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International audience; The Soil Moisture and Ocean Salinity (SMOS) satellite has been providing global data for more than 11 years. The algorithm to retrieve surface soil moisture (SM) and vegetation optical depth (VOD) from Brightness Temperatures (TB) has constantly evolved as our understanding of the instrument and of the responses to various ecosystems increased. The evolution of the radiative transfer modelling used in the inversion process is in part based upon ground measurements done on experimental sites. We present the particular case of an L-band radiometer placed on top of a 800- meter-high cliff. This design allows us to study large and various scenes when compared to classical experiments where a radiometer is placed 10–20 m above a surface. With our set up, the footprints cover areas larger than 300 m in diameter, covering thus several land use types and the footprint can be directed towards different dominant land classes (forest, crops, urban etc…). This paper presents the whole set up consisting of in situ measurements (soil moisture and surface temperatures) and L-band radiometry acquired by the LEWIS instrument at high incidence angles. We perform SM/VOD retrievals from brightness temperatures using various configurations which are compared to the in situ observations. We test in particular a 2-VOD retrieval approach that consists in deriving one SM for the entire scene but two VOD, one for agricultural/low vegetation and a VOD for the forest parts, which improves the performance of the SM/VOD retrievals.

International audience; As the volume of marine transportation increases, it becomes increasingly important to monitor ships for efficient coastal monitoring and management. To this end, high-resolution satellite images can be utilized to surveil oceanic environments synoptically. In this study, high-resolution optical satellite image was used to detect ships and estimate the size of each ship in the Korean coastal region. All the pixels in an image were first classified into ship, ship shadow, wake, sea, and land by applying a maximum likelihood classifier. The positions corresponding to the boundary of the ship were obtained from the magnitude of the 2-dimensional gradient on the classified ship pixels, and then the length and width of the ship were estimated by applying an ellipse fitting method to the ship periphery. This method resulted, in slight overestimations of the sizes of the ships. In order to improve the accuracy of the estimated ship sizes, a correction formula was developed by investigating the errors of the estimated values and their potential relationships to the variables representing the spatial shape of the vessels, such as eccentricity, kurtosis. Applying the suggested formulation for ship size estimation improved accuracy by 54.41% compared to the estimated sizes obtained through ellipse fitting. We anticipate that our method of estimating the lengths of the vessels will contribute to identifying missing ships using high-resolution satellite images.

International audience; Forest characterization at tree scale is possible with remotely sensed images of high spatial resolution. A first step is the Individual Tree Crown (ITC) delineation which corresponds to the segmentation of canopy cover into different tree crowns. In this study, a new method based on an initial watershed segmentation of Canopy Height Model (CHM) is proposed. This method is based on a graph transformation of the initial segmentation map in order to apply structural criteria (calculated owning to CHM) and spectral criterion (computed on red, green and blue bands). Adaptive thresholds are defined according to the studied forest characteristics in order to improve low quality segmentation cases. This method has been applied on a complex forest site (Broadleaf dominant, steep relief…). The results show a 17% increase of global performance in comparison to the reference watershed segmentation.; La caractérisation de la forêt à l'échelle de l'arbre est possible avec des images de télédétection de haute résolution spatiale. Une première étape est la délimitation de la couronne individuelle des arbres (ITC) qui correspond à la segmentation du couvert forestier en différentes couronnes d'arbres. Dans cette étude, une nouvelle méthode basée sur une segmentation initiale des bassins versants du modèle de hauteur de la canopée (CHM) est proposée. Cette méthode est basée sur une transformation graphique de la carte de segmentation initiale afin d'appliquer des critères structurels (calculés en propriété au CHM) et spectraux (calculés sur des bandes rouges, vertes et bleues). Des seuils adaptatifs sont définis en fonction des caractéristiques forestières étudiées afin d'améliorer les cas de segmentation de faible qualité. Cette méthode a été appliquée sur un site forestier complexe (dominante feuillue, relief escarpé…). Les résultats montrent une augmentation de 17% de la performance globale par rapport à la segmentation des bassins versants de référence.

International audience; Hyperspectral pansharpening methods, which aim to combine hyperspectral and panchromatic images, yield limited performance for scenes whose strong spatial heterogeneity induces mixed pixels. The SOSU method has been designed to handle this limitation and provided good results on agricultural and peri-urban landscapes. However, its performance was reduced on more complex urban scenes, which contain a higher proportion of mixed pixels. This article presents a new version of this method, called SOSU-2021, adapted to better process urban scenes. SOSU-2021 is tested on an urban dataset at a 1.6 m spatial resolution. We obtain better numerical results than with the previous SOSU version, and in the worst case, 56 % of the mixed pixels are better or equally processed by SOSU-2021 than by the method used as a reference.; Les méthodes d'affûtage hyperspectral, qui visent à combiner des images hyperspectrales et panchromatiques, donnent des performances limitées pour les scènes dont la forte hétérogénéité spatiale induit des pixels mixtes. La méthode SOSU a été conçue pour gérer cette limitation et a donné de bons résultats sur les paysages agricoles et périurbains. Cependant, ses performances ont été réduites sur des scènes urbaines plus complexes, qui contiennent une proportion plus élevée de pixels mixtes. Cet article présente une nouvelle version de cette méthode, appelée SOSU-2021, adaptée pour mieux traiter les scènes urbaines. SOSU-2021 est testé sur un ensemble de données urbaines à une résolution spatiale de 1,6 m. Nous obtenons de meilleurs résultats numériques qu'avec la version précédente de SOSU, et dans le pire des cas, 56% des pixels mixtes sont mieux ou également traités par SOSU-2021 que par la méthode utilisée comme référence.

International audience; Classification of hyperspectral scenes has been dominated in recent years by Convolutional Neural Networks (CNNs). Spectral and spatial convolutions have proven to be very effective in learning discriminative representations. The power of CNNs however is limited by their small receptive fields. Training deeper CNNs with wider receptive fields is a very difficult task with regard to the small amount of available training samples. Furthermore, CNNs seem to fail in capturing very local spectral features such as absorption peaks. In the present paper, we introduce a new paradigm inspired by physics-based hyperspectral indices and attention mechanisms. Our model learns spectral indices by focusing on specific spectral bands through soft attention units. It achieves high or better overall accuracy and kappa score than state-ofthe-art CNNs on Pavia University, Kennedy Space Center and our own real-world dataset while dramatically reducing the number of parameters needed and increasing interpretability.; La classification des scènes hyperspectives a été dominée ces dernières années par des réseaux de neurones convolutionnaires (CNNS). Les convolutions spectrales et spatiales se sont révélées très efficaces pour apprendre des représentations discriminantes. La puissance de CNNS cependant est limité par leurs petits champs réceptifs. Entraîneur de CNN plus profonds avec des champs réceptifs plus larges est une tâche très difficile en ce qui concerne la petite quantité d'échantillons de formation disponibles. En outre, les CNN semblent échouer dans le capturing des caractéristiques spectrales très locales telles que les pics d'absorption. Dans le présent document, nous introduisons un nouveau paradigme inspiré par des indices hyperspects basés sur la physique et des mécanismes d'attention. Notre modèle apprend les indices spectraux en se concentrant sur la SPE-bandes spectrales spécifiques à travers des unités d'attention douce. Il réalise une précision globale élevée ou supérieure et une score de kappa que l'état de la technologie CNNS sur la Pavie University, Kennedy Space Center et notre propre jeu de données du monde réel tout en réduisant radicalement le nombre de paramètres nécessaires et d'interprétabilité croissante.

International audience; In the context of climate change and rising frequency of extreme hydro-meteorological events around the world, flood risk management and mapping of heavy rainfall-related damages represent an ongoing critical challenge. For decades now, remote sensing has been largely used to investigate spatial and temporal changes in land use and water resources. Today, different satellite products provide fast and crucial knowledge for the study of hydrological disasters over large areas, possibly in remote regions, with high spatial resolution and high revisit frequency. Yet, until now, few works have sought to detect the full range of extreme rainfall-related damages with optical imagery, especially those caused by intense rainwater runoff beyond the direct vicinity of major waterways. The work presented in this paper focuses on the Aude severe weather event of October 15th, 2018, in the South of France, for which more than a thousand claims for agricultural disaster were registered, both related to river overflowing and rainwater runoff. The full resources of ground truths, contextual information, land use as well as digital elevation model (DEM) combined to high resolution and high frequency optical imagery (Sentinel-2, Pléiades) are used to develop an automatic damage detection method based on supervised classification algorithms. Through the combination of several indicators characterizing heterogeneous spectral variations among agricultural plots following the event, a Gaussian process classifier achieved various classification accuracies up to 90% on a large comparable and independent photo-interpreted validation sample. This work builds great expectations for applications in other areas with contrasted climate, topography and land cover.; Dans le contexte du changement climatique et de la fréquence croissante des événements hydrométéorologiques extrêmes dans le monde, la gestion des risques d'inondation et la cartographie des dommages liés aux fortes pluies représentent un défi critique permanent. Depuis des décennies, la télédétection a été largement utilisée pour étudier les changements spatiaux et temporels de l'utilisation des terres et des ressources en eau. Aujourd'hui, différents produits satellitaires fournissent des connaissances rapides et cruciales pour l'étude des catastrophes hydrologiques sur de vastes zones, éventuellement dans des régions éloignées, avec une résolution spatiale élevée et une fréquence de revisite élevée. Pourtant, jusqu'à présent, peu de travaux ont cherché à détecter la gamme complète des dommages liés aux pluies extrêmes par imagerie optique, en particulier ceux causés par un ruissellement intense des eaux de pluie au-delà du voisinage direct des principaux cours d'eau. Les travaux présentés dans cet article se concentrent sur l'épisode de temps violent de l'Aude du 15 octobre 2018, dans le sud de la France, pour lequel plus d'un millier de sinistres agricoles ont été enregistrés, tous deux liés au débordement des rivières et au ruissellement des eaux de pluie.L'ensemble des ressources de vérités de terrain, d'informations contextuelles, d'occupation des sols ainsi que du modèle numérique d'élévation (DEM) combiné à l'imagerie optique haute résolution et haute fréquence (Sentinel-2, Pléiades) sont utilisés pour développer une méthode de détection automatique des dommages basée sur une classification supervisée. algorithmes. Grâce à la combinaison de plusieurs indicateurs caractérisant les variations spectrales hétérogènes entre les parcelles agricoles à la suite de l'événement, un classificateur de processus gaussien a obtenu diverses précisions de classification allant jusqu'à 90% sur un grand échantillon de validation photo-interprété comparable et indépendant. Ce travail suscite de grandes attentes pour des applications dans d'autres domaines au climat, à la topographie et à la couverture du sol contrasté.

International audience; Elastic backscatter lidar is an established method useful to characterize the particles forming an atmospheric aerosol. Fundamental to lidar measurements are the extinction and backscattering properties of the aerosol particles in the lidar beam. This review aims to give the reader an understanding for how lidar measurements are made, modeled, and applied. Specific emphasis is placed on extinction, which manifests attenuation of the lidar beam by the aerosol, and the backscattering that ultimately constitutes the measured signal. The so-called lidar equation, which quantifies this signal in terms of aerosol-particle properties, is derived from radiative transfer theory. Extinction is examined in terms of the redistribution of energy from the lidar beam by the particles and is shown to be inherently linked to interference between the incident and scattered light. Ways to measure aerosol-particle extinction are reviewed, including a recent method where the wave interference constitutes a digital hologram that may be processed to yield both the cross section and an image of the particle. The semi-graphical method of phasor analysis is also presented and used to reveal connections between the scattering characteristics of a particle and the distribution of electric field within it. Finally, a recently developed elastic backscatter lidar system, Colibri, is described and an example of its measurement capabilities are presented.; Le lidar à rétrodiffusion élastique est une méthode établie utile pour caractériser les particules formant un aérosol atmosphérique et a de nombreuses applications en télédétection. Les propriétés d'extinction et de rétrodiffusion des particules d'aérosol dans un faisceau lidar sont fondamentales pour les mesures lidar élastique. Cet article de revue vise à donner au lecteur une compréhension de la façon dont les mesures lidar sont faites, modélisées et appliquées à la caractérisation des aérosols. Un accent particulier est mis sur l'extinction, qui manifeste l'atténuation du faisceau lidar par l'aérosol, et la rétrodiffusion qui constitue finalement le signal mesuré. L'équation dite lidar, qui quantifie ce signal en termes de propriétés des particules d'aérosol, est dérivée de la théorie du transfert radiatif. L'extinction est décrite en termes de conservation de l'énergie, car une particule absorbe et diffuse la lumière. Il est démontré que la redistribution de l'énergie du faisceau lidar par les particules est intrinsèquement liée à l'interférence entre la lumière incidente sur les particules et celle diffusée par celles-ci. Les méthodes de mesure de l'extinction des particules d'aérosol sont passées en revue, y compris une méthode récente où l'interférence des ondes impliquées dans l'extinction constitue un hologramme qui peut être traité pour donner à la fois la section transversale et une image d'une particule. La méthode semi-graphique d'analyse de phase est présentée et utilisée pour révéler le lien entre la diffusion d'une particule et la distribution du champ électrique en son sein. Enfin, un nouveau système de lidar élastique de rétrodiffusion, Colibri, est décrit dans le contexte des sujets abordés et un exemple de ses capacités de mesure est présenté.

Jose Antonio Benavent-Oltra is funded by the University of Granada through "Plan Propio. Programa 7, Convocatoria 2019". Roberto Roman is funded by MINECO under the postdoctoral programme Juan de la Cierva-Incorporacion (IJCI2016-30007). Juan Andres Casquero-Vera is funded by MINECO under the predoctoral programme FPI (BES-2017-080015). Maria J. Granados-Munoz received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 796539. Oleg Dubovik was supported by the Labex CaPPA project, which is funded by the French National Research Agency under contract "ANR-11-LABX0005-01". This work was also supported by the Spanish Ministry of Economy and Competitiveness (projects CMT2015-66742-R, CGL2016-81092-R, CGL2017-85344-R, RTI2018-097864-B-I00 and CGL2017-90884-REDT), by the Andalusia Regional Government through project P18-RT-3820 and the Unity of Excellence "Maria de Maeztu" (project MDM-2016-0600) financed by the Spanish State Research Agency (AEI). The authors thankfully ac-knowledge the FEDER programme for the instrumentation used in this work, the University of Granada, which supported this study through the Excellence Units Program, and the Sierra Nevada National Park. We also thank Dr. Grisa Monick who provided the Aethalometer AVIO AE-33 installed on the aircraft. Thanks to AERONET and ACTRIS/AERONET Europe for the scientific and technical support. Finally, the authors would like to acknowledge the use of the GRASP inversion algorithm software (http://www.grasp-open.com, last access: 1 April 2020), in this work., The Sierra Nevada Lidar aerOsol Profiling Experiment I and II (SLOPE I and II) campaigns were intended to determine the vertical structure of aerosols by remote sensing instruments and test the various retrieval schemes for obtaining aerosol microphysical and optical properties with in situ measurements. The SLOPE I and II campaigns were developed during the summers of 2016 and 2017, respectively, combining active and passive remote sensing with in situ measurements at stations belonging to the AGORA observatory (Andalusian Global ObseRvatory of the Atmosphere) in the Granada area (Spain). In this work, we use the in situ measurements of these campaigns to evaluate aerosol properties retrieved by the GRASP code (Generalized Retrieval of Atmosphere and Surface Properties) combining lidar and sun-sky photometer measurements. We show an overview of aerosol properties retrieved by GRASP during the SLOPE I and II campaigns. In addition, we evaluate the GRASP retrievals of total aerosol volume concentration (discerning between fine and coarse modes), extinction and scattering coefficients, and for the first time we present an evaluation of the absorption coefficient. The statistical analysis of aerosol optical and microphysical properties, both column-integrated and vertically resolved, from May to July 2016 and 2017 shows a large variability in aerosol load and types. The results show a strong predominance of desert dust particles due to North African intrusions. The vertically resolved analysis denotes a decay of the atmospheric aerosols with an altitude up to 5 km a.s.l. Finally, desert dust and biomass burning events were chosen to show the high potential of GRASP to retrieve vertical profiles of aerosol properties (e.g. absorption coefficient and single scattering albedo) for different aerosol types. The aerosol properties retrieved by GRASP show good agreement with simultaneous in situ measurements (nephelometer, aethalometer, scanning mobility particle sizer, and aerodynamic particle sizer) performed at the Sierra Nevada Station (SNS) in Granada. In general, GRASP overestimates the in situ data at the SNS with a mean difference lower than 6 mu m(3) cm(-3) for volume concentration, and 11 and 2 Mm(-1)for the scattering and absorption coefficients. On the other hand, the comparison of GRASP with airborne measurements also shows an overestimation with mean absolute differences of 14 +/- 10 and 1.2 +/- 1.2 Mm(-1) for the scattering and absorption coefficients, showing a better agreement for the absorption (scattering) coefficient with higher (lower) aerosol optical depth. The potential of GRASP shown in this study will contribute to enhancing the representativeness of the aerosol vertical distribution and provide information for satellite and global model evaluation., University of Granada, MINECO under the postdoctoral programme Juan de la Cierva-Incorporacion IJCI2016-30007, MINECO under the predoctoral programme FPI BES-2017-080015, European Commission 796539, French National Research Agency (ANR) ANR-11-LABX0005-01, Spanish Ministry of Economy and Competitiveness CMT2015-66742-R CGL2016-81092-R CGL2017-85344-R RTI2018-097864-B-I00 CGL2017-90884-REDT, Andalusia Regional Government P18-RT-3820, Spanish State Research Agency (AEI) MDM-2016-0600, Excellence Units Program, Sierra Nevada National Park

In this paper, we focus on the retrieval of microphysical and optical properties of industrial aerosol plumes through a process using airborne hyperspectral and Sentinel-2 multi-spectral images. The process allows first to perform atmospheric correction and second to determine background aerosols thanks to a comparison between hyperspectral and Sentinel-2 reflectances. Hyperspectral methodologies use the radiance differential between the measurement in the plume and the corresponding measurements out of the plume to estimate plume properties. To retrieve the surface reflectance under the plume, a principal component analysis coupling hyperspectral and multispectral data class by class is achieved. The developed method aims to compare the difference between measured and estimated reflectance with a radiative transfer model accounting for plume properties (particle radius and aerosol optical thickness of the plume). We have applied the method to a steel plant in the south of France. The retrieved plume show an aerosol mean radius between 0.05 and 0.2 µm with a mean aerosol optical thickness about 0.05 along the plume.

Monitoring of coastal areas by remote sensing is an important issue. The interest of using an unmixing method to determine the seabed composition from hyperspectral aerial images of coastal areas is investigated. Unmixing provides both seabed abundances and endmember reflectances. A sub-surface mixing model is presented, based on a recently proposed oceanic radiative transfer model that accounts for seabed adjacency effects in the water column. Two original non-negative matrix factorization ( N M F )-based unmixing algorithms, referred to as W A D J U M (Water ADJacency UnMixing) and W U M (Water UnMixing, no adjacency effects) are developed, assuming as known the water column bio-optical properties. Simulations show that W A D J U M algorithm achieves performance close to that of the N M F -based unmixing of the seabed without any water column, up to 10 m depth. W U M performance is lower and decreases with the depth. The robustness of the algorithms when using erroneous information about the water column bio-optical properties is evaluated. The results show that the abundance estimation is more reliable using W A D J U M approach. W A D J U M is applied to real data acquired along the French coast; the derived abundance maps of the benthic habitats are discussed and compared to the maps obtained using a fixed spectral library and a least-square ( L S ) estimation of the seabed mixing coefficients. The results show the relevance of the W A D J U M algorithm for the local analysis of the benthic habitats.

International audience; Surface soil moisture content (SMC) is known to impact soil reflectance at all wavelengths of the solar spectrum. As a consequence, many semi-empirical methods aim at inferring SMC from soil reflectance, but very few rely on physically-based models. This article presents a multilayer radiative transfer model of soil reflectance called MARMIT (multilayer radiative transfer model of soil reflectance) as a function of SMC given on a mass basis and a method called MARMITforSMC to estimate it from soil reflectance spectra. This model depicts a wet soil as a dry soil covered with a thin film of water. It is used to assess SMC over seven independent laboratory datasets gathered from the literature. A learning phase is required to link the thickness of the water film with the SMC. For that purpose, a sigmoid function, the parameters of which are related to soil physical and chemical properties such as porosity, grain size and mineralogy composition, is fitted. SMC can be inferred with good accuracy (RMSE ≈ 3%) if the learning step is applied soil by soil. The link between SMC and water thickness actually depends on soil texture and chemical composition. If the soils are divided into classes and if the learning phase is applied to a class, the RMSE slightly increases up to 5%. Finally, MARMITforSMC provides lower RMSE than any other existing semi-empirical or physically-based method.

International audience; This work assesses the ability of equivalent-sphere models to reproduce the optical properties of soot aggregates relevant for lidar remote sensing, i.e. the backscattering and extinction cross sections. Lidar cross-sections are computed with a spectral discrete dipole approximation model over the visible-to-infrared (40 0-50 0 0 nm) spectrum and compared with equivalent-sphere approximations. It is shown that the equivalent-sphere approximation, applied to fractal aggregates, has a limited ability to calculate such cross-sections well. The approximation should thus be used with caution for the computation of broad-band lidar cross-sections, especially backscattering, at small and intermediate wavelengths (e.g. UV to visible).

International audience; The remote assessment of soil contamination remains difficult in vegetated areas. Recent advances in hyperspectral spectroscopy suggest making use of plant reflectance to monitor oil and gas leakage from industrial facilities. However, knowledge about plant response to oil contamination is still limited, so only very few imaging applications are possible at this stage. We therefore conducted a greenhouse experiment on three species long-term exposed to either oil-contaminated or water-deficient soils. Reflectance measurements were regularly performed at leaf and plant scale over 61 days of exposure. Results showed an increase of reflectance in the visible (VIS), the red-edge and the short-wave infrared (SWIR) under both oil and water-deficit stress exposure. A contrasted response in the near-infrared (NIR) was also observed among species. Spectra underwent transformations to discriminate species’ responses to the different treatments using linear discriminant analysis (LDA) with a stepwise procedure. Original and transformed spectra enabled to discriminate the plants’ responses to the different treatments without confusion after 61 days. The discriminating wavelengths were consistent with the spectral differences observed. These results suggest differential changes in plant pigments, structure and water content as a response to various stressors, and open up promising perspectives for airborne and satellite applications.; L'évaluation à distance de la contamination du sol demeure difficile en régions végétalisées. De récentes avancées en spectroscopie hyperspectrale proposes d'exploiter la réflectance des plantes pour contrôler les déversements de pétrole et de gaz provenant d'installations pétrolières. Cependant, les connaissances sur la réponse de la plante à la contamination pétrolière demeurent limitées, donc peu d'application sont envisageables à l'échelle d'images. En ce sens, nous avons conduit une expérimentation en serre sur trois espèces exposées sur le long-terme à des sols contaminés par du pétrole ou déficient en eau. Des mesures de réflectance ont été régulièrement menées à l'échelle de la feuille et de la plante pendant 61 jours d'exposition. Les résultats ont montré une augmentation de la réflectance dans le visible (VIS), le red-edge et l'infra-rouge (SWIR) suite à l'exposition au pétrole et au stress hydrique. Une réponse contrastée a également été observée dans le proche infra(rouge (NIR). Les spectres ont fait l'objet de transformations pour discriminer les réponses des espèces aux traitements, en utilisant une analyse linéaire discriminante (LDA), suivant une procédure pas-à-pas. Les spectres originaux et transformés ont été capables de discriminer les réponses aux traitements, sans confusion, après 61 jours. Les longueurs d'ondes discriminantes se sont montrées cohérentes avec les différences spectrales observées. Ces résultats supposent des changements différentiels de pigments, de structure et de contenu en eau de la végétation comme réponse aux différents agents de stress, et laissent entrevoir des perspectives prometteuses pour des applications à l'échelle aéroportée et satellitaire.

International audience; For remote-sensing applications such as spectra classification or identification, atmospheric correction constitutes a very important pre-processing step, especially in complex urban environments where a lot of phenomenons alter the shape of the signal. The objective of this article is to compare the efficiency of two atmo-spheric correction algorithms, COCHISE (atmospheric COrrection Code for Hyperspectral Images of remote-sensing SEnsors) and an empirical method, on hyperspectral data and for classification applications. Classification is carried out on several simulated spaceborne data sets with different spatial resolutions (from 1.6 to 9.6 m). Four classifiers are considered in the study: a k-means, a Support Vector Machine (SVM), and a sun/shadow version of each of them, which processes sunlit and shadowed pixels separately. Results show that the most relevant atmospheric method for classification depends on the spatial resolution of the processed data set. Indeed, if the empirical method performs better on high-resolution data sets (up to 4%), its superiority fades out as the spatial resolution decreases, especially with the lower spatial resolution where COCHISE can be 10% more accurate than the empirical method.

International audience; This brief review focuses on the use of optical remote sensing for oil prospecting and monitoring in vegetated regions. Major advances have been achieved in this field during the last decade. Recent studies demonstrated that oil can be detected and quantified by exploiting vegetation reflectance from airborne-and satellite-embedded sensors. Various methods coupling vegetation indices or radiative transfer models with classification or regression algorithms have been proposed for this purpose. High spatial and spectral resolutions greatly increase the accuracy of oil detection and quantification. However, important limits remain in regions with sparse or highly diversified vegetation. Oil spills become also more difficult to map when other environmental stressors occur. Hence, an important effort remains to move toward operational applications, especially on upcoming drone-and satellite-embedded hyperspectral sensors.

International audience; We present smoke lidar measurements from the Canadian fires of 2017. The advected smoke layers over Europe are detected at both tropospheric and stratospheric heights, with the latter presenting non-typical values of the Linear Particle Depolarization Ratio (LPDR) with strong wavelength dependence from the UV to the Near-IR. Specifically, the LPDR values are of the order of 22, 18 and 4% at 355, 532 and 1064 nm respectively. In an attempt to interpret these results, we apply the hypothesis that smoke particles have near-spherical and/or more complicated shapes. Scattering calculations with the T-matrix code revealed that the near-spherical shape is able to reproduce the observed LPDR and LR values of the stratospheric smoke particles at the three measurement wavelengths.; Nous présentons les mesures du lidar de fumée des incendies canadiens de 2017. Les couches de fumée advectées sur l'Europe sont détectées à la fois à des hauteurs troposphériques et stratosphériques, ces dernières présentant des valeurs atypiques du rapport de dépolarisation linéaire des particules (LPDR) avec une forte dépendance de longueur d'onde de l'UV au proche IR. Plus précisément, les valeurs LPDR sont de l'ordre de 22, 18 et 4% à 355, 532 et 1064 nm respectivement. Pour tenter d'interpréter ces résultats, nous appliquons l'hypothèse que les particules de fumée ont des formes quasi sphériques et/ou plus complexes. Les calculs de diffusion avec le code de la matrice T ont révélé que la forme quasi-sphérique est capable de reproduire les valeurs LPDR et LR observées des particules de fumée stratosphériques aux trois longueurs d'onde de mesure.

In this paper, a new elastic lidar inversion equation is presented. It is based on the backscattering signal from a surface reference target (SRT) rather than that from a volumetric layer of reference (Rayleigh molecular scatterer) as is usually done. The method presented can be used when the optical properties of such a layer are not available, e.g., in the case of airborne elastic lidar measurements or when the lidar–target line is horizontal Also, a new algorithm is described to retrieve the lidar ratio and the backscattering coefficient of an aerosol plume without any a priori assumptions about the plume. In addition, our algorithm allows a determination of the instrumental constant. This algorithm is theoretically tested, viz. by means of simulated lidar profiles and then using real measurements. Good agreement with available data in the literature has been found.

International audience; This chapter aims at presenting thematic applications of hyperspectral imagery related to human activities. This chapter is a companion of Chapter 3.1 in which four applications related to monitoring of natural resources or inspection of scenes were presented.

International audience; During five years, in the frame of the NAOMI (New Advanced Observation Method Integration) research project, Total and ONERA have worked on radar and optical imagery to detect, characterize and quantify slicks at sea. Laboratory and pool measurements, physical modelling and offshore experiments have been combined to fully understand the signal collected over slick-covered area. As the measured signal is analytically expressed according to the geophysical parameters of the imaged slick, it enables to fully monitor the ocean surface: is a slick present? What kind of slick is it (extremely thin or not)? Is it a known product (existing in the data base)? Can the thickness be probed by the used of optical or radar device? What is the slick volume? In the Health Security and Environment (HSE) context, an exhaustive measurement campaign can be done in order to create a data base with hydrocarbon or hydrocarbon emulsion signatures, extinction coefficients, skin depths, minimum thicknesses perceptible thanks to extinction and thickness values. Thus, it offers more processing options in the optic branch of the tool to monitor the slick. Depending on the available data, optical and/or radar imagery, the capability of slick detection, characterization and quantification will be presented. After a recall of the HSE specificity, the paper will give an overview of the main features of the input data that is to say SAR and optical images. Then, based on modelling results, the optimal observation conditions for radar and optical imagery will be introduced. Afterwards, capability of detection will be described and illustrated for both the radar and the optical case. In the optical domain, the process will distinguish at least two classes: thin and thick. In the HSE context, a database can be used to identify some detected products. The last step is quantification. A sophisticated method, relying on L band radar imagery, will be used to identify pixels covered by a film, meaning presence of oil at the surface, and the ones for which the oil may be as droplets in the volume. The traditional use of SAR data is also extended to the estimation of the oil concentration within an oil and seawater mixture. For optical data, the most direct quantification process relies on automatic Bonn code classification. The code links a class with a range of thickness and computes a minimum and a maximum volume of product in each class. If the product is in the data base a more suited classification and volume assessment can be done. If the thickness is too thin (spectral signature due to absorption is too weak) or too thick (only the upper part of the product layer contributes to the signal), a thickness estimated thanks to pool experiment is associated to each class enabling to compute a volume per class and a global volume. In the other cases, in a near future, modelling would enable to assess the thickness. Concerning hydrocarbon emulsions, modelling in the optical domain is in progress in order to predict skin depth and to derive water content.; Pendant cinq ans, dans le cadre du projet de recherche NAOMI (New Advanced Observation Method Integration), Total et l'ONERA ont travaillé dans le domaine de l'imagerie radar et optique pour détecter, caractériser et quantifier les nappes d'hydrocarbures en mer. Des mesures en laboratoire et en bassin, de la modélisation physique et des expérimentations en mer ont été associées pour comprendre pleinement le signal mesuré au dessus d'une nappe. L'expression analytique du signal en fonction des paramètres géophysiques permet d'analyser et de suivre la surface marine : Une nappe est-elle présente ? Quel type de nappe est-ce (très fine ou pas) ? Le produit est-il connu (dans la base de données existante) ? L'épaisseur de la nappe peut-elle être mesurée par imagerie radar ou optique ? Quel est le volume de la nappe ?Dans le contexte Hygiène Sécurité et Environnement (HSE), une campagne de mesure exhaustive peut être faite pour créer une base de données avec les signatures des hydrocarbures ou des émulsions, les coefficients d'extinction, les épaisseurs de peau, les épaisseurs minimales perceptibles par extinction et les épaisseurs.Selon les données disponibles, imagerie radar et/ou optique, le potentiel de détection, caractérisation et quantification de nappe sera présenté. Après un rappel des spécificités HSE, le papier passera en revue les principales caractéristiques des données d'entrée, à savoir les images SAR et optiques. Ensuite, à partir des résultats de modélisation, on introduira les conditions d'observation optimales pour le radar et pour l'optique. Après cela, la capacité de détection sera présenté et illustrée pour le radar et pour l'optique. En optique, le traitement distingue a minima deux classes : fin et épais. Dans le contexte HSE, une base de données peut être utilisée pour identifier les produits détectés. La dernière étape est la quantification. Une méthode sophitiquée, s'appuyant sur la bande L en imagerie radar, sera utilisée pour identifier les pixels couverts par un film, ce qui signifie une présence l'huile en surface, et les pixels pour lesquels l'huile est sous forme de gouttelettes dans le volume. L'utilisation classique du SAR est aussi étendue à l'estimation de la concentration en huileau sein d'un mélange huile et eau de mer. Pour les données optiques, le traitement de quanticication le plus direct repose sur une classification automatique de type code de Bonn. Le code lie une classe avec une plage d'épaisseur et calcule un volume minimum et un volume maximum de produit dans chaque classe. Si le produit se trouve dans la base de données, une classification et une estimation de volume plus adaptées peuvent être faites. Si l'épaisseur est trop fine (signature spectrale due à l'absorption trop faible) ou trop épaisse (seule la partie supérieure de la couche de produit contribue au signal), une épaisseur estimée grâce à l'expérimentation en bassin est associée à chaque classe permettant de calculer un volume par classe et un volume global. Dans les autres cas, à court terme, la modélisation devrait permettre d'estimer l'épaisseur. Concernant les émulsions d'hydrocarbure, la modélisation en optique est en cours pour prédire l'épaisseur de peau et le contenu en eau.

International audience; Most satellite images are polluted by the presence of semi-transparent clouds, called cirrus, returning them unusable. Gao and Li (2017) have developed an empirical method for the correction of thin cirrus for Landsat-8, allowing to return to a clear sky apparent reflectance. Validated qualitatively, we propose here a quantitative validation method using Sentinel-2 data by comparing the corrected image with a clear sky reference image. Their method shows good results on dark surfaces, like water, with an apparent reflectance found close to 0.02. On the other hand, it becomes less accurate for thicker cirrus and on more reflective surfaces. In addition, the data analysis shows that pixels located in the shadow of the cirrus are over-corrected. The downward path should therefore be taken into account when correcting the signal.; Dans le domaine réflectif [0,4 - 2,5 μm], la télédétection par spectroscopie depuis l'espace permet d'accéder aux propriétés intrinsèques des surfaces, la réflectance, une fois les mesures corrigées des effets de l'atmosphère. Pour les scènes plates et sous l'hypothèse de réflectance lambertienne, cette correction atmosphérique est aujourd'hui très bien contrôlée en ciel clair. Mais statistiquement, les nuages couvrent environ les 2/3 de la surface Terrestre et réduisent donc considérablement le nombre d'images exploitables. Bien que des nuages épais comme le stratocumulus masquent complètement le paysage à acquérir, des cirrus fins, semi-transparents et situes à haute altitude, peuvent laisser entrevoir la surface sous-jacente mais induisent certains effets radiatifs qu'il convient de corriger pour retrouver la réflectance.Ce travail présentera une validation d'une méthode de correction des cirrus fins de la littérature.Dans un premier temps, une méthode de détection est développée par Gao et al. (1993). Elle est base sur l'utilisation simple d'une bande située près de 1.38 μm, qui est une bande d'absorption de vapeur d'eau saturée. Ensuite, une méthode de correction est proposée par Gao et al. (1995) dans la gamme spectrale [0,4 - 1,0 μm], ou ils supposent que le seul impact radiatif de tels nuages est du à la diffusion, qui ne dépend pas de la longueur d’onde (pas d’absorption). La méthode repose sur la correction d’une augmentation de la réflectance apparente, cause par la présence de cirrus. Cette correction est obtenue en utilisant un coefficient de corrélation calcule à partir de 2 bandes spectrales (1.38 vs 1.24 μm pour les surfaces d’eau et 1.38 vs 0.66 μm pour les surfaces mixtes). Plus récemment, Gao et al. (2017) ont amélioré la méthode en corrigeant chaque bande avec un coefficient distinct par bande n, calcule à partir de la corrélation linéaire entre la bande de cirrus (1.38 μm) et la bande n, et l'ont étendue au SWIR. Cette méthode est utilisée depuis de nombreuses années, mais sans validation quantitative. Aujourd'hui, avec l'avènement de la famille multispectrale Sentinel-2, grâce à sa haute revisite, nous avons la possibilité de réaliser cette validation en sélectionnant des couples d'images acquises sur la même scène, l'une avec cirrus et l'autre sous un ciel dégagé.L’étude a été initialement réalisée sur les surfaces d’eau et a donné de bons résultats avec des valeurs trouvées à 0,015 près, sur l’ensemble du spectre. Les cirrus plus épais (ρ * (1.38 μm)> 0.04) sont corriges avec la même précision. Cependant, la présence de nuages d'eau élevés ou de contrails perturbe l'estimation du coefficient de corrélation, ce qui entraine des erreurs plus importantes.Pour les surfaces continentales, la précision de la correction est plus difficile à analyser car celle-ci dépend du type de surface. La correction echoue dans le SWIR et aléatoirement entre 0.7 et 0.9 μm. En effet, pour une surface donnée, la présence de cirrus ne provoque pas nécessairement un décalage positif, entrainant une sur-correction de la méthode de Gao. Cela peut s’expliquer à partir de nos simulations, la méthode de Gao supposant un cirrus uniforme et homogène alors que le cirrus peut n'être présent que localement sur le trajet soleil-sol ou sur le trajet capteur-surface.Cette compréhension du phénomène conduira à proposer une amélioration du modèle de Gao et Li.

International audience; In the frame of the monitoring of Sentinel 2 MSI sensors in orbit, a method for inter-band calibration validation, using Antarctic site, has been developed and tested. The method relies on the directional hemispheric reflectance found in ASTER data base. In order to consider that the spectral shape of the directional directional reflectance is the same as the directional hemispheric one, wavelengths have to be limited to the spectral range below 0.9 µm. Thus this method cannot perform the inter-band calibration for the whole set of spectral bands of MSI but only from B1 to B8A. Results for B9 seem also correct although the central wavelength is a little bit beyond 0.9 µm. Given a clear day acquisition on DomeC site, a first set of computations of Top Of Atmosphere (TOA) reflectances for MSI spectral bands is performed using the three ASTER reflectances corresponding respectively to small, medium and coarse grain size for snow. The spectral reflectances are normalized by the B2 value. The comparison of the three normalized TOA reflectances to the actual one given by MSI enables to select the right snow grain size. Then the second step is the atmospheric parameters adjustment. Water content is assessed thanks to B9 band centered at 0.945 µm and ozone is assessed thanks to mainly B3 band centered at 0.56 µm. For a clear day, the aerosol optical thickness is weak and thus the TOA reflectance is not very sensitive to the more or less low abundance of continental aerosols. The ratio of normalized reflectance given by MSI to the normalized reflectance given by the computation is assessed for each spectral band between B1 and B9 and is compared to the inter-band calibration validations performed with other methods.; Dans le cadre du suivi en orbite du capteur MSI de Sentinel 2, une méthode de validation de l'étalonnage inter-bande a été développée et testée. La méthode s'appuie sur la réflectance hémisphérique - directionnelle que l'on trouve dans la base de données ASTER. Pour pouvoir considérer que la réflectance directionnelle - directionnelle est similaire à la réflectance hémisphérique - directionnelle, il faut se limiter aux longueurs d'onde inférieures à 0,9 µm. De ce fait, la méthode ne peut pas assurer la validation de l'étalonnage inter-bande pour l'ensemble des bandes spectrales de MSI mais uniquement pour les bandes B1 à B8A. Les résultats pour la bande B9 semblent également corrects bien que la longueur d'onde centrale soit un peu au delà de 0,9 µm.Pour une acquisition en ciel clair sur Dome C, un premier ensemble de réflectance en haut de l'atmosphère (TOA pour Top Of Atmosphère) pour les bandes spectrales de MSI est calculé en utilisant les trois réflectances ASTER correspondant à une taille de grain de neige respectivement petite, moyenne ou grosse. Les réflectances spectrales sont normalisées par leur valeur en B2. La comparaison des trois réflectances ainsi obtenues avec la réflectance réelle donnée par MSI permet de sélectionner la bonne taille de grain de neige. La seconde étape correspond à l'ajustement des paramètres atmosphériques. Le contenu en vapeur d'eau est estimé à partir de la bande B9 centrée à 0,945 µm et l'ozone est estimée à partir de la bande B3 centrée à 0,56 µm. En condition de ciel clair, l'épaisseur optique des aérosol est faible et de ce fait, la reflectance TOA n'est pas très sensible à l'abondance plus ou moins grande des aérosols continentaux. Le rapport de la réflectance normalisée fournie par MSI à la réflectance normalisée calculée est estimé pour chaque bande spectrale entre B1 et B9 et est comparé aux validations de l'étalonnage inter-bande réalisées avec d'autres méthodes.

International audience; In a very recent paper, we introduced (i) a specific hyper-spectral mixing model for the sea bottom, based on a detailed physical analysis which includes the adjacency effect, and (ii) an associated unmixing method, which is not blind in the sense that it requires a prior estimation of various parameters of that mixing model. We here proceed much further, by first analytically showing that this model can be seen as a specific member of the general class of mixing models involving spectral variability. Therefore, we then process such data with the IP-NMF and UP-NMF blind unmixing methods that we recently proposed in other works to handle spectral variability. Such a variability especially occurs when sea depth significantly varies over the considered scene, and we show that IP-NMF and UP-NMF then yield significantly better pure spectra estimation than a classical method from the literature which was not designed to handle such a variability.

Large-scale mapping of coastal oil spills and their monitoring over time is a major issue that can be adressed by using hyperspectral images and dedicated processing. Previous researches have shown that it is possible to map the polluted coastline caused by the explosion of the Deepwater Horizon (DwH) platform from AVIRIS images (AVIRIS: Airborne Visible/InfraRed Imaging Spectrometer). But the detection processes required either ground truth or laboratory spectra of hydrocarbons or were not fully automatic. In this paper we focused on an AVIRIS image which covers The Bay Jimmy, located south of New Orleans, and particularly impacted by oil pollution. Two automatic methods were developed to detect oiled coasts. In the first one, we have developed a new spectral index able to detect directly hydrocarbon and less sensitive to noise than indices proposed in previous works. The second one extracts endmembers via Orthogonal Subspace Projection, and then sorts the endmembers in terms of hydrocarbon indices scores, in descending order. Then, the detection map or the abundance map corresponding to the best endmember is used to map oiled areas. Both approaches give results consistent with those of studies previously conducted on the same image, and with maps built from field observations., La cartographie à grande échelle des marées noires côtières et leur suivi dans le temps est un problème majeur qui peut être résolu en utilisant des images hyperspectrales et un traitement dédié. Des recherches antérieures ont montré qu'il était possible de cartographier le littoral pollué par l'explosion de la plate-forme Deepwater Horizon (DwH) à partir d'images AVIRIS (AVIRIS : Airborne Visible/InfraRed Imaging Spectrometer). Mais les processus de détection nécessitaient soit l’utilisation de mesures in-situ, soit des spectres d'hydrocarbures en laboratoire, ou bien n'étaient pas entièrement automatiques.Dans cet article, nous nous sommes concentrés sur une image hyperspectrale AVIRIS qui couvre La Baie Jimmy, située au sud de la Nouvelle-Orléans, et particulièrement affectée par la pollution. Deux méthodes automatiques ont été mises au point pour détecter les côtes mazoutées. Dans la première, nous avons développé un nouvel indice spectral capable de détecter directement les hydrocarbures et moins sensible au bruit que les indices proposés dans les travaux précédents. La seconde utilise une méthode de démélange spectral, puis trie les pôles de mélange en termes d'indices d'hydrocarbure par ordre décroissant. Les cartes de détection ou d'abondance correspondant au meilleur pôle de mélange sont alors utilisées pour cartographier les zones mazoutées. Les deux approches donnent des résultats cohérents avec ceux d'études réalisées précédemment sur la même image et avec des cartes établies à partir d'observations sur le terrain.

International audience; A multiscale study was carried out under natural conditions for assessing the potential of vegetation reflectance to quantify soil Total Petroleum Hydrocarbons (TPH). The spectral signature of Rubus fruticosus L. was measured at leaf and canopy scales on an oil-contaminated site, and used for retrieving leaf pigment contents through inversion of PROSPECT and PROSAIL models. Leaf chlorophyll content was strongly related to soil TPH concentrations (R 2 ≥ 0.8), which allowed predicting TPH with good accuracy (RMSE < 4 g.kg-1). The quantification of TPH was also achieved at canopy scale (RMSE = 2.85 g.kg-1). The proposed method shows promising perspectives for oil prospection and contamination monitoring over vegetated areas. This method is under assessment on airborne hyperspectral images for applications over large scale.

International audience; To date, estimating oil thickness on the sea surface remains a challenge in most cases. When oil thickness estimation using optical data is limited by the absorption properties of the target, a solution consists in combining experimental and airborne hyperspectral data. We developed a method to identify thickness classes from hyperspectral data which, combined with realistic thickness values derived from a pool experiment, allows to estimate slick volume. Hyperspectral images of the same oil emulsion were acquired over a pool and at sea, under real conditions. From the pool data, we derived two classes: the sheen and the thick pixels, along with their respective thickness. These classes are then identified on the airborne images acquired during the NOFO campaign by generating a detection mask and using two classification approaches based on spectral indices. The proposed method allows to correctly identify the two thickness classes and, combined with the data from the pool experiment, provides a total slick volume larger than the one derived for the Bonn Agreement Oil Appearance Code.

International audience; Land surface emissivity is required for deriving surface temperature from thermal infrared radiances. When using single-channel or two-channel thermal infrared sensors, information on emissivity may be derived from spectral reflectance measurements through regression models. In this study, we present relationships derived over bare soils for Landsat 7 – ETM+ sensor. Reflectances in ETM+ channels were obtained from soil spectra (between 0.4 and 13 μm) extracted from the ASTER spectral library and the dataset acquired by Lesaignoux et al. (2013). The best relations were obtained between reflectances in the mid-infrared channels (ETM5 and ETM7) and the thermal infrared channel (ETM6) with correlation coefficients of 0.63 and 0.72 respectively. The relations were mostly generated by the variations of soil reflectances due to changes in soil moisture. Correlations were lower when considering the variations due to soil type.

International audience; The persistence of soil contamination after cessation of oil activities remains a major environmental issue in tropical regions. The assessment of the contamination is particularly difficult on vegetated sites, but promising advances in reflectance spectroscopy have recently emerged for this purpose. This study aimed to exploit vegetation reflectance for estimating low concentrations of Total Petroleum Hydrocarbons (TPH) in soils. A greenhouse experiment was carried out for 42 days on Cenchrus alopecuroides (L.) under realistic tropical conditions. The species was grown on oil-contaminated mud pit soils from industrial sites, with various concentrations of TPH. After 42 days, a significant decrease in plant growth and leaf chlorophyll and carotenoid contents was observed for plants exposed to 5–19 g kg−1 TPH in comparison to the controls (p 0.7). The same indices also succeeded in estimating the concentrations of TPH using random forest regression, at leaf and plant scales (RMSE = 1.46 and 1.63 g kg−1 and RPD = 5.09 and 4.44, respectively). Four out of the 33 indices contributed the most to the models (>75%). This study opens up encouraging perspectives for monitoring the cessation of oil activities in tropical regions. Further researches will focus on the application of our approach at larger scale, on airborne and satellite imagery.

To ensure confidence, measurements carried out by imaging radiometers mounted on satellites require robust validation using “fiducial quality” measurements of the same in situ parameter. For surface temperature measurements this is optimally carried out by radiometers measuring radiation emitted in the infrared region of the spectrum, collocated to that of a satellite overpass. For ocean surface temperatures the radiometers are usually on board ships to sample large areas but for land and ice they are typically deployed at defined geographical sites. It is of course critical that the validation measurements and associated instrumentation are internationally consistent and traceable to international standards. The Committee on Earth Observation Satellites (CEOS) facilitates this process and over the last two decades has organized a series of comparisons, initially to develop and share best practice, but now to assess metrological uncertainties and degree of consistency of all the participants. The fourth CEOS comparison of validation instrumentation: blackbodies and infrared radiometers, was held at the National Physical Laboratory (NPL) during June and July 2016, sponsored by the European Space Agency (ESA). The 2016 campaign was completed over a period of three weeks and included not only laboratory-based measurements but also representative measurements carried out in field conditions, over land and water. This paper is one of a series and reports the results obtained when radiometers participating in this comparison were used to measure the radiance temperature of the NPL ammonia heat-pipe blackbody during the 2016 comparison activities (i.e., an assessment of radiometer performance compared to international standards). This comparison showed that the differences between the participating radiometer readings and the corresponding temperature of the reference blackbody were within the uncertainty of the measurements, but there were a few exceptions, particularly for a reference blackbody temperature of −30°C. Reasons that give rise to the discrepancies observed at the low blackbody temperatures were identified.

International audience; This paper presents an approach for identifying the London plane in urban alignment based on hyperspectral data and contextual information. The proposed approach allows the London plane street trees of a study case to be perfectly identified thanks to both a supervised classification and a post regularization of the species prediction, based on the alignment membership derived from a Marked Point Process approach.

International audience; The future space joint-mission TRISHNA (Thermal infraRed Imaging Satellite for High-resolution Natural resource Assessment, CNES and ISRO) will allow to retrieve LST at 60 m spatial resolution every 3 days, improving the urban environment monitoring capacities. Two methods can be used to derive LST from remote sensing TIR data, Split-Window (SW) or TES (Temperature Emissivity Separation). Even if proven efficient, the complexity and heterogeneity of urban areas limit the performance of those methods. This paper focuses on the TES algorithm. For TES, errors can be generated by the impact of the surface roughness on the data. In order to investigate the efficiency of the future TRISHNA mission, research was conducted to evaluate the TES algorithm. To do so, the impacts of using a representative material database when using TES were explored and validated based on airborne or satellite data, and the impact of the surface geometry on the TES estimations was evaluated using 3D thermo-radiative model simulations. This study shows that TES can be used for TRISHNA images with a mean difference of 1.6 K between validation measurements and the retrieved LST for both daytime and nighttime images and that neglecting the impact of the surface geometry while performing TES could lead to errors up to 4 degrees C in LST estimations.

International audience; Mapping subsurface clay minerals is an important issue because they have particular behaviors in terms of mechanics and hydrology that directly affects assets laid at the surface such as buildings, houses, etc. They have a direct impact in ground stability due to their swelling capacities, constraining infiltration processes during flooding, especially when moisture is important. So detecting and characterizing clay mineral in soils serve urban planning issues and improve the risk reduction by predicting impacts of subsidence on houses and infrastruc-tures. High-resolution clay maps are thus needed with accurate indications on mineral species and abundances. Clay minerals, known as phyllosilicates, are divided in three main species: smectite, illite, and kaolinite. The smectite group highly contributes to the swelling behavior of soils, and because geotechnical soil analyses are expensive and time-consuming, it is urgent to develop new approaches for mapping clays' spatial distribution by using new technologies, e.g., ground spectrometer or remote hyperspectral cameras [0.4-2.5 μm]. These technics constitute efficient alternatives to conventional methods. We present in this chapter some recent results we got for characterizing clay species and their abundances from spectrometry, used either from a ground spectrometer or from hyperspectral cameras.

International audience; In-flight assessment of the radiometric performances of space-borne instruments can be achieved by means of vicarious calibration over Pseudo-Invariant Calibration Sites (PICS). PICS are chosen for the high temporal stability of their surface optical properties combined with a high spatial homogeneity. A first list of the main desert PIC sites was identified 20 years ago for the calibration of medium/coarse spatial resolution instruments in the solar spectral range (400–2500 nm). They are located in the Saharan desert and in the Arabian Peninsula. Six of them have since been endorsed by the CEOS/WGCV/IVOS as reference Calibration/Validation test sites. In this study, we have revisited the list of desert PIC sites at the global scale with the aim of (1) assessing if these twenty PICS are still “optimal”, in terms of temporal stability and spatial uniformity, and using up-to-date multi-spectral remote sensing data, and (2) identifying new calibration sites distributed over other areas of the world. We verified that the original sites remain very relevant, although alternate locations in their close vicinity have slightly better characteristics. We proposed four additional targets with similar characteristics, some of which may offer easier logistical access. In order to support radiative transfer simulations of satellite sensor measurements over the sites, we assessed the abilities of several semi-empirical models to reproduce the spectro-directional signatures of six IVOS sites and the four new candidate sites, and we derived climatologies of the main atmospheric properties (trace gas column load and aerosol optical depth).

Timely processing of observations from multi-spectral imagers, such as SEVIRI (Spinning Enhanced Visible and Infrared Imager), largely depends on fast radiative transfer calculations. This paper mostly concerns the development and implementation of a new forward model for SEVIRI to be applied to real time processing of infrared radiances. The new radiative transfer model improves computational time by a factor of &asymp, 7 compared to the previous versions and makes it possible to process SEVIRI data at nearly real time. The new forward model has been applied for the retrieval of surface parameters. Although the scheme can be applied for the simultaneous retrieval of temperature and emissivity, the paper mostly focuses on emissivity. The inverse scheme relies on a Kalman filter approach, which allows us to exploit a sequential processing of SEVIRI observations. Based on the new forward model, the paper also presents a validation retrieval performed with in situ observations acquired during a field experiment carried out in 2017 at Gobabeb (Namib desert) validation station. Furthermore, a comparison with IASI (Infrared Atmospheric Sounder Interferometer) emissivity retrievals has been performed as well. It has been found that the retrieved emissivities are in good agreement with each other and with in situ observations, i.e., average differences are generally well below 0.01.

The Indian and French Space Agencies, ISRO and CNES, have conceptualized a space-borne Thermal Infrared Reflectance (TIR) mission, TRISHNA (Thermal infRared Imaging Satellite for High-resolution Natural Resource Assessment). The primary design drivers of TRISHNA are the monitoring of (i) terrestrial water stress and use, and of (ii) coastal and continental water. A suit of four TIR bands and six optical bands is planned. The TIR bands will be centred at 8.6 μm, 9.1 μm, 10.3 μm and 11.5 μm to provide noon-night global observations at 57m nadir resolution over land and coastal regions. The field of view (FOV) is ±34° and the orbit of 761 km altitude was designed to allow 3 sub-cycle acquisitions during the 8-day cycle. The optical bands correspond to blue, green, red, and NIR plus two SWIR bands at 1.38 μm and 1.61 μm. The green, red, NIR and the 1.61 μm SWIR bands will have better radiometry quality than those of AWiFS. ISRO and CNES will develop optical and TIR payloads, respectively. Assessing evapotranspiration and furthermore Gross and Net Primary Productivity (GPP and NPP) will in turn assist in quantifying water use in rainfed and irrigated agriculture, water stress and water use efficiency, with expected applications to agricultural drought and early warning, crop yield prediction, water allocation, implementation of water rights, crop insurance business and agro-advisories to farmers. The other scientific objectives of TRISHNA are also briefly described. TRISHNA instrument will fly aboard a ISRO spacecraft scheduled to be launched from 2024 for a minimum period of 5 years’ mission lifetime.

International audience; Ceilometers are widely spread instruments mainly used for cloud base height determination. However, recent models are more sensitive to aerosols; hence, nowadays there is an increasing interest in these instruments to retrieve aerosol optical and microphysical properties.The high number of them distributed around the globe compared to the robust lidar systems and the fact that ceilometers work under unattended conditions are the main reasons behind this interest. In this paper a new methodology is proposed to retrieve aerosol vertical extinction and backscatter profiles from a Vaisala ceilometer CL51. This methodology is based in two parts: first, a signal pre-processing with a suppression of the dark current and background noises, and a correction of the water vapor absorption using near-real time temperature and absolute humidity (AH) profiles from a co-located Microwave radiometer (MWR). Then an iterative Klett-based algorithm that uses AERONET (AErosol RObotic NETwork) AOD (Aerosol Optical Depth) as an input to retrieve the extinction and backscatter profiles. The error analysis of the aerosol retrievals has been performed between MWR measurements and modelled radiosondes from HYSPLIT. The absolute errors found in temperature and AH are leading to errors in the pre-processed RCS signals up to 9%, and then in particle backscatter and particle extinction coefficients up to 2:2% and 25%, respectively.; Les ceilomètres sont des instruments très répandus, principalement utilisés pour déterminer la hauteur de la base des nuages. Cependant, des modèles récents sont plus sensibles aux aérosols ; c'est pourquoi, de nos jours, on s'intéresse de plus en plus à ces instruments pour mesurer des données optiques des aérosols et leurs propriétés microphysiques. Le nombre élevé de ces derniers, répartis dans le monde entier, par rapport aux systèmes lidar robustes et le fait que les plafonds fonctionnent dans des conditions non surveillées sont les principales raisons de cet intérêt. Dans ce document, une nouvelle méthodologie est proposée pour déterminer par inversion les profils d'extinction verticale et de rétrodiffusion des aérosols à partir d'un modèle CL51 de ceilomètre de Vaisala. Cette méthodologie est basée sur deux parties : premièrement, un prétraitement du signal avec une suppression du courant d'obscurité et du fond et une correction de l'absorption de la vapeur d'eau en utilisant des profils de température et d'humidité absolue (AH) en temps quasi réel d'un radiomètre à micro-ondes (MWR) colocalisé. Ensuite, un algorithme itératif basé sur Klett qui utilise AERONET (AErosol RObotic NETwork) AOD (Aerosol Optical Depth) comme entrée est appliquée pour récupérer les profils d'extinction et de rétrodiffusion. Les erreurs absolues trouvées dans la température et l'AH entraînent des erreurs dans les signaux RCS prétraités jusqu'à 9 %, puis dans les coefficients de rétrodiffusion et d'extinction des particules jusqu'à 2,2 % et 25 %, respectivement.

International audience; As marine transportation has increased in coastal regions, maritime accidents associated with vessels have steadily increased. Remotely sensed satellite or airborne images can aid rapid vessel monitoring over wide areas at high resolutions. In this study, airborne hyperspectral experiments were performed to detect marine vessels mainly including fishing boat and yacht by applying pixel-based mixture techniques and to estimate the size of the vessels through an objective ellipse fitting method. Various spectral libraries of marine objects and seawaters were constructed through in-situ experiments for spectral analysis of the internal structures of vessels. The hyperspectral images were dimensionally reduced through principal component analysis. Several hyperspectral mixture algorithms, such as N-FINDR, pixel purity index (PPI), independent component analysis (ICA), and vertex component analysis (VCA), were used for the detection of vessels. The N-FINDR and VCA techniques presented a total of 14 vessels, the ICA technique detected seven vessels, and the PPI technique detected two vessels. The pixel-based probability of detection (POD) and false alarm ratio (FAR) for all 14 vessels were 96.40% and 4.30%, respectively. The sizes of the vessels were estimated by extracting the boundaries of the vessels through a two-dimensional gradient and applying the ellipse fitting method. Compared with the digital mapping camera (DMC) images with resolutions of 0.10 m, the root-mean-square errors of the length and width of the vessels were approximately 1.19 m and 0.81 m, respectively. The application of spectral mixing methods provided a high probability of detecting the objects, as well as the overall structures of the decks of the vessels.

The modeling of radiative properties of soot particles can be addressed by a number of methods. Among them, the canonical Rayleigh-Debye-Gans (RDG) theory and the Superposition T-Matrix Method (STMM) are particularly well adapted to the task. Here, both RDG and STMM are used to model the radiative properties of two types of fractal aggregates indicative of soot relevant to lidar sensing. One type, a canonical aggregate with a chain-like morphology, corresponds to low-sooting flames and is well characterized by a single fractal dimension. The other type, a superaggregate, exhibits multiple fractal dimensions and is seen in heavily sooting flames. Radiative properties such as the differential scattering cross-section, total scattering cross-sections, backscattering cross-sections, and linear depolarization-ratio (LDR) are calculated for a range of wavelengths from 300 − 1100 nm while including the wavelength dependence of the soot refractive index. Of particular interest is that depolarization by a superaggregate is found to be approximately ten times larger than the depolarization by a canonical chain-like aggregate and both exhibit a power-law with wavelength. Results for specific wavelengths of interest to lidar (355, 532, and 1064 nm) are tabulated for lidar applications. Additionally, RDG theory yields fairly accurate results for modeling the radiative properties, including lidar relevant parameters such as backscattering cross-sections, only for canonical soot fractal aggregates.

International audience; A sensor's spatial resolution has traditionally been a difficult concept to define, but all would agree that it is inextricably linked to the Ground Sampling Distance (GSD) and Instantaneous Field of View (IFOV) of an imaging sensor system. As a measure of the geospatial quality of imagery, the Modulation Transfer Function (MTF) of the system is often used along with the signal-to-noise ratio (SNR). However, their calculation is not fully standardized. Further, consistent measurements and comparisons are often hard to obtain. Therefore, in the Infrared and Visible Optical Sensors (IVOS) subgroup of the Working Group on Calibration Validation (WGCV) of the Committee for Earth Observation Satellites (CEOS), a team from various countries and professional entities who are involved in MTF measurement was established to address the issue of on-orbit MTF measurements and comparisons. As a first step, a blind comparison of MTF measurements based on the slanted edge approach has been undertaken. A set of both artificial and actual satellite edge images was developed and a first comparison of processing results was generated. In all, seven organizations contributed to the experiment and several significant results were generated in 2016. No single participant produced the best results for all test images as measured by either the closest to the mean result, or closest to the truth for the synthetic test images. In addition, close estimates of the MTF value at Nyquist did not ensure the accuracy of other MTF values at other spatial frequencies. Some algorithm results showed that the accuracy of their estimates depended upon the type of MTF curve that was being analyzed. After the initial analysis, participants were allowed to modify their methodology and reprocess the test images since, in several cases, the results contained errors. Results from the second iteration, in 2017, verified that the anomalies in the experiment's first iteration were due to errors in either coding or methodology, or both. One organization implemented a third trial to fix software errors. This emphasizes the importance of fully understanding both methodology and implementation, in order to ensure accurate and repeatable results. To extend this comparison study, a reference data set, which is composed of edge images and corresponding MTF curves, will be built. A broader audience will be able to access the edge images through the CEOS CalVal Portal (http://calvalportal.ceos.org/. This paper, which is associated with the reference data set, can serve as a new tool to either implement or check, or both, the MTF measurement that relies on the slanted edge method.; La résolution spatiale d’un capteur a toujours été un concept difficile à définir, mais il est acquis qu’elle est intimement liée à au pas d’échantillonnage au sol et au champ de vue instantanné d’un système imageur. En tant que mesure de la mesure de la qualité image géospatiale, la Fonction de Transfert de Modulation (FTM) du système est souvent utilisée avec le Rapport Signal à Bruit (RSB). Cependant, le calcul de ces grandeurs n’est pas totalement standardisé et des mesures et de comparaisons cohérentes sont souvent difficiles à obtenir. De ce fait, dans le cadre du sous groupe Capteurs Optiques Visibles du groupe de travail sur l’étalonnage et la validation du Comité pour les satellites d’observation de la terre, un groupe de personnes issues de différents pays et de différentes entités professionnelles impliquées dans la mesure de FTM a été formé pour travailler sur la problématique de la mesure de FTM et des comparaison de mesures. Pour la première étape du travail, une comparaison en aveugle, concernant la méthode du bord de plage, a été organisée. Un jeu d’images satellitaires, à la fois artificielles et réelles, a été créé et une première comparaison des résultats de calcul de FTM a été faite. En tout, sept organisations différentes ont participé à l’expérience et ont conduit à des résultats intéressants en 2016. Aucun participant n’a obtenu le meilleur résultat, au sens le plus proche de la moyenne ou bien le plus proche de la FTM attendue, dans tous les cas. Il est également apparu qu’une bonne estimation de la valeur de la FTM à la fréquence de Nyquist ne garantissait pas une bonne estimation pour les autres fréquences spatiales. Certains algorithmes ont des résultats dont la précision dépend de la forme de la FTM. Après cette première analyse des résultats, les participants ont pu modifier leur méthodologie et retraiter les données car il y avait clairement des erreurs dans les premiers résultats. Les second résultats, en 2017, ont permis de vérifier cela. Une organisation a fait un troisième retraitement des données pour corriger un bug et valider son résultat. Tout ceci souligne l’importance de bien comprendre non seulement la méthodologie mais également son implémentation, de manière à obtenir des résultats reproductibles et fiables. A la suite de ce travail, un jeu de données de référence composé d’images et des courbes de FTM correspondantes va être construit. Il est prévu de donner accès aux images à travers le CalVal Portal et de les rendre disponibles à un large ensemble d’utilisateurs.

International audience; The use of hyperspectral spectroscopy for oil detection recently sparked a growing interest for risk assessment over vegetated areas. In a perspective of image applications, we conducted a greenhouse experiment on a brownfield-established species, Rubus fruticosus L. (bramble), to evaluate the potential of vegetation reflectance to detect and discriminate among various oil-contaminated soils. The species was grown for 32 days on four different soils with mixtures of petroleum hydrocarbons and heavy metals. Additional plants were grown on either uncontaminated control or water-deficient soils for comparison. Repeated reflectance measurements indicated modified spectral signatures under both oil and water-deficit exposure, from leaf to multi-plant scales. The amplitude of the response varied with mixture composition, exposure time, acquisition scale and spectrum region. Reflectance changes were linked to alterations in chlorophyll, carotenoid and water contents using vegetation indices. These indices were used to catch spectral similarities among acquisition scales and to discriminate among treatments using Kendall’s coefficient of concordance (W) and regularized logistic regression. Of the 33 vegetation indices tested, 14 were concordant from leaf to multi-plant scales (W > 0.75, p < 0.05) and strongly related to leaf biochemistry (R2 > 0.7). The 14 indices allowed discriminating between each mixture and the control treatment with no or minor confusions (≤ 5 %) at all acquisition scales, depending on exposure time. Some of the mixtures remained difficult to discriminate among them and from the water-deficit treatment. The approach was tested at the canopy scale under natural conditions and performed well for identifying bramble exposed to either one of the experimentally-tested mixtures (90 % accuracy) or to uncontaminated soil (83 % accuracy). This study provided better understanding of vegetation spectral response to oil mixtures and opens up promising perspectives for future applications.

International audience; This study presents the averaged lidar-relevant radiative properties of numerically generated soot fractal aggregate ensembles. The radiative properties of these aggregates have been computed using the Superposition T-Matrix Method, with emphasis put on those that are most relevant to lidar application; the backscattering and extinction cross-sections, the Lidar Ratio and the Linear Depolarization Ratio. These lidar-relevant radiative properties have been computed over a broad spectrum, going from the ultraviolet to the near infrared, in order to address lidar instrument need for a priori knowledge in signal inversion procedures and measurement analysis. By averaging the computed radiative properties according to each set of morphological parameters, we obtain statistically representative results and we study the impacts of morphological changes on these lidar-relevant radiative properties. Our results show a strong impact of the primary particle radius on all considered radiative properties, while the number of primary particles induce significant variations on the cross-sections only. The fractal dimension, although being an essential morphological parameter, has a weak influences on the lidar-relevant radiative properties.

International audience; In this paper we focus on airborne hyperspectral imaging methodology to characterize PM (Particulate Matter) near industrial emission sources. Two short-term intensive campaigns were carried out in the vicinity of a refinery in the South of France, in September 2015 and February 2016. Different protocols of in-situ PM measurements were performed, at stack measurements (flow rate and offline chemical analysis) and on-line measurement at the refinery border (size distribution, concentration and chemistry of aerosols). A multi temporal methodology to retrieve aerosol type, to map the aerosol concentration and to quantify mass flow rate from airborne hyperspectral data is described in this paper. This method applied to the refinery detected plume from the main stack yields a black carbon to sulfate ratio of 10/90 in mass inside the plume, with an average size distribution smaller than 100 nm. These results are in a good agreement with on-line analysis of aerosols at refinery border. The resulting quantitative map with a metric spatial resolution leads to a flow rate estimated of about 1g/s and is in a good agreement with in-situ stack measurements and modelling.; Ce papier propose une méthodologie de caractérisation des PM (Particulate Matter) proches des sources industrielles par imagerie hyperspectrale aéroportée. Il s’appuie sur deux campagnes de mesures réalisées autour d’une raffinerie dans le sud de la France en Septembre 2015 et Février 2016. Différents protocoles de mesures in-situ des PM ont été réalisées dans ce cadre, mesures au niveau de l’émissaire principal (debit et analyse chimique) et mesures on-line au voisinage de la raffinerie (distribution en taille, concentration et analyse chimique). Une méthodologie multi-temporelle dédiée à l’inversion des types d’aérosols présents dans le panache permettant de fournir une carte en concentration d’aérosols et d’estimer le débit est décrite dans ce papier. Appliquée à ce cas d’étude, les resultats hyperspectraux ont permis d’estimer un rapport suie/sulfate de 10/90 en masse dans le panache avec une distribution en taille inférieure à 100nm. Ces résultats sont en bon accord avec les mesures in-situ. Les cartes en concentration obtenue à une resolution métrique permettent d’estimer un debit de l’ordre de 1g/s en bon accord avec les mesures in-situ au niveau de l’émissaire et avec les résultats de modélisation de dispersion des aerosols.

International audience; The monitoring of the water cycle at the Earth surface which tightly interacts with the climate change processes as well as a number of practical applications (agriculture, soil and water quality assessment, irrigation and water resource management, etc...) requires surface temperature measurements at local scale. Such is the goal of the Indian-French high spatio-temporal TRISHNA mission (Thermal infraRed Imaging Satellite for High-resolution Natural resource Assessment). The scientific objectives of the mission and research work conducted to consolidate the mission specifications are presented. Progress in modelling of surface fluxes is then discussed. The main specifications of the mission such as the revisit, the spatial resolution, the overpass time, the spectral bands and the orbit are analyzed and justified. The resulting baseline of the mission is given.

International audience; In California, water is a perennial concern. As competition for water resources increases due to growth in population, California’s tree nut farmers are committed to improving the efficiency of water used for food production. There is an imminent need to have reliable methods that provide information about the temporal and spatial variability of crop water requirements, which allow farmers to make irrigation decisions at field scale. This study focuses on estimating the actual evapotranspiration and crop coefficients of an almond and pistachio orchard located in Central Valley (California) during an entire growing season by combining a simple crop evapotranspiration model with remote sensing data. A dataset of the vegetation index NDVI derived from Landsat-8 was used to facilitate the estimation of the basal crop coefficient (Kcb), or potential crop water use. The soil water evaporation coefficient (Ke) was measured from microlysimeters. The water stress coefficient (Ks) was derived from airborne remotely sensed canopy thermal-based methods, using seasonal regressions between the crop water stress index (CWSI) and stem water potential (Ψstem). These regressions were statistically-significant for both crops, indicating clear seasonal differences in pistachios, but not in almonds. In almonds, the estimated maximum Kcb values ranged between 1.05 to 0.90, while for pistachios, it ranged between 0.89 to 0.80. The model indicated a difference of 97 mm in transpiration over the season between both crops. Soil evaporation accounted for an average of 16% and 13% of the total actual evapotranspiration for almonds and pistachios, respectively. Verification of the model-based daily crop evapotranspiration estimates was done using eddy-covariance and surface renewal data collected in the same orchards, yielding an R2 ≥ 0.7 and average root mean square errors (RMSE) of 0.74 and 0.91 mm·day−1 for almond and pistachio, respectively. It is concluded that the combination of crop evapotranspiration models with remotely-sensed data is helpful for upscaling irrigation information from plant to field scale and thus may be used by farmers for making day-to-day irrigation management decisions.; En Californie, l’eau est une préoccupation constante. À mesure que la concurrence pour les ressources en eau augmente, la croissance de la population augmente. Il existe un besoin imminent de disposer de méthodes fiables pour fournir des informations sur la variabilité temporelle et spatiale des besoins en eau des cultures. Cette étude porte sur l'estimation des coefficients d'évaporation et des cultures d'un verger d'amandiers et de pistaches situé dans la Central Valley, en Californie, pendant toute une saison de croissance, en combinant un modèle simple d'évapotranspiration des cultures avec des données de télédétection. Un ensemble de données de l'indice de végétation NDVI dérivé de Landsat-8 a été utilisé pour faciliter l'estimation du coefficient de culture de base (Kcb) ou de l'utilisation potentielle de l'eau par la culture. Le coefficient d'évaporation de l'humidité du sol (Ke) a été mesuré à partir de microlysimètres. Le coefficient de stress hydrique (Ks) a été calculé à l'aide de méthodes thermiques basées sur le couvert forestier et télédétectées en vol, à l'aide de régressions saisonnières entre l'indice de stress hydrique des cultures (CWSI) et le potentiel hydrique de la tige (stem). Ces régressions étaient statistiquement significatives pour les deux cultures, indiquant de nettes différences saisonnières dans les pistaches, mais pas dans les amandes. Dans les amandes, les valeurs maximales estimées de Kcb se situaient entre 1,05 et 0,90, tandis que pour les pistaches, elles se situaient entre 0,89 et 0,80. Le modèle indiquait une différence de transpiration de 97 mm au cours de la saison entre les deux cultures. L'évaporation du sol représentait en moyenne 16% et 13% de l'évapotranspiration réelle totale d'amandes et de pistaches, respectivement. La vérification de l'évapotranspiration quotidienne des cultures basée sur un modèle a été effectuée à l'aide des données de covariance de Foucault et de renouvellement de la surface recueillies dans les mêmes vergers, conduisant à un R2 ≥ 0,7 et des erreurs moyennes de racine carrée (RMSE) de 0,74 et 0,91 mm · jour-1 pour amande et pistache, respectivement. Il est conclu que la combinaison de modèles d'évapotranspiration de cultures et de données de télédétection est utile pour augmenter l'information d'irrigation de l'échelle de la plante au champ et peut donc être utilisée par les agriculteurs pour prendre des décisions quotidiennes de gestion de l'irrigation.

International audience; With the current expansion of cities, urban trees have an important role for preserving the health of its in- habitants. With their evapotranspiration, they reduce the urban heat island phenomenon, by trapping CO2 emission, improve air quality. In particular, street trees or alignment trees, create shade on the road network, are structuring elements of the cities and decorate the roads. Street trees are also subject to specific conditions as they have little space for growth, are pruned and can be affected by the spread of diseases in single-species plantations. Thus, their detection, identification and monitoring are necessary. In this study, an approach is proposed for mapping these trees that are characteristic of the urban environment. Three areas of the city of Toulouse in the south of France are studied. Airborne hyperspectral data and a Digital Surface Model (DSM) for high vegetation detection are used. Then, contextual information is used to identify the street trees. Indeed, Geographic Information System (GIS) data are considered to detect the vegetation canopies close to the streets. Afterwards, individual street tree crown delineation is carried out by modeling the discriminative contextual features of individual street trees (hypotheses of small angle between the trees and similar heights) based on Marked Point Process (MPP). Compared to a baseline individual tree crown delineation method based on region growing, our method logically provides the best results with F-score values of 91%, 75% and 85% against 70%, 41% and 20% for the three studied areas respectively. Our approach mainly succeeds in identifying the street trees. In addition, the contribution of the angle, the height and the GIS data in the street tree mapping has been studied. The results encourage the use of the angle, the height and the GIS data together. However, with only the angle and the height, the results are similar to those obtained with the inclusion of the GIS data for the first and the second study cases with F-score values of 88%, 79% and 62% against 91%, 75% and 85% for the three study cases respectively. Finally, it is shown that the GIS data only is not sufficient.

As compared to near InfraRed passive instruments, lidars reduce the blases on the measurement of concentrations in the presence of diffusion by aerosols, but until recent days they were limited to one active wavelength at a time.CNES and ONERA conceived a novel type of lidar based on short frequency combs that provides the spectrum of a complete absorption line of the target molecule. The technique of Dual Comb Spectroscopy is adapted to short (up to 13 teeth) combs, as a compromise between spectral richness and Signal to Noise Ratio. The advantages of DCS remain: reduction of the impact of scene evolutions and spectral mis-calibration. The latter will make the high power laser emitters easier. Above all, the acquisition of a complete absorption line opens the path to the retrieval of two or more independent elements in the vertical profile of molecule concentration.We describe the technique of comb generation, the layout of the emitter section and the detection principles. Then we introduce the Short Comb Atmospheric Lidar Experiment (SCALE) project led by CNES in the frame of a new advance "phase 0" study. We expose the preliminary performances of this space lidar that could fit on a microsatellite platform in the case of CO2 sounding at 1.57 or 2 um.Results of CNES-ONERA four-year R&T activities are also presented that validate in the laboratory and in open space the short comb lidar.Finally first results of retrieval simulations are exposed., Les lidars réduisent l'imprécision des instruments passifs sur l'estimation de la distance sondée, donc sur la concentration de la molécule ciblée dans l'atmosphère. Mais jusqu'à récemment, les lidars étaient limités à une seule longueur d'onde active à la fois.Le CNES et l'ONERA ont conçu un nouveau type de lidar basé sur des mini- peignes de fréquence qui fournissent le spectre d'une ligne d'absorption complète de la molécule cible. La technique de la spectroscopie à double peigne (DCS) est adaptée aux mini-peignes (jusqu'à 13 dents), qui fait un compromis entre la richesse spectrale et le rapport signal/bruit. Les avantages du DCS sont : réduction de l'impact des évolutions temporelles de la scène, étalonnage auto spectral, étalement spectral de l'énergie par rapport au seuil de Brillouin. Ce dernier avantage facilitera la réalisation des émetteurs laser à haute puissance. L'acquisition d'une ligne d'absorption complète ouvre la voie à la récupération de deux ou plusieurs éléments indépendants (DOFS) dans le profil vertical de la concentration moléculaire.Nous décrivons la technique de génération de peigne, l'architecture de la section émettrice et les principes de détection. Nous présentons ensuite le projet SCALE (Short Comb Atmospheric Lidar Experiment) que le CNES étudiera prochainement dans le cadre d'une nouvelle étude avancée de "phase 0". Nous exposons les performances préliminaires de ce lidar spatial qui pourrait tenir sur une plate-forme microsatellite dans le cas d'un sondage CO2 à 1,5 µm.Enfin, les résultats des activités de R&T quadriennales du CNES-ONERA sont présentés pour valider en laboratoire et en espace libre le lidar a mini-peigne.

International audience; This paper is focused on the retrieval of industrial aerosol optical thickness (AOT) and microphysical properties by means of airborne imaging spectroscopy. Industrial emissions generally lead to optically thin plumes requiring an adapted detection method taking into account the weak proportion of particles sought in the atmosphere. To this end, a semi-analytical model combined with the Cluster-Tuned Matched Filter (CTMF) algorithm is presented to characterize those plumes, requiring the knowledge of the soil under the plume. The model allows the direct computation of the at-sensor radiance when a plume is included in the radiative transfer. When applied to industrial aerosol classes as defined in this paper, simulated spectral radiances can be compared to ‘real’ MODTRAN (Moderate Resolution Atmospheric Transmission) radiances using the Spectral Angle Mapper (SAM). On the range from 0.4 to 0.7 µm, for three grounds (water, vegetation, and bright one), SAM scores are lower than 0.043 in the worst case (a both absorbing and scattering particle over a bright ground), and usually lower than 0.025. The darker the ground reflectance is, the more accurate the results are (typically for reflectance lower than 0.3). Concerning AOT retrieval capabilities, with a pre-calculated model for a reference optical thickness of 0.25, we are able to retrieve plume AOT at 550 nm in the range 0.0 to 0.4 with an error usually ranging between 9% and 13%. The first test case is a CASI (Compact Airborne Spectrographic Imager) image acquired over the metallurgical industry of Fos-sur-Mer (France). First results of the use of the model coupled with CTMF algorithm reveal a scattering aerosol plume with particle sizes increasing with the distance from the stack (from detection score of 54% near the stack for particles with a diameter of 0.1 µm, to 69% away from it for 1.0 µm particles). A refinement is made then to estimate more precisely aerosol plume properties, using a multimodal distribution based on the previous results. It leads to find a mixture of sulfate and brown carbon particles with a plume AOT ranging between 0.2 and 0.5. The second test case is an AHS (Airborne Hyperspectral Scanner) image acquired over the petrochemical site of Antwerp (Belgium). The first CTMF application results in detecting a brown carbon aerosol of 0.1 µm mode (detection score is 51%). Refined results show the evolution of the AOT decreasing from 0.15 to 0.05 along the plume for a mixture of brown carbon fine mode and 0.3 µm radius of sulfate aerosol.

International audience; Sea bottom unmixing is a challenging task for the analysis of coastal zones. Actually the upward photons are attenuated and diffused by the water column layer, giving low signal to noise hyperspectral data. A classical approach is to perform inversion of the water column using semi-analytical parametric models and estimation process, and obtain the water column constituents (chlorophyll, suspended matter, dissolved organic matter and bathymetry), and the coefficients of pure materials reflectance spectra (endmembers), given in spectral libraries, for each pixel. We consider here the case of unknown endmembers, and we suppose that the water column components have been obtained by a classical inversion method or in-situ measurements. For each observed pixel the upward luminance is analysed and decomposed into three terms, respectively issued after interaction with the target bottom pixel, its neighbours, and the water column. We show that in some conditions the adjacent pixels effect is not negligible, due to the diffusion in the water column, and we develop in accordance a new mixing model for the sea bottom. We propose a non-negative matrix factorisation based unmixing method to solve the problem, and present results for hyperspectral data simulations.

International audience; As part of the Copernicus programme of the European Commission (EC), the European Space Agency (ESA) operates the Sentinel-2 mission that acquires high spatial resolution optical imagery. The consistency of the image time series is ensured by some specific performance requirements such as multi-temporal spatial registration and radiometric stability, routinely monitored by the Sentinel-2 Mission Performance Centre (S2MPC). The products also provide a rich set of metadata and auxiliary data to support high-level processing activities. This presentation provides a description of the main level-1 products calibration and validation activities, performed by the S2MPC including several Expert Support Laboratories (ESL). Measured performances and analysed results show the good quality of the mission products both in terms of radiometry and geometry. The current performances for Sentinel-2A and Sentinel-2B are compared to mission product quality requirements.

International audience; Towns are characterized by a strong intern dynamic, a very high spatial heterogeneity of their elements, their 3D geometric shapes (horizontal and vertical) inducing shadows, and their large variety of materials. These characteristics make the collection of information of land surface properties and urban descriptors more delicate. Due to the enhancement of spatial resolution capacities,[virgule] multispectral imagery can provide a wide range of information to deepen the observation of urban areas. Nevertheless, such a type of sensors would not contribute to the characterization of the urban land surface properties (chemical composition of materials, species of vegetation, quality of soils, etc.). Hyperspectral imagery capacities might be considered as providing useful products by themselves and show great potentials but it becomes mandatory to define which type of information can be delivered by these different sensors. The ANR HYEP project 1 has the purpose to demonstrate the benefit of a second generation of hyperspectral space borne mission characterized by a high spatial resolution (8m GSD) and a high temporal revisit. After a detailed description of the motivation of such a proposal, applications are given focused on urban vegetation, sealed and impervious areas, solar panel area estimation.

Remote sensing technologies can be applied for a wide range of gas leak flowrates and in three main cases: (1) major leaks in crisis management; (2) medium size leaks in safety monitoring; (3) small leaks in environmental monitoring.A gas test campaign, conducted by Total, the ONERA – the French Aerospace Lab – and ADCIS in September 2015 using three hyperspectral infrared cameras from Telops, confirmed our capacity to visualize in 3D and quantify in real time plumes of methane in the range of 1 g/s to 50g/s. The R&D project on gas remote quantification continued with a second gas test campaign in 2017.The second gas test campaign was organized on Total's Lacq Pilot Platform in France and involved several gas spectral imaging systems: (1) mobile hyperspectral cameras in the Long-Wavelength InfraRed (LWIR) band (7.7-12μm); (2) a multispectral camera in the LWIR band (7-9μm); (3) a multigas lidar (LIght Detection And Ranging) system coupled with a wind lidar system; (4) five other international teams (US, Spain, Norway and France) were also invited to assess the capacity of their remote-sensing systems to quantify methane and carbon dioxide releases.The two-week test demonstrated that methane leak emissions ranging from 0.7 g/s to 140 g/s could be visualized and quantified in real time using a mobile Telops Hyper-Cam. This campaign also served to validate the performance of several remote sensing technologies.Total's Lacq Pilot Platform is a test area for qualifying cost-effective systems designed to complement the gas detection system of a plant and provide valuable information should a gas leak incident occur. New methodologies for the early detection of anomalies using remote observation systems including drones, robots and artificial intelligence data processing systems are currently being investigated there.