Hilbert space of vector valued functions. The proposed model extends the existing ones by accounting for band-dependent and neighboring nonlinear contributions. The key idea is to work under the assumption that nonlinear contributions are dominant in some parts of the spectrum, while they are less pronounced in other parts. In addition to this, we motivate the need for taking into account nonlinear contributions originating from the ground covers of neighboring pixels by practical considerations, precisely the adjacency effect. The relevance of the proposed model is that the nonlinear function is associated with a matrix valued kernel that allows to jointly model a wide range of nonlinearities and includes prior information regarding band dependences. Furthermore, the choice of the nonlinear function input allows to incorporate neighboring effects. The optimization problem is strictly convex and the corresponding iterative algorithm is based on the alternating direction method of multipliers. Finally, experiments conducted using synthetic and real data demonstrate the effectiveness of the proposed approach.

The Flexible Combined Imager (FCI) is an instrument to be borne by the future geostationary meteorological satellite Meteosat Third Generation (MTG). A numerical simulator was set up to provide simulated outputs of the instrument. It includes top-of-atmosphere scene of upwelling spectral radiance obtained by a radiative transfer model in the clear atmosphere, and the transfer function of the FCI. The sensitivity of the sensor outputs to aerosol properties is studied by varying the inputs defining the scenes and their illumination. The Global Sensitivity Analysis (GSA) with the Sobol' decomposition is applied to the outputs of the simulator, yielding a ranking of the inputs with respect to their influence on the FCI numerical outputs. The results are presented for all visible and near infrared channels of the FCI for desert type of aerosols according to the OPAC database. The study highlights the most relevant channels for aerosol detection and characterization and gives assessment of the different sources of uncertainties in aerosol retrieval with such channels.

The Flexible Combined Imager (FCI) is an instrument on the future geostationary meteorological satellite Meteosat Third Generation (MTG). This communication presents preliminary results on its capability in measuring and characterizing the optical properties of the aerosols, their load, and nature. A numerical simulator has been built that includes top-of-atmosphere scene simulation obtained by a radiative transfer model in the clear atmosphere, and the transfer function of the FCI (spectral response, SNR…) to provide simulated outputs of the instrument. Changes of inputs depicting the atmosphere and the ground yield a series of FCI outputs that are analyzed by means of global sensitivity analysis to assess the sensitivity of FCI to changing aerosol properties.

The objective of this work is to simulate global images that would be provided by a theoretical ocean color sensor on a geostationary orbit at longitude 0, in order to assess the range of radiance value data reaching the sensor throughout the day for 20 spectral bands similar to those of the Ocean and Land Color Imager (OLCI). The secondary objective is to assess the illumination and viewing geometries that result in sunglint. For this purpose, we combined a radiative transfer model for ocean waters (Hydrolight) and a radiative transfer model for atmosphere (MODTRAN) to construct the simulated radiance images at the sea surface and at the Top-Of-Atmosphere (TOA). Bio-optical data from GlobColour level 3 products are used as input maps in the ocean radiance model. The first result of this study is the radiance dynamic range of the scene during the day. The second result indicates the angular limit to avoid the sun glint phenomenon ( and ), where the viewing zenith angle, the solar zenith angle and the relative azimuth angle. We have also shown that a significant signal from water is measured when the ratio is higher than 3%, i.e., when is lower than 90, with a limit of 60 for the two angles.

The impact of the solar and sensor angles on band-ratio chlorophyll concentration (Chl) estimation in Case 1 waters (open ocean) is analyzed in this work. The error range of Chl estimation due to angular variation is evaluated. The radiative transfer code Hydrolight is used for remote sensing reflectance simulation for 20 spectral bands. OC4v4 algorithm is used for Chl estimation. The results indicate that the error range of Chl estimation is between -41.91% and +46.15% when Chl range is from 0.0425 mg/m3 to 10.6685 mg/m3 and the solar and sensor zenith angles vary between 0 and 80°. This study provides a reference to determine the effective observation area of a future multispectral or hyperspectral geostationary ocean color sensor.

The objective of this work is to simulate global images that would be provided by a theoretical ocean color sensor on a geostationary orbit at longitude 0, in order to assess the range of radiance value data reaching the sensor throughout the day for 20 spectral bands similar to those of the Ocean and Land Color Imager (OLCI). The secondary objective is to assess the illumination and viewing geometries that result in sunglint. For this purpose, we combined a radiative transfer model for ocean waters (Hydrolight) and a radiative transfer model for atmosphere (MODTRAN) to construct the simulated radiance images at the sea surface and at the Top-Of-Atmosphere (TOA). Bio-optical data from GlobColour level 3 products are used as input maps in the ocean radiance model. The first result of this study is the radiance dynamic range of the scene during the day. The second result indicates the angular limit to avoid the sun glint phenomenon ( and ), where the viewing zenith angle, the solar zenith angle and the relative azimuth angle. We have also shown that a significant signal from water is measured when the ratio is higher than 3%, i.e., when is lower than 90, with a limit of 60 for the two angles.

The Thau lagoon, located in southern France, suffers episodically from anoxic crises locally known as 'malaigue'. Such crises mostly occur under warm conditions, low winds leading to a strong eutrophication of the lagoon. The development of a sulphur bacterium sometimes gives locally to the waters a 'milky turquoise' appearance and leads to shellfish mortality. One of the indicators of the eutrophication status of the lagoon can be surveyed by the chlorophyll product provided by remote sensing images such as Medium Resolution Imaging Spectrometer (MERIS). In this paper we compare chl2 (or algal2) estimations provided by MERIS level 2 products and the ground measurements of chlorophyll a concentrations in water and we propose a linear correction of the chl2 MERIS product. The corrected chl2 estimations obtained over four years are analysed to understand the seasonal evolution of the trophic status of the Thau lagoon. We also study the influence of the anoxic crises of summers 2003 and 2006 on the chl2 estimations and we find a strong correlation between chl2 and the oxygen percentage at 1 m depth (0.70 for measurements in summers 2003 and 2006).

A method of image simulation of geostationary sensor dedicated to ocean color for open water (case1) and coastal water (case2) is presented in this paper. This method uses HYDROLIGHT to model the radiative transfer in order to obtain the water surface radiance. MeRIS level 3 products have been used for input water components to provide a realistic spatial distribution. The atmospheric radiative transfer model and the sensor model finely lead to satellite remote sensing images. This system allows to evaluate the dynamic range of BOA and TOA radiances depending on solar and viewing angles in operational situation and latter their influence on water composition retrieval.

The growing number of sensors raises questions about the image parameters required for the application, soil identification and moisture estimation. Hyperspectral images are also known to contain highly redundant information. Hence not all the spectral bands are needed for the satisfactory classification of the soil types. Hence, the work was aimed at obtaining these optimal spectral bands for identifying the soil types and to use these spectral bands to estimate the moisture content of the soils using the method proposed by Whiting et.al.

Remote sensing of urban areas is currently in significant development thanks to the achievement of new instruments allowing the observation of cities at very high spatial resolution (~1m). With such sensors, appropriate techniques must be developed. The characterization of urban aerosols to perform atmospheric corrections of remote sensing images is an issue that can take advantage of those new possibilities. A new characterization procedure of the atmospheric particles is presented in this paper. Based on the observation of sun/shadow transitions, it allows the retrieval of an aerosol model and of its spectral optical thickness. Retrieval results performed with synthetic images are presented to show the potential of this new method.

Geosynchronous satellite can measure any area with high temporal repetitivity within its coverage region because of its relative static location compared to Earth. Considering the temporal repetitivity, it can satisfy requirements for coastal zone monitoring but also has to face the influence of the varying solar angle and sensor angle (zenith and azimuth). Up to now, there is no geosynchronous sensor dedicated to ocean color monitoring (a geosynchronous sensor "Korea Geostationary Ocean Color Imager" (KGOCI) is supposed to be launched in 2009). To obtain radiances from the ocean at 36000 km of altitude, we have to use a simulation model. In this conference, we present generic model of simulation of geosynchronous optical sensor. This model is composed of different models: a water bio-optical model, an atmospheric transfer model and a sensor model. We also present our recent results, that is the influence of solar angle and sensor angle on deviation of estimation of chlorophyll concentration in open ocean (case1 water).

A cell suspension culture of cv. Gamay was studied for its ability to metabolize two different C13-norisoprenoidic volatiles, β-ionone and dehydrovomifoliol, together with monoterpenes, geraniol and linalool, biogenetically common pathways sharing compounds. β-Ionone was totally metabolized leading to fourteen norisoprenoidic volatiles oxygenated mainly at carbons 3 or 4 of the cyclohexane ring or reduced at side chain. The biotransformation of dehydrovomifoliol was at a lesser extent, giving rise to oxygenated and reduced derivatives. The norisoprenoidic metabolites were present both under free and glycosylated forms. Geraniol and linalool were also metabolized, leading to several free and glycosylated compounds.

Hyperspectral imaging systems could be used for identifying the different soil types from the satellites. However, detecting the reflectance of the soils in all the wavelengths involves the use of a large number of sensors with high accuracy and also creates a problem in transmitting the data to earth stations for processing. The current sensors can reach a bandwidth of 20 nm and hence, the reflectance obtained using the sensors are the integration of reflectance obtained in each of the wavelength present in the spectral band. Moreover, not all spectral bands contribute equally to classification and hence, identifying the bands necessary to have a good classification is necessary to reduce sensor cost and problem in data transmission from the satellite. The work presents the spectral bands selected using a PCA-Based Forward Sequential band selection algorithm.