BRDFs acquired by directional radiative measurements during EAGLE and AGRISAR

Radiation is the driving force for all processes and interactions between earth surface and atmosphere. The amount of measured radiation reflected by vegetation depends on its structure, the viewing angle and the solar angle. This angular dependence is usually expressed in the Bi-directional Reflectance Distribution Function (BRDF). This BRDF is not only different for different types of vegetation, but also different for different stages of the growth. The BRDF therefore has to be measured at ground level before any satellite imagery can be used the calculate surface-atmosphere interaction. The objective of this research is to acquire the BRDFs for agricultural crop types. A goniometric system is used to acquire the BRDFs. This is a mechanical device capable of a complete hemispherical rotation. The radiative directional measurements are performed with different sensors that can be attached to this system. The BRDFs are calculated from the measured radiation. In the periods 10 June - 18 June 2006 and 2 July - 10 July 2006 directional radiative measurements were performed at three sites: Speulderbos site, in the Netherlands, the Cabauw site, in the Netherlands, and an agricultural test site in Goermin, Germany. The measurements were performed over eight different crops: forest, grass, pine tree, corn, wheat, sugar beat and barley. The sensors covered the spectrum from the optical to the thermal domain. The measured radiance is used to calculate the BRDFs or directional thermal signature. This contribution describes the measurements and calculation of the BRDFs of forest, grassland, young corn, mature corn, wheat, sugar beat and barley during the EAGLE2006 and AGRISAR 2006 fieldcampaigns. Optical BRDF have been acquired for all crops except barley. Thermal angular signatures are acquired for all the crop

A parameterisation of vertical profile of solar irradiance for correcting solar fluxes for changes in terrain elevation

International audienceThis paper deals with the modelling of vertical profile of solar irradiance for correcting solar radiation data. An approximation of the influence of the terrain elevation on all-skies radiation and a parameterisation of vertical profile on clear-skies radiation are proposed. This parameterisation, called double-z fitting function, is validated using two radiative transfer models. The main applications of this work are: computing clear-sky irradiances from satellite images, extrapolation of irradiances from one site to another of different altitude and correction of databases derived from satellite images

Discrete anisotropic radiative transfer (DART 5) for modeling airborne and satellite spectroradiometer and LIDAR acquisitions of natural and urban landscapes

International audienceSatellite and airborne optical sensors are increasingly used by scientists, and policy makers, and managers for studying and managing forests, agriculture crops, and urban areas. Their data acquired with given instrumental specifications (spectral resolution, viewing direction, sensor field-of-view, etc.) and for a specific experimental configuration (surface and atmosphere conditions, sun direction, etc.) are commonly translated into qualitative and quantitative Earth surface parameters. However, atmosphere properties and Earth surface 3D architecture often confound their interpretation. Radiative transfer models capable of simulating the Earth and atmosphere complexity are, therefore, ideal tools for linking remotely sensed data to the surface parameters. Still, many existing models are oversimplifying the Earth-atmosphere system interactions and their parameterization of sensor specifications is often neglected or poorly considered. The Discrete Anisotropic Radiative Transfer (DART) model is one of the most comprehensive physically based 3D models simulating the Earth-atmosphere radiation interaction from visible to thermal infrared wavelengths. It has been developed since 1992. It models optical signals at the entrance of imaging radiometers and laser scanners on board of satellites and airplanes, as well as the 3D radiative budget, of urban and natural landscapes for any experimental configuration and instrumental specification. It is freely distributed for research and teaching activities. This paper presents DART physical bases and its latest functionality for simulating imaging spectroscopy of natural and urban landscapes with atmosphere, including the perspective projection of airborne acquisitions and LIght Detection And Ranging (LIDAR) waveform and photon counting signals

Modélisation 3D du transfert raidatif pour simuler les images et données de spectroradiomètres et Lidars satellites et aéroportés de couverts végétaux et urbains

Les mesures de télédétection (MT) dépendent de l'interaction du rayonnement avec les paysages terrestres et l'atmosphère ainsi que des configurations instrumentales (bande spectrale, résolution spatiale, champ de vue: FOV,...) et expérimentales (structure et propriétés optiques du paysage et atmosphère,...). L'évolution rapide des techniques de télédétection requiert des outils appropriés pour valider leurs principes et améliorer l'emploi des MT. Les modèles de transfert radiatif (RTM) simulent des quantités (fonctions de distribution de la réflectance (BRDF) et température (BTDF), forme d'onde LiDAR, etc.) plus ou moins proches des MT. Ils constituent l'outil de référence pour simuler les MT, pour diverses applications : préparation et validation des systèmes d'observation, inversion de MT,... DART (Discrete Anisotropic Radiative Transfer) est reconnu comme le RTM le plus complet et efficace. J'ai encore nettement amélioré son réalisme via les travaux de modélisation indiqués ci-dessous. 1. Discrétisation de l'espace des directions de propagation des rayons. DART simule la propagation des rayons dans les paysages terrestres et l'atmosphère selon des directions discrètes. Les méthodes classiques définissent mal le centroïde et forme des angles solides de ces directions, si bien que le principe de conservation de l'énergie n'est pas vérifié et que l'obtention de résultats précis exige un grand nombre de directions. Pour résoudre ce problème, j'ai conçu une méthode originale qui crée des directions discrètes de formes définies. 2. Simulation d'images de spectroradiomètre avec FOV fini (caméra, pushbroom,...). Les RTMs sont de type "pixel" ou "image". Un modèle "pixel" calcule une quantité unique (BRDF, BTDF) de toute la scène simulée via sa description globale (indice foliaire, fraction d'ombre,...). Un modèle "image" donne une distribution spatiale de quantités (BRDF,...) par projection orthographique des rayons sur un plan image. Tous les RTMs supposent une acquisition monodirectionnelle (FOV nul), ce qui peut être très imprécis. Pour pouvoir simuler des capteurs à FOV fini (caméra, pushbroom,...), j'ai conçu un modèle original de suivi de rayons convergents avec projection perspective. 3. Simulation de données LiDAR. Beaucoup de RTMs simulent le signal LiDAR de manière rapide mais imprécise (paysage très simplifié, pas de diffusions multiples,...) ou de manière précis mais avec de très grands temps de calcul (e.g., modèles Monte-Carlo: MC). DART emploie une méthode "quasi-MC" originale, à la fois précise et rapide, adaptée à toute configuration instrumentale (altitude de la plateforme, attitude du LiDAR, taille de l'empreinte,...). Les acquisitions multi-impulsions LiDAR (satellite, avion, terrestre) sont simulées pour toute configuration (position du LiDAR, trajectoire de la plateforme,...). Elles sont converties dans un format industriel pour être traitées par des logiciels dédiés. Un post-traitement convertit les formes d'onde LiDAR simulées en données LiDAR de comptage de photons. 4. Bruit solaire et fusion de données LiDAR et d'images de spectroradiomètre. DART peut combiner des simulations de LiDAR multi-impulsions et d'image de spectro-radiomètre (capteur hyperspectral,...). C'est une configuration à 2 sources (soleil, laser LiDAR) et 1 capteur (télescope du LiDAR). Les régions mesurées par le LiDAR, dans le plan image du sol, sont segmentées dans l'image du spectro-radiomètre, elle aussi projetée sur le plan image du sol. Deux applications sont présentées : bruit solaire dans le signal LiDAR, et fusion de données LiDAR et d'images de spectro-radiomètre. Des configurations d'acquisition (trajectoire de plateforme, angle de vue par pixel du spectro-radiomètre et par impulsion LiDAR) peuvent être importées pour encore améliorer le réalisme des MT simulées, De plus, j'ai introduit la parallélisation multi-thread, ce qui accélère beaucoup les calculsRemote Sensing (RS) data depend on radiation interaction in Earth landscapes and atmosphere, and also on instrumental (spectral band, spatial resolution, field of view (FOV),...) and experimental (landscape/atmosphere architecture and optical properties,...) conditions. Fast developments in RS techniques require appropriate tools for validating their working principles and improving RS operational use. Radiative Transfer Models (RTM) simulate quantities (bidirectional reflectance; BRDF, directional brightness temperature: BTDF, LiDAR waveform...) that aim to approximate actual RS data. Hence, they are celebrated tools to simulate RS data for many applications: preparation and validation of RS systems, inversion of RS data... Discrete Anisotropic Radiative Transfer (DART) model is recognized as the most complete and efficient RTM. During my PhD work, I further improved its modeling in terms of accuracy and functionalities through the modeling work mentioned below. 1. Discretizing the space of radiation propagation directions.DART simulates radiation propagation along a finite number of directions in Earth/atmosphere scenes. Classical methods do not define accurately the solid angle centroids and geometric shapes of these directions, which results in non-conservative energy or imprecise modeling if few directions are used. I solved this problem by developing a novel method that creates discrete directions with well-defined shapes. 2. Simulating images of spectroradiometers with finite FOV.Existing RTMs are pixel- or image-level models. Pixel-level models use abstract landscape (scene) description (leaf area index, overall fraction of shadows,...) to calculate quantities (BRDF, BTDF,...) for the whole scene. Image-level models generate scene radiance, BRDF or BTDF images, with orthographic projection of rays that exit the scene onto an image plane. All models neglect the multi-directional acquisition in the sensor finite FOV, which is unrealistic. Hence, I implemented a sensor-level model, called converging tracking and perspective projection (CTPP), to simulate camera and cross-track sensor images, by coupling DART with classical perspective and parallel-perspective projection. 3. Simulating LiDAR data.Many RTMs simulate LiDAR waveform, but results are inaccurate (abstract scene description, account of first-order scattering only...) or require tremendous computation time for obtaining accurate results (e.g., Monte-Carlo (MC) models). With a novel quasi-MC method, DART can provide accurate results with fast processing speed, for any instrumental configuration (platform altitude, LiDAR orientation, footprint size...). It simulates satellite, airborne and terrestrial multi-pulse laser data for realistic configurations (LiDAR position, platform trajectory, scan angle range...). These data can be converted into industrial LiDAR format for being processed by LiDAR processing software. A post-processing method converts LiDAR waveform into photon counting LiDAR data, through modeling single photon detector acquisition. 4. In-flight Fusion of LiDAR and imaging spectroscopy.DART can combine multi-pulse LiDAR and cross-track imaging spectroscopy (hyperspectral sensor...). It is a 2 sources (sun, LiDAR laser) and 1 sensor (LiDAR telescope) system. First, a LiDAR multi-pulse acquisition and a sun-induced spectro-radiometer radiance image are simulated. Then, the LiDAR FOV regions projected onto the ground image plane are segmented in the spectro-radiometer image, which is also projected on the ground image plane. I applied it to simulate solar noise in LiDAR signal, and to the fusion of LiDAR data and spectro-radiometer images. To further improve accuracy when simulating actual LiDAR and spectro-radiometer, DART can also import actual acquisition configuration (platform trajectory, view angle per spectro-radiometer pixel / LiDAR pulse). Moreover, I introduced multi-thread parallelization, which greatly accelerates DART simulation

Three dimensional estimation of vegetation moisture content using dual-wavelength terrestrial laser scanning

PhD ThesisLeaf Equivalent Water Thickness (EWT) is a water status metric widely used in vegetation health monitoring. Optical Remote Sensing (RS) data, spaceborne and airborne, can be used to estimate canopy EWT at landscape level, but cannot provide information about EWT vertical heterogeneity, or estimate EWT predawn. Dual-wavelength Terrestrial Laser Scanning (TLS) can overcome these limitations, as TLS intensity data, following radiometric corrections, can be used to estimate EWT in three dimensions (3D). In this study, a Normalized Difference Index (NDI) of 808 nm wavelength, utilized in the Leica P20 TLS instrument, and 1550 nm wavelength, employed in the Leica P40 and P50 TLS systems, was used to produce 3D EWT estimates at canopy level. Intensity correction models were developed, and NDI was found to be able to minimize the incidence angle and leaf internal structure effects. Multiple data collection campaigns were carried out. An indoors dry-down experiment revealed a strong correlation between NDI and EWT at leaf level. At canopy level, 3D EWT estimates were generated with a relative error of 3 %. The method was transferred to a mixed-species broadleaf forest plot and 3D EWT estimates were generated with relative errors < 7 % across four different species. Next, EWT was estimated in six short-rotation willow plots during leaf senescence with relative errors < 8 %. Furthermore, a broadleaf mixed-species urban tree plot was scanned during and two months after a heatwave, and EWT temporal changes were successfully detected. Relative error in EWT estimates was 6 % across four tree species. The last step in this research was to study the effects of EWT vertical heterogeneity on forest plot reflectance. Two virtual forest plots were reconstructed in the Discrete Anisotropic Radiative Transfer (DART) model. 3D EWT estimates from TLS were utilized in the model and Sentinel-2A bands were simulated. The simulations revealed that the top four to five metres of canopy dominated the plot reflectance. The satellite sensor was not able to detect severe water stress that started in the lower canopy layers. This study showed the potential of using dual-wavelength TLS to provide important insights into the EWT distribution within the canopy, by mapping the EWT at canopy level in 3D. EWT was found to vary vertically within the canopy, with EWT and Leaf Mass per Area (LMA) being highly correlated, suggesting that sun leaves were able to hold more moisture than shade leaves. The EWT vertical profiles varied between species, and trees reacted in different ways during drought conditions, losing moisture from different canopy layers. The proposed method can provide time series of the change in EWT at very high spatial and temporal resolutions, as TLS instruments are active sensors, independent of the solar illumination. It also has the potential to provide EWT estimates at the landscape level, if coupled with automatic tree ii segmentation and leaf-wood separation techniques, and thus filling the gaps in the time series produced from satellite data. In addition, the technique can potentially allow the characterisation of whole-tree leaf water status and total water content, by combining the EWT estimates with Leaf Area Index (LAI) measurements, providing new insights into forest health and tree physiology.Egyptian Ministry of Higher Educatio

Sensibilité des observables radars à la variabilité temporelle et à la configuration géométrique de forêts tempérées et tropicales à partir de mesure de proximité haute-résolution

L'augmentation importante de la population mondiale, et par conséquent de ses besoins, exerce une pression de plus en plus importante sur les surfaces forestières. L'outil le mieux adapté au suivi des forêts, à l'échelle du globe, est la télédétection. C'est dans ce contexte que se situe ce travail de thèse, qui vise à améliorer l'estimation des paramètres biophysiques des arbres à partir de données de télédétection. L'originalité de ce travail a été d'étudier cette estimation des paramètres biophysiques en menant plusieurs études de sensibilité avec une démarche expérimentale sur des données expérimentales et sur des données simulées. Tout d'abord, l'étude s'est portée sur des séries temporelles de mesures de diffusiométrie radar obtenues sur deux sites : l'un constitué d'un cèdre en zone tempérée et l'autre d'une parcelle de forêt tropicale. Puis, cette étude de sensibilité a été poursuivie en imageant, avec une résolution élevée, plusieurs parcelles aux configurations différentes à l'intérieur d'une forêt de pin. Enfin, des données optiques et radars simulées ont été fusionnés afin d'évaluer l'apport de la fusion de données optique et radar dans l'inversion des paramètres biophysiques.The significant increase of the world population, and therefore its needs, pushes increasingly high in forest areas. The best tool for monitoring forest across the globe is remote sensing. It is in this context that this thesis, which aims to improve the retrieval of biophysical parameters of trees from remote sensing data, takes place. The originality of this work was to study the estimation of biophysical parameters across multiple sensitivity studies on experimental data and simulated data. First, the study focused on the time series of radar scatterometry measurements obtained on two sites: one characterized by a cedar in the temperate zone and the other by a forest plot of rainforest. Then, the sensitivity analysis was continued by imaging with high resolution, several forest plots with different configurations within a pine forest. Finally, simulated radar and optical data were combined to evaluate the contribution of optical and radar data fusion in the inversion of biophysical parameters.RENNES1-Bibl. électronique (352382106) / SudocSudocFranceF