A new global fAPAR and LAI dataset derived from optimal albedo estimates: comparison with MODIS products

We present the first comparison between new fAPAR and LAI products derived from the GlobAlbedo dataset and the widely-used MODIS fAPAR and LAI and products. The GlobAlbedo derived products are produced using a 1D two-stream radiative transfer (RT) scheme designed explicitly for global parameter retrieval from albedo, with consistency between RT model assumptions and observations, as well as with typical large-scale land surface model RT schemes. The approach does not require biome-specific structural assumptions (e.g. cover, clumping, understory), unlike more detailed 3D RT model approaches. GlobAlbedo-derived values of fAPAR and LAI are compared with MODIS values over 2002-2011 at multiple flux tower sites within selected biomes, over 1200 × 1200 km regions and globally. GlobAlbedo-derived fAPAR and LAI values are temporally more stable than the MODIS values due to (1) the smoothness of the underlying albedo, derived via optimal estimation (assimilation) using an a priori estimate of albedo derived from an albedo ‘climatology’ (composited multi-year albedo observations) and (2) space-time invariant prior information in the inversion of the two-stream RT scheme. Parameters agree closely in timing but with GlobAlbedo values consistently lower than MODIS, particularly for LAI. Larger differences occur in winter (when values are lower) and in the Southern hemisphere. Globally, we find that: GlobAlbedo-derived fAPAR is ~0.9- 1.01 × MODIS fAPAR with an offset of ~0.03; GlobAlbedo-derived LAI is ~0.6 × MODIS LAI with an offset of ~0.2. Differences arise due to the RT model assumptions underlying the products, meaning care is required in interpreting either set of values, particularly when comparing to finescale ground-based estimates. We present global calibrations between GlobAlbedo-derived and MODIS products.JRC.H.5-Land Resources Managemen

Fonctions de Croyance et Indexation Multimodale<br />Application à l'Identification de Personnes dans des Albums

This thesis presents an information fusion strategy for digital photograph semi-automatic indexing using people's identities. The final goal of this work is to help users to recognize the identities of people in photo. Our fusion process is named -FUSINDEX-. It has been integrated in a webbased management application which allows user to share photos with a community and add textual and vocal comments to a selected photo. Fusindex combines the information issued from multiple modalities suchas image, text, speech, social context, date and geographic position. We used several indexing engines. Each one of these engines analysis a single modality: the image itself, textual comments and vocal comments. But in this paper we focalize essentially on engines which analyze theimage. The algorithms of Fusindex are based on the evidence theory of Dempster-Shafer in order to manage, as well as possible the imprecision and the uncertainty of the results obtained by the indexing engines.Cette thèse se situe dans la cadre de l'organisation semi-automatique d'albums photo et s'intègre dans un cadre applicatif particulier d'un prototype de service développé par la division recherche et développement de France Telecom. Dans ce cadre applicatif, les photos peuvent être partagées entre plusieurs personnes et peuvent êtres commentées vocalement et/ou textuellement par ces déférents utilisateurs. Le processus d'indexation développé dans cette thèse ne se limite pas seulement à l'indexation d'une collection d'images mais traite également leurs commentaires associés ce qui rend ces contenus multimédia. D'autres informations peuvent également être associées aux photos comme les dates et les lieux d'acquisition de l'image (qui sont connus avec une grande précision grâce notamment au développement de moyens de géo-localisation des appareils multimédia) et peuvent êtres exploitées pour l'organisation de la base. Ainsi, le travail envisagé dans le cadre de cette thèse se focalise sur des documents multimédias avec déférentes modalités : image, texte, son et données. L'un des objectifs à atteindre concerne la fusion des informations issues de ces déférentes modalités dans le but d'identifier les personnages figurant dans les images qui permettent ainsi d'indexer les documents. Chacun des documents de la collection est représenté par ses contenus relatifs aux déférents médias mais est aussi considéré dans son contexte. Pour analyser chaque contenu d'un document, nous utilisons des outils d'indexation qui leur sont spécifiques. Le contexte d'une image est exploité à partir de descripteurs déjà calculés sur des documents de la base en exploitant les dates et lieux d'acquisition des images associées. La contribution essentielle de ce travail concerne donc l'indexation de documents multimédia par leur contenu et leur contexte

Assessment of Satellite-Derived Surface Reflectances by NASA’s CAR Airborne Radiometer over Railroad Valley Playa

CAR (Cloud Absorption Radiometer) is a multi-angular and multi-spectral airborne radiometer instrument, whose radiometric and geometric characteristics are well calibrated and adjusted before and after each flight campaign. CAR was built by NASA (National Aeronautics and Space Administration) in 1984. On 16 May 2008, a CAR flight campaign took place over the well-known calibration and validation site of Railroad Valley in Nevada, USA (38.504°N, 115.692°W). The campaign coincided with the overpasses of several key EO (Earth Observation) satellites such as Landsat-7, Envisat and Terra. Thus, there are nearly simultaneous measurements from these satellites and the CAR airborne sensor over the same calibration site. The CAR spectral bands are close to those of most EO satellites. CAR has the ability to cover the whole range of azimuth view angles and a variety of zenith angles depending on altitude and, as a consequence, the biases seen between satellite and CAR measurements due to both unmatched spectral bands and unmatched angles can be significantly reduced. A comparison is presented here between CAR’s land surface reflectance (BRF or Bidirectional Reflectance Factor) with those derived from Terra/MODIS (MOD09 and MAIAC), Terra/MISR, Envisat/MERIS and Landsat-7. In this study, we utilized CAR data from low altitude flights (approx. 180 m above the surface) in order to minimize the effects of the atmosphere on these measurements and then obtain a valuable ground-truth data set of surface reflectance. Furthermore, this study shows that differences between measurements caused by surface heterogeneity can be tolerated, thanks to the high homogeneity of the study site on the one hand, and on the other hand, to the spatial sampling and the large number of CAR samples. These results demonstrate that satellite BRF measurements over this site are in good agreement with CAR with variable biases across different spectral bands. This is most likely due to residual aerosol effects in the EO derived reflectances

Sea Ice Albedo from MISR and MODIS: Production, Validation, and Trend Analysis

The Multi-angle Imaging SpectroRadiometer (MISR) sensor onboard the Terra satellite provides high accuracy albedo products. MISR deploys nine cameras each at different view angles, which allow a near-simultaneous angular sampling of the surface anisotropy. This is particularly important to measure the near-instantaneous albedo of dynamic surface features such as clouds or sea ice. However, MISR&#8217;s cloud mask over snow or sea ice is not yet sufficiently robust because MISR&#8217;s spectral bands are only located in the visible and the near infrared. To overcome this obstacle, we performed data fusion using a specially processed MISR sea ice albedo product (that was generated at Langley Research Center using Rayleigh correction) combining this with a cloud mask of a sea ice mask product, MOD29, which is derived from the MODerate Resolution Imaging Spectroradiometer (MODIS), which is also, like MISR, onboard the Terra satellite. The accuracy of the MOD29 cloud mask has been assessed as &gt;90% due to the fact that MODIS has a much larger number of spectral bands and covers a much wider range of the solar spectrum. Four daily sea ice products have been created, each with a different averaging time window (24 h, 7 days, 15 days, 31 days). For each time window, the number of samples, mean and standard deviation of MISR cloud-free sea ice albedo is calculated. These products are publicly available on a predefined polar stereographic grid at three spatial resolutions (1 km, 5 km, 25 km). The time span of the generated sea ice albedo covers the months between March and September of each year from 2000 to 2016 inclusive. In addition to data production, an evaluation of the accuracy of sea ice albedo was performed through a comparison with a dataset generated from a tower based albedometer from NOAA/ESRL/GMD/GRAD. This comparison confirms the high accuracy and stability of MISR&#8217;s sea ice albedo since its launch in February 2000. We also performed an evaluation of the day-of-year trend of sea ice albedo between 2000 and 2016, which confirm the reduction of sea ice shortwave albedo with an order of 0.4&#8315;1%, depending on the day of year and the length of observed time window

Intercomparison of Surface Albedo Retrievals from MISR, MODIS, CGLS Using Tower and Upscaled Tower Measurements

Surface albedo is of crucial interest in land&ndash;climate interaction studies, since it is a key parameter that affects the Earth&rsquo;s radiation budget. The temporal and spatial variation of surface albedo can be retrieved from conventional satellite observations after a series of processes, including atmospheric correction to surface spectral bi-directional reflectance factor (BRF), bi-directional reflectance distribution function (BRDF) modelling using these BRFs, and, where required, narrow-to-broadband albedo conversions. This processing chain introduces errors that can be accumulated and then affect the accuracy of the retrieved albedo products. In this study, the albedo products derived from the multi-angle imaging spectroradiometer (MISR), moderate resolution imaging spectroradiometer (MODIS) and the Copernicus Global Land Service (CGLS), based on the VEGETATION and now the PROBA-V sensors, are compared with albedometer and upscaled in situ measurements from 19 tower sites from the FLUXNET network, surface radiation budget network (SURFRAD) and Baseline Surface Radiation Network (BSRN) networks. The MISR sensor onboard the Terra satellite has 9 cameras at different view angles, which allows a near-simultaneous retrieval of surface albedo. Using a 16-day retrieval algorithm, the MODIS generates the daily albedo products (MCD43A) at a 500-m resolution. The CGLS albedo products are derived from the VEGETATION and PROBA-V, and updated every 10 days using a weighted 30-day window. We describe a newly developed method to derive the two types of albedo, which are directional hemispherical reflectance (DHR) and bi-hemispherical reflectance (BHR), directly from three tower-measured variables of shortwave radiation: downwelling, upwelling and diffuse shortwave radiation. In the validation process, the MISR, MODIS and CGLS-derived albedos (DHR and BHR) are first compared with tower measured albedos, using pixel-to-point analysis, between 2012 to 2016. The tower measured point albedos are then upscaled to coarse-resolution albedos, based on atmospherically corrected BRFs from high-resolution Earth observation (HR-EO) data, alongside MODIS BRDF climatology from a larger area. Then a pixel-to-pixel comparison is performed between DHR and BHR retrieved from coarse-resolution satellite observations and DHR and BHR upscaled from accurate tower measurements. The experimental results are presented on exploring the parameter space associated with land cover type, heterogeneous vs. homogeneous and instantaneous vs. time composite retrievals of surface albedo

An Automatic Relevance Feedback in Image Retrieval Using Belief Functions

International audienceThis paper proposes an automatic relevance feedback approach for content-based image retrieval using information fusion and without any user input. This method is proposed as an alternative of the simple ranking of result images. The idea consists to pass from a simple user selected query image to multi-images query in order to get more information about the query image type. Given a query image, the system first computes its feature vector to rank the images according to a well-chosen similarity measure. For each retrieved image, the degree of belief about the relevance is then assigned as a function of this measure. This degree of belief is then updated using an iterative process. At each iteration, we evaluate, for each retrieved image, the degree of relevance using the combination of belief functions associated to previously retrieved images. Then, each retrieved image is not found by the query image only but it is found by the query image and previously retrieved images too. Some experimental results will be proposed in this paper in order to demonstrate that the methodology improves the efficiency and accuracy of retrieval systems

Histogrammes spatiaux couleur optimisés pour l'indexation d'images par le contenu

International audienceDans cet article, nous présentons une méthode qui augmente l'efficacité et la précision des systèmes d'indexation et de recherche d'images couleur par le contenu basés sur les histogrammes spatiaux. Cette technique consiste essentiellement à extraire les informations spatiales de l'image en la divisant en plusieurs sous-images rectangulaires interférées (grille des histogrammes). La méthodologie proposée optimise, via une combinaison linéaire, le découpage horizontal et vertical de l'image pour le calcul des histogrammes spatiaux. Nous augmentons ainsi la performance de la recherche en réduisant en même temps le coût de stockage et le temps de calcul par rapport aux méthodes classiques dont le choix concernant le découpage reste arbitraire

In-situ and aircraft reflectance measurement effectiveness for CAL/VAL Activities: A study over Railroad Valley

This paper aims to assess the relationship between the surface reflectance derived from ground based and aircraft measurements. The parameters of the Rahman–Pinty–Verstraete (RPV) and Ross Thick-LiSparse (RTLS) kernel based bi-directional reflectance distribution functions (BRDF), have been derived using actual measurements of the hemispherical-directional reflectance factor (HDRF), collected during different campaigns over the Railroad Valley Playa. The effect of the atmosphere, including that of the diffuse radiation on bi-directional reflectance factor (BRF) parameter retrievals, assessed using 6S model simulations, was negligible for the low turbidity conditions of the site under investigation (t550 < 0.05). It was also shown that the effects of the diffuse radiation on RPV spectral parameters retrieval is linear for the isotropic parameter r0 and the scattering parameter Q, and can be described with a second order polynomial for the k-Minnaert parameter. In order to overcome the lack of temporal collocations between aircraft and in-situ measurements, Monte Carlo 3-D radiative transfer simulations mimicking in-situ and remote sensing techniques were performed on a synthetic parametric meshed scene defined by merging Landsat and Multiangle Imaging Spectroradiometer (MISR) remote sensing reflectance data. We simulated directional reflectance measurements made at different heights for PARABOLA and CAR, and analyzed them according to practices adopted for real measurements, consisting of the inversion of BRF functions and the calculation of the bi-hemispherical reflectance (BHR). The difference of retrievals against the known benchmarks of kernel parameters and BHR is presented. We associated an uncertainty of up to 2% with the retrieval of area averaged BHR, independently of flight altitudes and the BRF model used for the inversion. As expected, the local nature of PARABOLA data is revealed by the difference of the anisotropic kernel parameters with the corresponding parameters retrieved from aircraft loops. The uncertainty of the resultant BHR fell within +/-3%.JRC.D.6-Knowledge for Sustainable Development and Food Securit