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

Multipath Interferences in Ground-Based Radar Data: A Case Study

Multipath interference can occur in ground-based radar data acquired with systems with a large antenna beam width in elevation in an upward looking geometry, where the observation area and the radar are separated by a reflective surface. Radiation reflected at this surface forms a coherent overlay with the direct image of the observation area and appears as a fringe-like pattern in the data. This deteriorates the phase and intensity data and therefore can pose a considerable disadvantage to many ground-based radar measurement campaigns. This poses a problem for physical parameter retrieval from backscatter intensity and polarimetric data, absolute and relative calibration on corner reflectors, the generation of digital elevation models from interferograms and in the case of a variable reflective surface, differential interferometry. The main parameters controlling the interference pattern are the vertical distance between the radar antennas and the reflective surface, and the reflectivity of this surface. We used datasets acquired in two different locations under changing conditions as well as a model to constrain and fully understand the phenomenon. To avoid data deterioration in test sites prone to multipath interference, we tested a shielding of the antennas preventing the radar waves from illuminating the reflective surface. In our experiment, this strongly reduced but did not completely prevent the interference. We therefore recommend avoiding measurement geometries prone to multipath interferences

Hemiboreaalsete metsade kaardistamine interferomeetrilise tehisava-radari andmetelt

Väitekirja elektrooniline versioon ei sisalda publikatsioone.Käesolev doktoritöö uurib tehisavaradari (SAR) kasutusvõimalusi metsa kõrguse hindamiseks hemiboreaalsete metsade vööndis. Uurimistöö viidi läbi Tartu Üli¬kooli, Tartu Observatooriumi, Aalto Ülikooli, Euroopa Kosmoseagentuuri (ESA) kaugseire keskuse ESRIN ja Reach-U koostöös. Uurimistöös kasutatud satelliidi¬andmed on pärit Saksa Kosmosekeskuse (DLR) kõrglahutusega bistaatilise X-laineala tehisavaradari TanDEM-X satelliidipaarilt. Sagedasti uuenevad satelliidiandmed, nende globaalne katvus ja kõrge ruumi¬line lahutus võimaldavad tehisavaradari abil kaardistada metsi ning nendes toimu¬vaid muutusi suurtel maa-aladel. Radari abil on võimalik saada kõrge lahutusvõimega pilte, mis on tundlikud taimestikule, maapinna karedusele ja dielektrilistele omadustele. Sünkroonis lendava radaripaari samaaegselt tehtud pildid elimineerivad võimalikud ajalised muutused taimestikus ning tänu sellele on radariandmetest võimalik tuletada metsade vertikaalset struktuuri ja kõrgust. Uurimistöös käsitletakse tehisavaradari interferomeetrilise koherentsuse tund¬likkust metsa kõrguse suhtes ning analüüsitakse, millised keskkonna ja klimaati¬lised tingimused ning satelliidi orbiidiga seotud parameetrid mõjutavad radari¬piltidelt erinevate puuliikide kõrguse hindamise täpsust. Lisaks keskendub väitekiri interferomeetrilisele koherentsusele tuginevate mudelite analüüsi¬misele ning nende täpsuse hindamisele operatiivse metsa kõrguse kaardistamise raken-duseks. Vaatluse alla on võetud kolm testala, mis asuvad Soomaa rahvuspargis, Võrtsjärve idakaldal Rannus ja Peipsiveere looduskaitsealal ning katavad kokku 2291 hektarit metsa. 23 TanDEM-X satelliidipildi koherentsuspilte võrreldakse samadel testaladel aerolaserskaneerimise (LiDAR) abil mõõdetud puistute kõrgu¬sega, mis on omakorda jagatud kolme rühma (kuused, männid ja laia¬lehised segametsad). RVoG (Random Volume over Ground) taimekatte mudel ning sellest tule¬tatud lihtsamad pooleempiirilised mudelid sobituvad olemasolevate TanDEM-X koherentsuse ning LiDARi metsa puistute kõrgusandmetega hästi. Töö tule¬mused kinnitavad, et tulevikus on suurte ja erinevatest metsatüüpidest koosne¬vate metsade kõrguse kosmosest kaardistamisel otstarbekas kasutusele võtta esmalt just soovitatud lihtsamad ja universaalsemad mudelid.This thesis presents research in the field of radar remote sensing and contributes to the forest monitoring application development using space-borne synthetic aperture radar (SAR). Satellite data is particularly useful for large-scale forestry applications making high revisit monitoring of the state of forests worldwide possible. The sensitivity of SAR to the dielectric and geometrical properties of the targets, penetration capacity and coherent imaging properties make it a unique tool for mapping and monitoring forest biomes. SAR satellites are also capable of retrieving additional information about the structure of the forest, tree height and biomass estimates as an essential input for monitoring the changes in the carbon stocks. Interferometric SAR (InSAR) is an advanced SAR imaging technique that allows the retrieval of forest parameters while working in nearly all weather conditions, independently of daylight and cloud cover. This research concen¬trates on assessing the impact of different variables affecting hemiboreal forest height estimation from space-borne X-band interferometric SAR coherence data. In particular, the research analyses the changes in coherence dynamics related to seasonal conditions, tree species and imaging properties using a large collection of interferometric SAR images from different seasons over a four-year period. The study is carried out over three test sites in Estonia using the extensive multi-temporal dataset of 23 TanDEM-X images, covering 2291 hectares of forests to describe the relation between the interferometric SAR coherence mag¬nitude and forest parameters. The work demonstrates how the correlation of interferometric coherence and Airborne LiDAR Scanning (ALS)-derived forest height varies for pine and deciduous tree species, for summer (leaf-on) and winter (leaf-off) conditions and for flooded forest floor. A simple semi-empirical modelling approach is proposed as being suitable for wide area forest mapping with limited a priori information under a range of seasonal and environ¬¬mental conditions. A Random Volume over Ground (RVoG) model and three semi-empirical models are compared and validated against a large dataset of coherence magnitude and ALS-measured data over hemiboreal forests in Estonia. The results show that all proposed models perform well in describing the relationship between hemiboreal forest height and interferometric coherence, allowing in future to derive forest stand height with an accuracy suitable for a wide range of applications

Study of the speckle noise effects over the eigen decomposition of polarimetric SAR data: a review

This paper is focused on considering the effects of speckle noise on the eigen decomposition of the co- herency matrix. Based on a perturbation analysis of the matrix, it is possible to obtain an analytical expression for the mean value of the eigenvalues and the eigenvectors, as well as for the Entropy, the Anisotroopy and the dif- ferent a angles. The analytical expressions are compared against simulated polarimetric SAR data, demonstrating the correctness of the different expressions.Peer ReviewedPostprint (published version

GNSS-R as a source of opportunity for remote sensing of the cryosphere

This work evaluates the potential use of signals from the Global Navigation Satellite Systems (GNSS) that scatter off the Earth surface for the retrieval of geophysical information from the cryosphere. For this purpose, the present study is based on data collected with a dedicated reflectometry GNSS receiver during two field campaigns, which were focused on two types of characteristic surfaces of the cryosphere: thin sea ice covers and thick dry snow accumulations. During the first experiment, the complete process of formation, evolution and melting of sea ice was monitorized for more than seven months in a bay located in Greenland. This type of ice is typically characterized by its thickness, concentration and roughness. Different observables from GNSS reflections are analyzed to try to infer these properties. The ice thickness is linked to the free-board level, defined as the height of the sea ice surface. Accurate phase altimetry is achieved, showing good agreement with an Arctic tide model. In addition, the long term results of ellipsoidal height retrievals are consistent with the evolution of the ice surface temperature product given by MODIS, which is a key parameter in the rate of growth of sea ice. On the other hand, the presence of salinity in the sea ice modifies its dielectric properties, resulting in different amplitude and phase for the co- and cross-polar components of the complex Fresnel coefficients. The polarimetric measurements obtained show good agreement with visual inspections of ice concentration from an Arctic weather station. Finally, the shape of the reflected signals and its phase dispersion are tested as potential signatures of surface roughness. For comparison, ice charts of the experimental area are employed. In particular, maximums in roughness given by the GNSS observables coincide with fast ice events. Fast ice is defined as ice anchored to the coast, where the tidal movements contribute to the development of strange patterns, cracks, and fissures on its surface, thus consistent with the GNSS-R roughness retrievals. The second experiment took place on Antarctica, monitoring a pristine snow area which is well-known for the calibration of remote sensing instruments. Due to the relative stability of the snow layers, the data acquisition was limited to ten continuous days. Interferometric beats were found after a first analysis of the amplitude from the collected signals, which were consistent with a multipath model where the reflector lies below the surface level. Motivated by these results, a forward model is developed that reconstructs the complex received signal as a sum of a finite number of reflections, coming from different snow layers (a snow density profile obtained from in-situ measurements). The interferometric information is then retrieved from the spectral analysis applied to time series from both real and modeled signals (lag-holograms). We find that the frequency bands predicted by the model are in general consistent with the data and the lag-holograms show repeatability for different days. Then, we attempt a proper inversion of the collected data to determine the dominant layers of the dry snow profile that contribute to L-band reflections, which are related to significant gradients of snow density/permittivity.Aquest treball avalua el possible ús dels senyals dels sistemes mundials de navegació per satèl lit (GNSS) que es reflecteixen a la superfície terrestre, per a l’extracció de la informació geofísica de la criosfera. Amb aquest propòsit, el present estudi es basa en dades recollides amb un reflectòmetre GNSS durant dues campanyes experimentals, centrades en dos tipus de superfícies característiques de la criosfera: cobertes de gel marí i gruixudes acumulacions de neu seca. En el primer experiment, el procés complet de formació, evolució i fusió del gel marí va ser monitoritzat durant més de set mesos a una badia situada a Groenlàndia. Aquest tipus de gel es caracteritza típicament amb el seu gruix, concentració i rugositat. Diferents observables de les reflexions GNSS són analitzats per tractar de fer una estimació d’aquestes propietats. El gruix de gel està relacionat amb el nivell de francbord, que a la seva vegada està relacionat amb l’alçada de la superfície de gel marí. S’ha aconseguit altimetria de fase precisa, que mostra correlació amb un model de marea de l’Àrtic. A més, els resultats a llarg termini de l’alçada elipsoidal segueixen l’evolució de les mesures de temperatura de superfície de gel donades per MODIS. La temperatura és un paràmetre clau en el ritme de creixement del gel marí. Per altra banda, la presència de sal a aquest tipus de gel modifica les seves propietats dielèctriques, el que implica variacions d’amplitud i fase per als coeficients de Fresnel complexos amb polaritzacions oposades. Les mesures polarimètriques obtingudes mostren concordança amb els valors de concentració de gel obtinguts des d’una estació meteorològica propera. Finalment, la forma de la senyal reflectida i la dispersió de la seva fase s’evaluen com a potencials indicadors de la rugositat de superfície. Per a la seva comparació, es fan servir mapes del gel de la zona experimental. En concret, els valors màxims a la rugositat estimada a partir pels observables GNSS coincideixen amb el gel fixe, que es refereix a gel ancorat a la costa, on els moviments de les marees contribueixen al desenvolupament de patrons estranys, esquerdes i fissures en la seva superfície. El segon experiment es va dur a terme a l’Antàrtida, monitoritzant una àrea de neu pristina que és ben coneguda per al calibratge d’instruments de teledetecció. A causa de la relativa estabilitat de les capes de neu, l’adquisició de dades es va limitar a deu dies consecutius. Es van trobar pulsacions interferomètriques a partir d’un primer anàlisi de l’amplitud de les senyals recollides, les quals eren compatibles amb un model de propagació multicamí a on el reflector es troba per sota del nivell de superfície. Com a conseqüència d’aquests resultats, s’ha desenvolupat un model que reconstrueix el senyal complexe rebut com la suma d’un nombre finit de reflexions, procedents de diferents capes de neu (determinat per mesures locals). La informació interferomètrica es recupera després de l’anàlisi espectral aplicat a les sèries temporals tant de les senyals reals, com de les modelades (lag-hologrames). Trobem que les bandes de freqüències predites pel model són en general consistents amb les dades i que els lag-hologrames mostren repetibilitat per dies diferents. Posteriorment, es realitza un anàlisi de les dades recollides per determinar les capes dominants del perfil de neu seca que contribueixen a les reflexions en banda L, i que a la seva vegada, estan relacionades amb gradents significatius de densitat/permitivitat.Este trabajo evalúa el posible uso de las señales de los sistemas globales de navegación por satélite (GNSS) que se reflejan en la superficie terrestre para la extracción de información geofísica de la criosfera. Con este propósito, el presente estudio se basa en datos recogidos con un reflectómetro GNSS durante dos campañas experimentales, centradas en dos tipos de superficies características de la criosfera: capas de hielo marino y gruesas acumulaciones de nieve seca. Durante el primer experimento, el proceso completo de formación, evolución y fusión del hielo marino fue monitorizado durante más de siete meses en una bahía ubicada en Groenlandia. Este tipo de hielo se caracteriza típicamente por su grosor, concentración y rugosidad. Diferentes observables de las reflexiones GNSS son analizados para tratar de estimar dichas propiedades. El espesor de hielo está relacionado con el nivel de francobordo o borda libre, que a su vez está relacionado con la altura de la superficie de hielo marino. Se ha logrado altimetría de fase precisa, mostrando correlación con un modelo de marea del Ártico. Además, los resultados a largo plazo de la altura elipsoidal siguen la evolución de las mediciones de temperatura de superficie de hielo proporcionadas por MODIS. La temperatura es un parámetro clave en el ritmo de crecimiento del hielo marino. Por otro lado, la presencia de sal en este tipo de hielo modifica sus propiedades dieléctricas, lo que implica variaciones en las amplitudes y fases de los coeficientes complejos de Fresnel con polarizaciones opuestas. Los resultados polarimétricos concuerdan con los valores de concentración de hielo obtenidos mediante inspección visual desde una estación meteorológica cercana. Por último, la forma de la señal reflejada y la dispersión de su fase son evaluadas como potenciales indicadores de la rugosidad de superficie. Para su comparación, se emplean mapas del hielo de la zona experimental. En particular, valores máximos de rugosidad estimada por los observables GNSS coinciden con hielo fijo, que se refiere al hielo anclado a la costa, donde los movimientos de las mareas contribuyen al desarrollo de patrones extraños, grietas y fisuras en su superficie. El segundo experimento se llevó a cabo en la Antártida, monitorizando una área de nieve pristina que es bien conocida para la calibración de instrumentos de teledetección. Debido a la relativa estabilidad de las capas de nieve, la adquisición de datos se limitó a diez días consecutivos. Se encontraron pulsaciones interferométricas a partir de un primer análisis de la amplitud de las señales recibidas, las cuales eran compatibles con un modelo de propagación multicamino donde el reflector se encuentra por debajo del nivel de la superficie. Como consecuencia de estos resultados, se ha desarrollado un modelo que reconstruye la señal recibida como la suma de un número finito de reflexiones, procedentes de diferentes capas de nieve (caracterizados por mediciones locales). La información interferométrica se recupera después del análisis espectral aplicado a las series temporales tanto de las señales reales, como de las modeladas (lag-hologramas). Encontramos que las bandas de frecuencias predichas por el modelo son en general consistentes con los datos y que los lag-hologramas muestran repetibilidad para días diferentes. Posteriormente, se realiza un análisis de los datos recogidos para determinar las capas dominantes del perfil de nieve seca que contribuyen a las reflexiones en banda L, y que a su vez, están relacionadas con gradientes significativos de densidad/permitivida

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

Characterizing Olive Grove Canopies by Means of Ground-Based Hemispherical Photography and Spaceborne RADAR Data

One of the main strengths of active microwave remote sensing, in relation to frequency, is its capacity to penetrate vegetation canopies and reach the ground surface, so that information can be drawn about the vegetation and hydrological properties of the soil surface. All this information is gathered in the so called backscattering coefficient (σ0). The subject of this research have been olive groves canopies, where which types of canopy biophysical variables can be derived by a specific optical sensor and then integrated into microwave scattering models has been investigated. This has been undertaken by means of hemispherical photographs and gap fraction procedures. Then, variables such as effective and true Leaf Area Indices have been estimated. Then, in order to characterize this kind of vegetation canopy, two models based on Radiative Transfer theory have been applied and analyzed. First, a generalized two layer geometry model made up of homogeneous layers of soil and vegetation has been considered. Then, a modified version of the Xu and Steven Water Cloud Model has been assessed integrating the canopy biophysical variables derived by the suggested optical procedure. The backscattering coefficients at various polarized channels have been acquired from RADARSAT 2 (C-band), with 38.5° incidence angle at the scene center. For the soil simulation, the best results have been reached using a Dubois scattering model and the VV polarized channel (r2 = 0.88). In turn, when effective LAI (LAIeff) has been taken into account, the parameters of the scattering canopy model are better estimated (r2 = 0.89). Additionally, an inversion procedure of the vegetation microwave model with the adjusted parameters has been undertaken, where the biophysical values of the canopy retrieved by this methodology fit properly with field measured values

DETERMINE: Novel Radar Techniques for Humanitarian Demining

Today the plague of landmines represent one of the greatest curses of modern time, killing and maiming innocent people every day. It is not easy to provide a global estimate of the problem dimension, however, reported casualties describe that the majority of the victims are civilians, with almost a half represented by children. Among all the technologies that are currently employed for landmine clearance, Ground Penetrating Radar (GPR) is one of those expected to increase the efficiency of operation, even if its high-resolution imaging capability and the possibility of detecting also non-metallic landmines are unfortunately balanced by the high sensor false alarm rate. Most landmines may be considered as multiple layered dielectric cylinders that interact with each other to produce multiple reflections, which will be not the case for other common clutter objects. Considering that each scattering component has its own angular radiation pattern, the research has evaluated the improvements that multistatic configurations could bring to the collected information content. Employing representative landmine models, a number of experimental campaigns have confirmed that GPR is capable of detecting the internal reflections and that the presence of such scattering components could be highlighted changing the antennas offset. In particular, results show that the information that can be extracted relevantly changes with the antenna separation, demonstrating that this approach can provide better confidence in the discrimination and recognition process. The proposed bistatic approach aims at exploiting possible presence of internal structure beneath the target, which for landmines means the activation or detonation assemblies and possible internal material diversity, maintaining a limited acquisition effort. Such bistatic configurations are then included in a conceptual design of a highly flexible GPR system capable of searching for landmines across a large variety of terrains, at reasonably low cost and targeting operators safety

Statistical modeling of polarimetric SAR data: a survey and challenges

Knowledge of the exact statistical properties of the signal plays an important role in the applications of Polarimetric Synthetic Aperture Radar (PolSAR) data. In the last three decades, a considerable research effort has been devoted to finding accurate statistical models for PolSAR data, and a number of distributions have been proposed. In order to see the differences of various models and to make a comparison among them, a survey is provided in this paper. Texture models, which could capture the non-Gaussian behavior observed in high resolution data, and yet keep a compact mathematical form, are mainly explained. Probability density functions for the single look data and the multilook data are reviewed, as well as the advantages and applicable context of those models. As a summary, challenges in the area of statistical analysis of PolSAR data are also discussed.Peer ReviewedPostprint (published version