EFFECT OF SALINITY ON THE DIELECTRIC PROPERTIES OF GEOLOGICAL MATERIALS : IMPLICATION FOR SOIL MOISTURE DETECTION BY MEANS OF REMOTE SENSING

International audienceThis paper deals with the exploitation of dielectric properties of saline deposits for the detection and mapping of moisture in arid regions on both Earth and Mars. We then present a simulation and experimental study in order to assess the effect of salinity on the permittivity of geological materials and therefore on the radar backscattering coefficient in the [1-7GHz] frequency range. Dielectric mixing models were first calibrated by means of experimental measurements before being used as input parameters of analytical scattering models (IEM, SPM). Simulation results will finally be compared to field measurements (Pyla dune, Death Valley, Mojave Desert) and will be used for the interpretation of SAR data (AIRSAR, PALSAR)

Remote sensing backscattering model for sea ice: Theoretical modelling and analysis

Remote sensing has been used in Antarctic studies as an earth observation technique to study the polar region. A remote sensing forward model is an important tool in polar research to study and understand scattering mechanisms and sensitivity of physical parameters of snow and sea ice. In this paper, a reliable theoretical model to study sea ice is developed. The theoretical model in a prior work was improved by including multiple-surface scattering, based on an existing integral equation model and additional second-order surface-volume scattering. This model is applied to a desalinated ice layer above thick saline ice and analyzed using different frequencies, bottom surface roughness and sea-ice layer thickness. Improvement in calculation of the backscattering coefficient of the sea-ice layer is investigated for both co-polarized and cross-polarized returns. The effect on each scattering mechanism is also investigated, to understand in more detail the effect of surface multiple scattering and second-order surface-volume scattering. Comparisons are also made with field measurement results, to validate the theoretical model. Results show improvement in the total backscattering coefficient for cross-polarized return in the studied range, suggesting that multiple-surface scattering and surface-volume scattering up to second order are important scattering mechanisms in the sea-ice layer and should not be ignored in polar research

Quantitative Estimation of Surface Soil Moisture in Agricultural Landscapes using Spaceborne Synthetic Aperture Radar Imaging at Different Frequencies and Polarizations

Soil moisture and its distribution in space and time plays an important role in the surface energy balance at the soil-atmosphere interface. It is a key variable influencing the partitioning of solar energy into latent and sensible heat flux as well as the partitioning of precipitation into runoff and percolation. Due to their large spatial variability, estimation of spatial patterns of soil moisture from field measurements is difficult and not feasible for large scale analyses. In the past decades, Synthetic Aperture Radar (SAR) remote sensing has proven its potential to quantitatively estimate near surface soil moisture at high spatial resolutions. Since the knowledge of the basic SAR concepts is important to understand the impact of different natural terrain features on the quantitative estimation of soil moisture and other surface parameters, the fundamental principles of synthetic aperture radar imaging are discussed. Also the two spaceborne SAR missions whose data was used in this study, the ENVISAT of the European Space Agency (ESA) and the ALOS of the Japanese Aerospace Exploration Agency (JAXA), are introduced. Subsequently, the two essential surface properties in the field of radar remote sensing, surface soil moisture and surface roughness are defined, and the established methods of their measurement are described. The in situ data used in this study, as well as the research area, the River Rur catchment, with the individual test sites where the data was collected between 2007 and 2010, are specified. On this basis, the important scattering theories in radar polarimetry are discussed and their application is demonstrated using novel polarimetric ALOS/PALSAR data. A critical review of different classical approaches to invert soil moisture from SAR imaging is provided. Five prevalent models have been chosen with the aim to provide an overview of the evolution of ideas and techniques in the field of soil moisture estimation from active microwave data. As the core of this work, a new semi-empirical model for the inversion of surface soil moisture from dual polarimetric L-band SAR data is introduced. This novel approach utilizes advanced polarimetric decomposition techniques to correct for the disturbing effects from surface roughness and vegetation on the soil moisture retrieval without the use of a priori knowledge. The land use specific algorithms for bare soil, grassland, sugar beet, and winter wheat allow quantitative estimations with accuracies in the order of 4 Vol.-%. Application of remotely sensed soil moisture patterns is demonstrated on the basis of mesoscale SAR data by investigating the variability of soil moisture patterns at different spatial scales ranging from field scale to catchment scale. The results show that the variability of surface soil moisture decreases with increasing wetness states at all scales. Finally, the conclusions from this dissertational research are summarized and future perspectives on how to extend the proposed model by means of improved ground based measurements and upcoming advances in sensor technology are discussed. The results obtained in this thesis lead to the conclusion that state-of-the-art spaceborne dual polarimetric L-band SAR systems are not only suitable to accurately retrieve surface soil moisture contents of bare as well as of vegetated agricultural fields and grassland, but for the first time also allow investigating within-field spatial heterogeneities from space

GNSS reflectometry for land remote sensing applications

Soil moisture and vegetation biomass are two essential parameters from a scienti c and economical point of view. On one hand, they are key for the understanding of the hydrological and carbon cycle. On the other hand, soil moisture is essential for agricultural applications and water management, and vegetation biomass is crucial for regional development programs. Several remote sensing techniques have been used to measure these two parameters. However, retrieving soil moisture and vegetation biomass with the required accuracy, and the appropriate spatial and temporal resolutions still remains a major challenge. The use of Global Navigation Satellite Systems (GNSS) reflected signals as sources of opportunity for measuring soil moisture and vegetation biomass is assessed in this PhD Thesis. This technique, commonly known as GNSS-Reflectometry (GNSS-R), has gained increasing interest among the scienti c community during the last two decades due to its unique characteristics. Previous experimental works have already shown the capabilities of GNSS-R to sense small reflectivity changes on the surface. The use of the co- and cross-polarized reflected signals was also proposed to mitigate nuisance parameters, such as soil surface roughness, in the determination of soil moisture. However, experimental evidence of the suitability of that technique could not be demonstrated. This work analyses from a theoretical and an experimental point of view the capabilities of polarimetric observations of GNSS reflected signals for monitoring soil moisture and vegetation biomass. The Thesis is structured in four main parts. The fi rst part examines the fundamental aspects of the technique and provides a detailed review of the GNSS-R state of the art for soil moisture and vegetation monitoring. The second part deals with the scattering models from land surfaces. A comprehensive description of the formation of scattered signals from rough surfaces is provided. Simulations with current state of the art models for bare and vegetated soils were performed in order to analyze the scattering components of GNSS reflected signals. A simpli ed scattering model was also developed in order to relate in a straightforward way experimental measurements to soil bio-geophysical parameters. The third part reviews the experimental work performed within this research. The development of a GNSS-R instrument for land applications is described, together with the three experimental campaigns carried out in the frame of this PhD Thesis. The analysis of the GNSS-R and ground truth data is also discussed within this part. As predicted by models, it was observed that GNSS scattered signals from natural surfaces are a combination of a coherent and an incoherent scattering components. A data analysis technique was proposed to separate both scattering contributions. The use of polarimetric observations for the determination of soil moisture was demonstrated to be useful under most soil conditions. It was also observed that forests with high levels of biomass could be observed with GNSS reflected signals. The fourth and last part of the Thesis provides an analysis of the technology perspectives. A GNSS-R End-to-End simulator was used to determine the capabilities of the technique to observe di erent soil reflectivity conditions from a low Earth orbiting satellite. It was determined that high accuracy in the estimation of reflectivity could be achieved within reasonable on-ground resolution, as the coherent scattering component is expected to be the predominant one in a spaceborne scenario. The results obtained in this PhD Thesis show the promising potential of GNSS-R measurements for land remote sensing applications, which could represent an excellent complementary observation for a wide range of Earth Observation missions such as SMOS, SMAP, and the recently approved ESA Earth Explorer Mission Biomass.La humedad del suelo y la biomasa de la vegetaci on son dos parametros clave desde un punto de vista tanto cient co como econ omico. Por una parte son esenciales para el estudio del ciclo del agua y del carbono. Por otra parte, la humedad del suelo es esencial para la gesti on de las cosechas y los recursos h dricos, mientras que la biomasa es un par ametro fundamental para ciertos programas de desarrollo. Varias formas de teledetección se han utilizado para la observaci on remota de estos par ametros, sin embargo, su monitorizaci on con la precisi on y resoluci on necesarias es todav a un importante reto tecnol ogico. Esta Tesis evalua la capacidad de medir humedad del suelo y biomasa de la vegetaci on con señales de Sistemas Satelitales de Posicionamiento Global (GNSS, en sus siglas en ingl es) reflejadas sobre la Tierra. La t ecnica se conoce como Reflectometr í a GNSS (GNSS-R), la cual ha ganado un creciente inter es dentro de la comunidad científ ca durante las dos ultimas d ecadas. Experimentos previos a este trabajo ya demostraron la capacidad de observar cambios en la reflectividad del terreno con GNSS-R. El uso de la componente copolar y contrapolar de la señal reflejada fue propuesto para independizar la medida de humedad del suelo de otros par ametros como la rugosidad del terreno. Sin embargo, no se pudo demostrar una evidencia experimental de la viabilidad de la t ecnica. En este trabajo se analiza desde un punto de vista te orico y experimental el uso de la informaci on polarim etrica de la señales GNSS reflejadas sobre el suelo para la determinaci on de humedad y biomasa de la vegetaci on. La Tesis se estructura en cuatro partes principales. En la primera parte se eval uan los aspectos fundamentales de la t ecnica y se da una revisi on detallada del estado del arte para la observaci on de humedad y vegetaci on. En la segunda parte se discuten los modelos de dispersi on electromagn etica sobre el suelo. Simulaciones con estos modelos fueron realizadas para analizar las componentes coherente e incoherente de la dispersi on de la señal reflejada sobre distintos tipos de terreno. Durante este trabajo se desarroll o un modelo de reflexi on simpli cado para poder relacionar de forma directa las observaciones con los par ametros geof sicos del suelo. La tercera parte describe las campañas experimentales realizadas durante este trabajo y discute el an alisis y la comparaci on de los datos GNSS-R con las mediciones in-situ. Como se predice por los modelos, se comprob o experimentalmente que la señal reflejada est a formada por una componente coherente y otra incoherente. Una t ecnica de an alisis de datos se propuso para la separacióon de estas dos contribuciones. Con los datos de las campañas experimentales se demonstr o el bene cio del uso de la informaci on polarim etrica en las señales GNSS reflejadas para la medici on de humedad del suelo, para la mayor a de las condiciones de rugosidad observadas. Tambi en se demostr o la capacidad de este tipo de observaciones para medir zonas boscosas densamente pobladas. La cuarta parte de la tesis analiza la capacidad de la t ecnica para observar cambios en la reflectividad del suelo desde un sat elite en orbita baja. Los resultados obtenidos muestran que la reflectividad del terreno podr a medirse con gran precisi on ya que la componente coherente del scattering ser a la predominante en ese tipo de escenarios. En este trabajo de doctorado se muestran la potencialidades de la t ecnica GNSS-R para observar remotamente par ametros del suelo tan importantes como la humedad del suelo y la biomasa de la vegetaci on. Este tipo de medidas pueden complementar un amplio rango de misiones de observaci on de la Tierra como SMOS, SMAP, y Biomass, esta ultima recientemente aprobada para la siguiente misi on Earth Explorer de la ESA

Developing Parameter Constraints for Radar-based SWE Retrievals

Terrestrial snow is an important freshwater reservoir with significant influence on the climate and energy balance. It exhibits natural spatiotemporal variability which has been enhanced by climate change, thus it is important to monitor on a large scale. Active microwave, or radar remote sensing has shown frequency-dependent promise in this regard, however, interpretation remains a challenge. The aim of this thesis was to develop constraints for radar based SWE retrievals which characterize and limit uncertainty with a focus on the underlying physical processes, snowpack stratigraphy, the influence of vegetation, and effects of background scattering. The University of Waterloo Scatterometer (UWScat) was used to make measurements at 9.6 and 17.2 GHz of snow and bare ground in a series of field-based campaigns in Maryhill and Englehart, ON, Grand Mesa, CO (NASA SnowEx campaign, year 1), and Trail Valley Creek, NT. Additional measurements from Tobermory, ON, and Churchill, MB (Canadian Snow and Ice Experiment) were included. The Microwave Emission Model for Layered Snowpacks, Version 3, adapted for backscattering (MEMLS3&a) was used to explore snowpack parameterization and SWE retrieval and the Freeman-Durden three component decomposition (FD3c) was used to leverage the polarimetric response. Physical processes in the snow accumulation environment demonstrated influence on regional snowpack parameterization and constraints in a SWE retrieval context with a single-layer snowpack parameterization for Maryhill, ON and a two-layer snowpack parameterization for Englehart, ON resulting in a retrieval RMSE of 21.9 mm SWE and 24.6 mm SWE, respectively. Use of in situ snow depths improved RMSE to 12.0 mm SWE and 10.9 mm SWE, while accounting for soil scattering effects further improved RMSE by up to 6.3 mm SWE. At sites with vegetation and ice lenses, RMSE improved from 60.4 mm SWE to 21.1 mm SWE when in situ snow depths were used. These results compare favorably with the common accuracy requirement of RMSE ≤ 30 mm and underscore the importance of understanding the driving physical processes in a snow accumulation environment and the utility of their regional manifestation in a SWE retrieval context. A relationship between wind slab thickness and the double-bounce component of the FD3c in a tundra snowpack was introduced for incidence angles ≥ 46° and wind slab thickness ≥ 19 cm. Estimates of wind slab thickness and SWE resulted in an RMSE of 6.0 cm and 5.5 mm, respectively. The increased double-bounce scattering was associated with path length increase within a growing wind slab layer. Signal attenuation in a sub-canopy SWE retrieval was also explored. The volume scattering component of the FD3c yielded similar performance to forest fraction in the retrieval with several distinct advantages including a real-time description of forest condition, accounting for canopy geometry without ancillary information, and providing coincident information on forest canopy in remote locations. Overall, this work demonstrated how physical processes can manifest regional outcomes, it quantified effects of natural inclusions and background scattering on SWE retrievals, it provided a means to constrain wind slab thickness in a tundra environment, and it improved characterization of coniferous forest in a sub-canopy SWE retrieval context. Future work should focus on identifying ice and vegetation conditions prior to SWE retrieval, testing the spatiotemporal validity of the methods developed herein, and finally, improving the integration of snowpack attenuation within retrieval efforts

Modeling microwave emission from snow covered soil

Il ciclo idrologico rappresenta l’insieme di tutti i fenomeni legati alla circolazione e alla conservazione dell’acqua sulla Terra. Il monitoraggio su scala globale dei fattori che concorrono a produrre e modificare tale ciclo (umidità del terreno, copertura vegetale, estensione e caratteristiche del manto nevoso) risulta di estrema importanza per lo studio del clima e dei cambiamenti globali. Inoltre, l’osservazione sistematica di queste grandezze è importante per prevedere condizioni di rischio da alluvioni, frane e valanghe come pure fare stime delle risorse idriche. In questo contesto Il telerilevamento da satellite gioca un ruolo fondamentale per le sue caratteristiche di osservazioni continuative di tutto globo terrestre. I sensori a microonde permettono poi di effettuare misure indipendentemente dall’illuminazione solare e anche in condizioni meteorologiche avverse. I processi idrologici, ed in particolare quelli della criosfera (la porzione di superficie terrestre in cui l’acqua è presente in forma solida), sono fra quelli che meglio si possono investigare analizzando la radiazione elettromagnetica emessa o diffusa. Mediante l’utilizzo di modelli elettromagnetici che permettono di simulare l’emissione e lo scattering da superfici naturali è possibile interpretare le misure elettromagnetiche ed effettuare l’estrazione di quelle grandezze che caratterizzano i suoli e la loro copertura. In questo lavoro di dottorato si è affrontato il problema della modellistica a microonde dei terreni coperti da neve, sia asciutta che umida. Dopo aver preso in considerazione i modelli analitici maggiormente utilizzati per simulare diffusione ed emissione a microonde dei suoli nudi e coperti da neve si è proceduto allo sviluppo e implementazione di due modelli di emissività. Il primo, basato sulla teoria delle fluttuazioni forti, è atto a descrivere il comportamento di un manto nevoso umido. Il secondo, basato sull’accoppiamento del modello di scattering superficiale AIEM (Advanced Integral Equation Method) con la teoria del trasferimento radiativo nei mezzi densi, è volto allo studio di uno strato di neve asciutta sovrastante un suolo rugoso. Tali modelli tengono conto degli effetti coerenti presenti nell’emissione del manto nevoso e non inclusi nella teoria del trasporto radiativo classico. Entrambi i codici sono stati validati con datasets numerici e sperimentali in parte derivati da archivi ed in parte ottenuti nel contesto di questo lavoro che ha previsto quindi anche una fase sperimentale. Quest’ultima è stata condotta con misure radiometriche multifrequenza su un’area di test situata sulle Alpi orientali. Le simulazioni ottenute con questi modelli e le conseguenti analisi hanno permesso di individuare la sensibilità della temperatura di brillanza ai parametri di interesse (spessore, equivalente in acqua e umidità del manto nevoso) in funzione di diverse configurazioni osservative (frequenza, polarizzazione ed angolo di incidenza). Questo ha consentito di migliorare la comprensione dei meccanismi di emissione dalle superfici innevate e di individuare le migliori condizioni osservative per un sistema di telerilevamento terrestre

衛星搭載型多偏波SARを用いた土壌水分分布評価手法の開発とALOS/PALSARへの適用

学位の種別: 論文博士審査委員会委員 : （主査）東京大学教授 小池 俊雄, 東京大学教授 田島 芳満, 東京大学教授 西村 拓, 東京大学准教授 平林 由希子, 東京大学准教授 沖 一雄, 東京大学准教授 竹内 渉University of Tokyo(東京大学

Assimilation d'observations de débit et d'humidité du sol dans un modèle hydrologique distribué, application au bassin versant de la rivière des anglais

Les techniques d’assimilation de données permettent non seulement d’améliorer les simulations et prévisions d’un modèle par l’intégration d’observations, mais permettent aussi de porter un diagnostique sur le modèle et les observations. Peu de publications se sont intéressées à l’assimilation d’observations à un modèle hydrologique distribué à base physique simulant autant les débits en rivière que l’humidité du sol. L’objectif de cette thèse est donc d’évaluer l’impact de l’assimilation d’observations de débit et d’humidité du sol sur les simulations du modèle hydrologique CATHY. Un filtre d’ensemble de Kalman a été utilisé afin d’assimiler des observations de débit à l’exutoire, débits en amont, humidité du sol à différentes profondeur (15 cm, 45 cm et 90 cm) mesurées à l’aide de sondes (stations hydrométéorologiques) ainsi que des observations d’humidité du sol en surface estimées à l’aide de la télédétection radar. Une méthodologie permettant d’estimer l’humidité du sol en surface pour des sols nus ou de faible végétation à l’aide d’images radar multipolarisations (ENVISAT-ASAR) et polarimétriques (RADARSAT-2) a été développée. Une analyse de l’impact de la végétation a également été effectuée. L’utilisation de données polarimétriques plutôt que multipolarisation a permis d’améliorer l’estimation de l’humidité du sol pour les champs de faible végétation. La recherche a également permis de conclure que l’assimilation d’observations de débit à l’exutoire améliore les simulations de débits en amont. Par contre, l’assimilation des observations de débit (exutoire ou en amont) détériore les simulations d’humidité du sol. L’assimilation des observations d’humidité du sol a mise en évidence la présence d’un biais entre le modèle et les observations. L’élimination de ce biais devra faire l’objet de futures recherches. L’assimilation des observations d’humidité du sol a tout de même permis de constater que l’assimilation d’observations provenant d’une seule station a un impact similaire sur les simulations d’humidité du sol que l’assimilation d’observations provenant de cinq stations. De plus, elle a mise en évidence l’importance de la fréquence d’assimilation. L’assimilation d’observations d’humidité du sol en surface (radar) à seulement deux moments sur la période de 90 jours a eu très peu d’impact sur les simulations. Enfin, l’assimilation d’observations d’humidité du sol en plus de celle de débit à l’exutoire améliore les simulations de débits (exutoire et en amont) sans détériorer les simulations d’humidité du sol

Apports des données radar à haute répétitivité et à haute résolution du capteur Sentinel-1 pour la caractérisation de l'état hydrique des surfaces agricoles dans les régions sud-méditerranéennes

Le suivi de l'irrigation est un enjeu important pour l'optimisation de l'irrigation. L'humidité superficielle (SSM) est une variable clé pour la gestion de l'irrigation. De plus, la détection précoce du stress hydrique peut contribuer à une utilisation optimale de l'eau agricole. Les données radar en bande C ont montré un grand potentiel pour le suivi des conditions hydriques du sol et de la végétation. Dans ce contexte, cette thèse a pour objectif général d'évaluer les potentialités des données radar bande C pour suivre le fonctionnement hydrique des céréales irriguées. Nos objectifs spécifiques sont : (1) développer une nouvelle approche pour l'inversion de la SSM en utilisant uniquement les données radar ; (2) proposer une méthodologie pour l'estimation des quantités et des dates d'irrigation à l'échelle de la parcelle sur la base de ces nouveaux produits de SSM ; (3) étudier les potentialités de la réponse radar bande C pour le suivi du fonctionnement physiologique et, in fine, la détection du stress hydrique. En préliminaire à l'inversion, les séries temporelles de données Sentinel-1, notamment le coefficient de rétrodiffusion (sigma^0), le rapport de polarisation (PR) et la cohérence interférométrique (rho) sont interprétées à l'aide de données expérimentales collectées sur des parcelles de blé irriguées au Maroc. Les résultats montrent que rho et PR sont fortement liés au développement de la végétation alors que la dynamique de sigma^0 suit les variations de SSM pendant les premiers stades de croissance du blé. En outre, les changements drastiques de la géométrie du couvert associés à la phase d'épiaison ont un fort impact sur sigma^0. Les résultats montrent que le modèle Water Cloud (WCM) est capable de reproduire le cycle saisonnier de Sentinel-1. Grâce à une configuration multicouche du modèle Karam, le 2ème cycle est attribué à la diffusion de volume au sein de la couche des épis. Dans un 2ème temps, une nouvelle approche basée sur l'inversion du WCM pour estimer la SSM a été proposée en utilisant uniquement les données radar Sentinel-1. Dans ce but, les descripteurs de la végétation : la biomasse aérienne (AGB) et le contenu en eau de la végétation ont été estimés à partir de rho et PR. Les meilleurs résultats d'inversion de SSM sont obtenus en utilisant la relation entre rho_VV et l'AGB (R = 0.82 et RMSE = 0.05 m3/m3). Les produits SSM sont assimilés dans la FAO-56 par une technique de filtrage particulaire pour estimer les dates et les quantités d'irrigation. Premièrement, des expériences jumelles sont conçues pour évaluer l'impact de certains paramètres de l'approche. La méthode est ensuite évaluée en utilisant des mesures in situ de SSM avec 3 temps de revisite différents (3, 6 et 12 jours). Enfin, les produits de SSM Sentinel-1 dérivés par l'approche rho_VV-AGB sont utilisés. L'utilisation de données in situ permet d'obtenir de bons résultats. Avec une observation tous les 6 jours, les quantités saisonnières sont inversés avec R > 0.98 et RMSE 0.98 and RMSE < 32 mm. Similarly, over the flood-irrigated fields, more than 70% of the events are correctly detected. Using the SSM products derived from Sentinel-1, the statistics are still acceptable. For the drip-irrigated fields, the 15-day cumulative amounts are estimated with R = 0.64 and RMSE = 28.7 mm; metrics close to those obtained using in situ data (R = 0.74 and RMSE = 24.8 mm). Finally, the last part is devoted to the preliminary analysis of in situ radar acquisition by the C-band antennas installed on a wheat field in Morocco. The analysis of the fully polarimetric acquisitions (sigma^0 and rho) with a time step of 15 min reveals the existence of a diurnal cycle of rho whose amplitude evolves with the development of the canopy. The drop in rho at dawn is concomitant with the increase in evapotranspiration. In contrast, the lowest coherence values at the end of the afternoon are rather related to wind peaks

Développement et validation de méthodologies pour le suivi des états de surface des sols agricoles nus par télédétection radar (bande X)

Le recours à la caractérisation des états hydrique, géométrique et physique de surface du sol est essentiel dans la gestion et la conservation des ressources naturelles dans les régions agricoles semi-aride. Dans ce contexte, les travaux de cette thèse visent à estimer la variabilité spatio-temporelle des paramètres de surfaces agricoles nues (humidité, rugosité et texture) moyennant des données radars multi-temporelles acquises en bande X à haute résolution spatiale. Une nouvelle description de l'état géométrique des sols est d'abord proposée à travers l'estimation d'un nouveau paramètre de rugosité, le paramètre Zg, estimé en fonction de trois paramètres statistiques de rugosité (écart type des hauteurs "s", longueur de corrélation "l" et la forme de la fonction de corrélation). Les simulations des signaux radar montrent une très forte corrélation avec ce paramètre de rugosité. L'apport du paramètre Zg est confirmé à travers une large base de données expérimentale et spatiale acquises sur différents sites en France. Le deuxième volet de cette thèse présente une analyse des sensibilités des signaux radars issus de capteurs (TerraSAR-X et COSMO-SkyMed), aux paramètres de surface (l'humidité et les trois paramètres de rugosité : s, Zs=s2/l et Zg). Une forte corrélation est observée entre les mesures radars acquises à différentes configurations (polarisations HH et VV, et à 26° et 36°d'incidences) et tous les paramètres du sol. Cette analyse est suivie par des comparaisons des coefficients de rétrodiffusion réels et simulés à partir des modèles physique et semi empirique couramment utilisés : Modèle d'équation intégrale " IEM " de Fung et al., 1992, Modèle de Dubois (Dubois et al., 1995) et le Modèle IEM empiriquement calibré par Baghdadi et al., 2011. Le dernier modèle a montré une forte cohérence avec les mesures radar. Dans le troisième volet, une méthode empirique de détection de changement est développée, en combinant les images radars TerraSAR-X avec des données d'humidités ponctuelles dérivées du réseau des 7 capteurs repartis sur la zone d'étude en continue, pour spatialiser l'état hydrique du sol. La performance de l'algorithme proposé, est évaluée et validée sur de nombreuses parcelles de référence. La spatialisation de la teneur en argile des sols est déduite à partir du calcul de la moyenne des cartes de l'état hydrique du sol (une erreur quadratique moyenne équivalent à 108 g/kg). Pour cartographier la rugosité des sols, des relations empiriques reliant le signal radar aux paramètres de rugosité (Ecart type des hauteurs et le paramètre Zg) étaient élaborées. En inversant les mesures radars, les cartes de rugosité qui en résultent, ont permis de distinguer différents états de surface des sols (labourés, dégradés ou en jachère). Dans le dernier volet, un modèle d'estimation du bilan hydrique des sols agricoles nus " MHYSAN " qui simule l'évaporation et l'état hydrique surfacique est développé. Cette dernière partie souligne le potentiel de calibrer un modèle hydrologique des sols en assimilant les produits d'humidité radars.The characterization of geometric, water and physical surface soil parameters for semi-arid regions is a key requirement for sustainable agricultural management and natural resources conservation. In this context, the current study aims to estimate the spatio-temporal variability of soil properties (soil moisture, roughness and texture) using multi-temporal X-band radar images acquired at high spatial resolution over bare agricultural site in Tunisia. In the first section of this work, a new roughness parameter was proposed; it was the Zg parameter which combines the three most commonly used soil parameters: root mean surface height "s", correlation length "l", and correlation function shape, into just one parameter. A strong correlation was observed between this new parameter and the radar backscattering simulations. The parameter Zg was validated using large database acquired at several agricultural sites in France. Secondly, the sensitivity of X-band TerraSAR-X and COSMO-SkyMed sensors to soil moisture and different roughness parameters (s, Zs=s2/l and Zg parameters) was analyzed. The radar measurements acquired at different configurations (HH and VV polarizations, incidence angles of 26° and 36°) were found to be highly sensitive to the various soil parameters of interest. After that, the performance of different physical and semi-empirical backscattering models (IEM, Baghdadi-calibrated IEM and Dubois models) is compared with SAR measurements. Considerable improvements in the IEM model performance were observed using the Baghdadi-calibrated version of this model. Thirdly, an empirical change detection approach was developed using TerraSAR-X data and ground auxiliary thetaprobe network measurements for the retrieval of surface soil moisture at a high spatial resolution. The accuracy of the soil moisture retrieval algorithm was determined, and validated successfully over numerous test fields. Maps of soil clay percentages at the studied site were derived from the mean of the seven soil moisture radar outputs (a root mean square error equal to 108 g/kg). To retrieve surface soil roughness, empirical expressions were established between backscattering TerraSAR-X coefficients data and the roughness parameters (s and Zg). By inversing radar signals, resulting surface roughness maps have revealed that is possible to use spatial roughness variability observations at plot scale to identify soil surface changes between multi-temporal images. Finally, a Bare Soil HYdrological balance Model "MHYSAN" was developed to estimate surface evaporation fluxes and soil moisture time series over our study site. The present section of this work highlighted the feasibility of calibrating our proposed MHYSAN model through the use of multi-temporal TerraSAR-X moisture products