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Le Alpi sono state colpite dall'intensificarsi della siccità meteorologica negli ultimi anni. A causa delle mutevoli condizioni climatiche, la regione è vulnerabile alle deviazioni nel ciclo dell'acqua, che possono essere osservate nel contesto delle anomalie dell'evapotraspirazione (ET). La temperatura della superficie terrestre (LST) è un fattore chiave nella regolazione dello scambio di acqua ed energia tra terra e atmosfera, che la mette in relazione direttamente con ET. Lo sviluppo di modelli di bilancio energetico a due fonti (TSEB) guidati da dati di telerilevamento termico ha dato un contributo significativo alla stima dell'ET su larga scala. Tuttavia, la loro risoluzione spaziale grossolana e la sensibilità degli strumenti TIR alle condizioni del cielo nuvoloso li rendono insufficienti per ecosistemi complessi, come le regioni di montagna. Per superare queste limitazioni, questa tesi è servita per sviluppare un nuovo prodotto della temperatura della superficie terrestre in cielo sereno con una risoluzione spaziale di 250 m, in alternativa ai dati MODIS LST di 1 km, per la stima dei flussi TSEB a risoluzione fine. Nella prima parte della tesi, lo squilibrio tra la risoluzione spaziale dei dati MODIS LST di 1 km è stato risolto applicando una procedura di sharpening per ottenere LST giornaliero a una risoluzione spaziale di 250 m. A causa delle ridotte capacità dei modelli statistici LST-VNIR in ecosistemi complessi, sono stati utilizzati predittori multi-sorgente, tra cui l'indice di NDVI e il DEM. Ispirato dalla superiorità dell'apprendimento automatico per problemi non lineari, sono state sfruttate le relazioni tra LST a risoluzione grossolana e predittori di 250 m con algoritmo a foresta casuale (RF). I risultati ottenuti indicano un miglioramento del 20% nell'accordo tra Landsat e l'affilato LST rispetto alle statistiche per il set di dati MODIS originale. I modelli LST hanno determinato un RMSE medio di 2,3°C e un MAE di 1,8°C. Al fine di ricostruire gli LST mancanti sotto le nuvole, l'autore ha proposto un nuovo approccio per prevedere i pixel non validi sfruttando la correlazione tra LST a terra e temperatura dell'aria in combinazione con variabili ausiliarie, ad esempio radiazione solare discendente, albedo e LAI sotto cieli nuvolosi a lungo termine. Considerando un'elevata dipendenza del sito determinata da diversi tipi di copertura del suolo, la ricostruzione LST è stata eseguita per stazioni aggregate che rappresentano tre gruppi di vegetazione: praterie, foreste e colture permanenti. Il gap-filling è stato eseguito con due passaggi: modellazione LST basata sul sito da variabili derivate dal suolo sotto cieli nuvolosi e quindi applicazione dei modelli adattati a predittori a griglia a livello di subpixel corrispondenti all'output ridotto. La ricostruzione ha ottenuto prestazioni affidabili con dati locali che producono R2 di 0,84 e RMSE di 2,12°C. Nell'ultima parte della tesi, le mappe LST risultanti sono state incorporate nel modello di bilancio energetico a due fonti di Priestley-Taylor per la stima dei flussi energetici a una risoluzione spaziale di 250 m. Innanzitutto, le prestazioni del modello forzato dalle temperature locali sono state valutate con flussi misurati da torri di eddy covariance. Le simulazioni di riferimento per il calore latente (LE) e sensibile (H) hanno prodotto un RMSE medio di 57 Wm-2 e un bias assoluto medio (MB) di 26 Wm-2. Successivamente, le stime del modello guidate da LST basati su satellite, ovvero il prodotto LST MODIS originale di 1 km e le mappe ridimensionate, sono state convalidate rispetto ai dati in situ. Flussi turbolenti modellati con LST di 250 m hanno portato a RMSE di 86 Wm-2 e MB di 55 Wm-2, che si sono tradotti in una diminuzione dell'8% e del 15% nei rispettivi errori rispetto alle stime TSEB combinate con l'LST MODIS originale. The European Alps have been affected by intensification of meteorological droughts in recent years. Due to changing climatic conditions, the region is vulnerable to deviations in water cycling, which can be observed in the context of evapotranspiration (ET) anomalies. Land surface temperature (LST) is a key factor in regulating the exchange of water and energy between land and atmosphere, which directly relates it to ET. Development of two-source energy balance (TSEB) models driven by thermal remote sensing data has made a significant contribution to estimate ET at large scale. However, their coarse spatial resolution and sensitivity of TIR instruments to cloudy-sky conditions make them insufficient for complex ecosystems, such as mountain regions. To overcome these limitations, this thesis served to develop a new clear-sky land surface temperature product at 250 m spatial resolution, as an alternative to 1-km MODIS LST data, for estimating fine-resolution TSEB fluxes. In the first part of the thesis, imbalance between spatial resolution of 1-km MODIS LST data was solved by applying a sharpening procedure to obtain daily LST at 250-m spatial resolution. Due to reduced capabilities of LST–VNIR statistical models in complex ecosystems, multi-source predictors, including normalized difference vegetation index (NDVI) and digital elevation model (DEM) were used. Inspired by superiority of machine learning for non-linear problems, relationships between coarse resolution LSTs and 250-m predictors with random forest (RF) algorithm were exploited. The obtained results indicate an improvement of 20% in the agreement between Landsat and the sharpened LST compared to statistics for the original MODIS dataset. The LST models determined averaged RMSE of 2.3°C and MAE of 1.8°C. In order to reconstruct missing LSTs beneath the clouds, the author proposed a novel approach to predict invalid pixels by exploiting correlation between ground-based LST and air temperature in conjunction with auxiliary variables, e.g., downwelling solar radiation, albedo- and LAI-derived products under long-term cloudy-skies. Considering a high site dependency driven by different land-cover types, LST reconstruction was performed for aggregated stations that represent three vegetation groups: grassland, forest and permanent crops. The gap-filling was performed with two steps: site-based LST modelling from ground-derived variables under cloudy skies, and then applying the fitted models to gridded predictors at subpixel level corresponding to the downscaled output. The reconstruction achieved reliable performance with local data yielding R2 of 0.84 and RMSE of 2.12°C. In the last part of the thesis, the resulting LST maps were incorporated into two-source energy balance model of Priestley-Taylor for estimating energy fluxes at 250-m spatial resolution. First, the performance of the model forced by local temperatures was evaluated with measured fluxes from eddy covariance towers. The benchmark simulations for latent (LE) and sensible heat (H) yielded an averaged RMSE of 57 Wm-2 and mean absolute bias (MB) of 26 Wm-2. Next, the model estimates driven by satellite-based LSTs, i.e., original 1-km MODIS LST product and downscaled maps, were validated against in-situ data. Turbulent fluxes modelled with 250-m LSTs resulted in RMSE of 86 Wm-2 and MB of 55 Wm-2, which translated to 8% and 15% decrease in the respective errors when compared to TSEB estimates combined with original MODIS LST.

Worldwide, snow and ice can be polluted with impurities also referred as Light-Absorbing Particles (LAPs). In this chapter, we review the different processes occurring at middle latitudes, tropical areas, and polar regions. We show that snow and ice albedo reduction due to LAPs deposition or resurfacing is a global phenomenon with regional characteristics. Later in the chapter, we provide a classification of LAPs based on their optical features. We divided LAPs in non-carbonaceous (mineral dust) and carbonaceous (biogenic particles and cryoconite), and we created a set of radiative transfer simulations for each category. Lastly, we described different observation approaches for studying LAPs impact on snow and ice. We divided these methods in proximal (field spectroscopy) and remote (aerial surveys and satellite data) sensing. We expect that the study of LAPs in snow and ice will grow in the future, and more data and models will be developed in order to describe the hydrological and climatic effect of LAPs in the cryosphere.

Passive measurement of sun-induced chlorophyll fluorescence (F) represents the most promising tool to quantify changes in photosynthetic functioning on a large scale. However, the complex relationship between this signal and other photosynthesis-related processes restricts its interpretation under stress conditions. To address this issue, we conducted a field campaign by combining daily airborne and ground-based measurements of F (normalized to photosynthetically active radiation), reflectance and surface temperature and related the observed changes to stress-induced variations in photosynthesis. A lawn carpet was sprayed with different doses of the herbicide Dicuran. Canopy-level measurements of gross primary productivity indicated dosage-dependent inhibition of photosynthesis by the herbicide. Dosage-dependent changes in normalized F were also detected. After spraying, we first observed a rapid increase in normalized F and in the Photochemical Reflectance Index, possibly due to the blockage of electron transport by Dicuran and the resultant impairment of xanthophyll-mediated non-photochemical quenching. This initial increase was followed by a gradual decrease in both signals, which coincided with a decline in pigment-related reflectance indices. In parallel, we also detected a canopy temperature increase after the treatment. These results demonstrate the potential of using F coupled with relevant reflectance indices to estimate stress-induced changes in canopy photosynthesis.

[EN] The HyPlant imaging spectrometer is a high-performance airborne instrument consisting of two sensor modules. The DUAL module records hyperspectral data in the spectral range from 400-2500 nm, which is useful to derive biochemical and structural plant properties. In parallel, the FLUO module acquires data in the red and near infrared range (670-780 nm), with a distinctly higher spectral sampling interval and finer spectral resolution. The technical specifications of HyPlant FLUO allow for the retrieval of sun-induced chlorophyll fluorescence (SIF), a small signal emitted by plants, which is directly linked to their photosynthetic efficiency. The combined use of both HyPlant modules opens up new opportunities in plant science. The processing of HyPlant image data, however, is a rather complex procedure, and, especially for the FLUO module, a precise characterization and calibration of the sensor is of utmost importance. The presented study gives an overview of this unique high-performance imaging spectrometer, introduces an automatized processing chain, and gives an overview of the different processing steps that must be executed to generate the final products, namely top of canopy (TOC) radiance, TOC reflectance, reflectance indices and SIF maps., We gratefully acknowledge the financial support by the European Space Agency (ESA) for airborne data acquisition, development of the HyPlant processing chain and data analysis in the frame of the HyFLEX campaign (ESA contract no. 4000107143/12/NL/FF/If CCN3), the FLEXSense campaign (ESA Contract No. RFP/3-15477/18/NL/NA) and the HYPER project (ESA Contract No. 4000112890/14/NL/FF/gp). The Deutsche Forschungsgemeinschaft (DFG) provided additional financial support by the SFB/TR 32 'Pattern in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling, and Data Assimilation' project D2. Moreover, this work has partially been funded by the German Federal Ministry of Education and Research within the German-Plant-Phenotyping Network (DPPN) (project identification number: 031A053), the European Union in the frame of the INTEREG project 'Sensor Products for Enterprises Creating Technological Opportunities in airborne Remote Sensing' (SPECTORS) (project identification number: 143081) and the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement number 721995 in the frame of the 'Training on Remote Sensing for Ecosystem Modelling' (TRuStEE) network.

Thermal inertia has been successfully used in remote sensing applications that span from geology, geomorphology to hydrology. In this paper, we propose the use of thermal inertia for describing snow dynamics. Two different formulations of thermal inertia were tested using experimental and simulated data related to snowpack dynamics. Experimental data were acquired between 2012 and 2017 from an automatic weather station located in the western Italian Alps at 2,160 m. Simulations were obtained using the one‐dimensional multilayer Crocus model. Results provided evidences that snowmelt phases can be recognized, and average snowpack density can be estimated reasonably well from thermal inertia observations (R2 = 0.71; RMSE = 65 kg/m3). The empirical model was also validated with manual snow density measurements (R2 = 0.80; RMSE = 54 kg/m3). This study is the first attempt at the exploitation of thermal inertia for snow monitoring, combining optical and thermal remote sensing data. Plain Language Summary Alpine snow represents a fundamental reservoir of fresh water at midlatitude. Remote sensing offers the opportunity to estimate snow properties in different spectral domains. In particular, the knowledge of the spatial and temporal variability of snow density could allow modeling of the snow water equivalent, which knowledge is crucial for managing water resources in the face of current climate change. In this study we show for the first time that snow thermal inertia can contribute to monitoring of snowmelt processes and snow density, opening new perspectives for remote sensing of the cryosphere.

Imaging and non-imaging spectroscopy employed in the field and from aircraft is frequently used to assess biochemical, structural, and functional plant traits, as well as their dynamics in an environmental matrix. With the increasing availability of high-resolution spectroradiometers, it has become feasible to measure fine spectral features, such as those needed to estimate sun-induced chlorophyll fluorescence (F), which is a signal related to the photosynthetic process of plants. The measurement of F requires highly accurate and precise radiance measurements in combination with very sophisticated measurement protocols. Additionally, because F has a highly dynamic nature (compared with other vegetation information derived from spectral data) and low signal intensity, several environmental, physiological, and experimental aspects have to be considered during signal acquisition and are key for its reliable interpretation. The European Cooperation in Science and Technology (COST) Action ES1309 OPTIMISE has produced three articles addressing the main challenges in the field of F measurements. In this paper, which is the second of three, we review approaches that are available to measure F from the leaf to the canopy scale using ground-based and airborne platforms. We put specific emphasis on instrumental aspects, measurement setups, protocols, quality checks, and data processing strategies. Furthermore, we review existing techniques that account for atmospheric influences on F retrieval, address spatial scaling effects, and assess quality checks and the metadata and ancillary data required to reliably interpret retrieved F signals. ISSN:2072-4292

Retrieval of Sun-Induced Chlorophyll Fluorescence (F) spectrum is one of the challenging perspectives for further advancing F studies towards a better characterization of vegetation structure and functioning. In this study, a simplified Spectral Fitting retrieval algorithm suitable for retrieving the F spectrum with a limited number of parameters is proposed (two parameters for F). The novel algorithm is developed and tested on a set of radiative transfer simulations obtained by coupling SCOPE and MODTRAN5 codes, considering different chlorophyll content, leaf area index and noise levels to produce a large variability in fluorescence and reflectance spectra. The retrieval accuracy is quantified based on several metrics derived from the F spectrum (i.e., red and far-red peaks, O2 bands and spectrally-integrated values). Further, the algorithm is employed to process experimental field spectroscopy measurements collected over different crops during a long-lasting field campaign. The reliability of the retrieval algorithm on experimental measurements is evaluated by cross-comparison with F values computed by an independent retrieval method (i.e., SFM at O2 bands). For the first time, the evolution of the F spectrum along the entire growing season for a forage crop is analyzed and three diverse F spectra are identified at different growing stages. The results show that red F is larger for young canopy; while red and far-red F have similar intensity in an intermediate stage; finally, far-red F is significantly larger for the rest of the season.

Remote sensing of solar-induced chlorophyll fluorescence (SIF) is a rapidly advancing front in terrestrial vegetation science, with emerging capability in space-based methodologies and diverse application prospects. Although remote sensing of SIF – especially from space – is seen as a contemporary new specialty for terrestrial plants, it is founded upon a multi-decadal history of research, applications, and sensor developments in active and passive sensing of chlorophyll fluorescence. Current technical capabilities allow SIF to be measured across a range of biological, spatial, and temporal scales. As an optical signal, SIF may be assessed remotely using high-resolution spectral sensors in tandem with state-of-the-art algorithms to distinguish the emission from reflected and/or scattered ambient light. Because the red to far-red SIF emission is detectable non-invasively, it may be sampled repeatedly to acquire spatio-temporally explicit information about photosynthetic light responses and steady-state behaviour in vegetation. Progress in this field is accelerating with innovative sensor developments, retrieval methods, and modelling advances. This review distills the historical and current developments spanning the last several decades. It highlights SIF heritage and complementarity within the broader field of fluorescence science, the maturation of physiological and radiative transfer modelling, SIF signal retrieval strategies, techniques for field and airborne sensing, advances in satellite-based systems, and applications of these capabilities in evaluation of photosynthesis and stress effects. Progress, challenges, and future directions are considered for this unique avenue of remote sensing., In addition, we recognize the following funding: Zbyněk Malenovský was supported by the Australian Research Council Future Fellowship Bridging Scales in Remote Sensing of Vegetation Stress (FT160100477). Uwe Rascher acknowledges the SEN2Exp project funded by the European Space Agency in supporting part of this work.

International audience; Terrestrial gross primary productivity (GPP) plays an essential role in the global carbon cycle, but the quantification of the spatial and temporal variations in photosynthesis is still largely uncertain. Our work aimed to investigate the potential of remote sensing to provide new insights into plant photosynthesis at a fine spatial resolution. This goal was achieved by exploiting high-resolution images acquired with the FLuorescence EXplorer (FLEX) airborne demonstrator HyPlant. The sensor was flown over a mixed forest, and the images collected were elaborated to obtain two independent indicators of plant photosynthesis. First, maps of sun-induced chlorophyll fluorescence (F), a novel indicator of plant photosynthetic activity, were successfully obtained at both the red and far-red peaks (r2 = 0.89 and p 0.05). The spatial relationships found at high resolution provide valuable insight into the critical role of spatial heterogeneity in controlling the relationship between the far-red F and the GPP, indicating the need to consider this heterogeneity at a coarser resolution.

We have evaluated a technique initially developed for the seismic refraction imaging, the stacked refraction convolution section (SRCS), which we have properly adapted to process ground-penetrating radar (GPR) refraction data. Through a mute operation, the subsurface refracting signals, recorded by the receiver from two reciprocal sources, are selected. Following that, a velocity analysis by means of the crosscorrelation of the refracted signals and the convolution of resulting traces is performed. The refraction image in intercept times is successively derived from three main steps, namely: (1) the convolution of the subsurface refracted signals, (2) the crosscorrelation of convolved trace with the reciprocal refracted signal, and (3) the stacking of crosscorrelated traces over all source couples. The technique is not only suitable for the processing of GPR data acquired with two or more reciprocal common source profiles but it is also convenient for its low acquisition cost in addition to the simplicity of software implementation and short processing times. We have evaluated the technique on a real GPR data set to characterize a near-surface morphostructure associated with a deep-seated gravitational slope deformation affecting Mt. Watles (Upper Venosta Valley, Italy). Results of the SRCS technique were validated against the direct trenching log data up to approximately 3 m in depth and complemented by the reflection processing outputs of common-source and common-offset data acquired along the line. The SRCS and common-midpoint processing provide the best reconstruction of the subsurface morphology of a shallow basement (approximately [Formula: see text] depth), characterized by a velocity range of [Formula: see text] and made of strongly to moderately weathered paragneiss. The full-wave modeling response of the reconstructed model demonstrates good agreement with the recorded signals.

Full Waveform Inversion has become an important research field in the context of seismic exploration, due to the possibility to estimate a high-resolution model of the subsurface in terms of acoustic and elastic parameters. To this aim, issues such as an efficient implementation of wave equation solution for the forward problem, and optimization algorithms, both local and global, for this high non-linear inverse problem must be tackled. In this thesis, in the framework of 2D acoustic approximation, I implemented an efficient numerical solution of the wave equation based on a local order of approximation of the spatial derivatives to reduce the computational time and the approximation error. Moreover, for what concerns the inversion, I studied two different global optimization algorithms (Simulated Annealing and Genetic Algorithms) on analytic functions that represent different possible scenarios of the misfit function to estimate an initial model for local optimization algorithm in the basin of attraction of the global minimum. Due to the high number of unknowns in seismic exploration context, of the order of some thousands or more, different strategies based on the adjoint method must be used to compute the gradient of the misfit function. By this procedure, only three wave equation solutions are required to compute the gradient instead of a number of solutions proportional to the unknown parameters. The FWI approach developed in this thesis has been applied first on a synthetic inverse problem on the Marmousi model to validate the whole procedure, then on two real seismic datasets. The first is a land profile with two expanding spread experiments and is characterized by a low S/N ratio. In this case, the main variations of the estimated P-wave velocity model well correspond to the shallow events observed on the post-stack depth migrated section. The second is a marine profile extracted from a 3D volume where the local optimization, based on the adjoint method, allows to estimate a high-resolution velocity model whose reliability has been checked by the alignment of the CIGs computed by pre-stack depth migration.

Full Waveform Inversion (FWI) is a computational method to estimate the physical features of Earth subsurface from seismic data, leading to the minimization of a misfit function between the observed data and the predicted ones, computed by solving the wave equation numerically. This function is usually multimodal, and any gradient-based method would likely get trapped in a local minimum, without a suitable starting point in the basin of attraction of the global minimum. The starting point of the gradient procedure can be provided by an exploratory stage performed by an algorithm incorporating random elements. In this paper, we show that Bayesian Optimization (BO) can offer an effective way to structure this exploration phase. The computational results on a 2D acoustic FWI benchmark problem show that BO can provide a starting point in the parameter space from which the gradient-based method converges to the global optimum.

Borehole flowmeter logs can provide information on direction and discharge of vertical flows, hydraulic conductivities of different aquifer intervals. Furthermore, they can give a valid support to the interpretation of environmental data (e.g. electrical conductivity, pH, temperature, dissolved oxygen) into aquifers and along each borehole, and to correctly design and analyse tracer tests for aquifer characterization. We show the results for the application of electromagnetic flowmeter measurements in three case studies (Northern Italy). All the test sites are located in a plain area. The first case study concerns a complex aquifer, characterized by a chaotic sequence of gypsum-marls, where closely spaced boreholes have been drilled to design a remediation project. We performed both natural and forced gradient tests. The second is a single aquifer contaminated site by an oil blow out event for which a complete geophysical and hydrogeological characterization is available. The last one is a test site equipped by our department in a single highly stressed aquifer where three closely spaced boreholes have been used for a complete tracing test under "ambient" flow conditions. At all the sites the analysis of ambient vertical flows within a borehole allows the identification of inflow/outflow zones. As an example at the first study site, we observed a large vertical ambient flow (up to 3 l/min), due to head differences between levels associated with highly permeable layers/fractures. The collected data have been fundamental for a correct evaluation of observed changes in borehole environmental data. In fact, without the collected information on vertical flows, these changes could be misleading, compromising the hydrogeological site characterization. A single-hole flowmeter analysis under stressed conditions (injection or pumping) can provide a high resolution vertical profile of hydraulic conductivity depending on the log sampling spacing. By a cross-hole flowmeter analysis it is possible to check the hydraulic interconnections between the boreholes through a network of permeable layers. Again, a complete understanding of ambient flows and interconnections provides the support for cross-hole tracer test design and evaluation. This has been experienced at different sites. In fact, flowmeter logs can provide the exact points for tracer injection and detection within the boreholes. Moreover, the water discharge at the tracer detection point can be measured allowing for a quantitative analysis of the tracer breakthrough curve and mass recovery. One clear example is presented for this type of analysis, showing how it can provide an index of reliability of the tracer test. Finally, the detailed characterization of the aquifer system provided by the flowmeter alone or in conjunction with other techniques

La prospezione archeologica e lo scavo di un'antica città è un’operazione delicata, lenta e perciò costosa. Spesso, e soprattutto nell'area mediterranea, le città venivano costruite nei pressi della costa per permettere lo svolgimento di attività commerciali lungo le vie di trasporto più comode per le epoche passate. Successivi movimenti relativi tra la terraferma e il mare, in scenario con una sedimentazione accentuata dall'azione dei venti e del mare stesso, hanno portato al ricoprimento di queste città e quasi regolarmente dei loro sistemi portuali. La prospezione archeologica in questi siti è spesso complicata dalla difficile "lettura" della parte a mare e perciò dei rapporti tra strutture su terraferma e strutture a mare. Nasce quindi come importante necessità quella di una prospezione complessiva del sito, che è ovviamente molto costosa e lenta e perciò poco fruibile se non in tempi molto lunghi. Questi siti sono difficilmente valorizzabili. Una prospezione preliminare attuata con metodologie innovative di tipo non distruttivo, può consentire in tempi brevi una visualizzazione complessiva del sito e ad ottimizzare i costi dell'intervento diretto, proponendolo solo su aree di interesse. Quasi tutti i siti di interesse archeologico fino ad oggi sono stati poco studiati con metodi di tipo indiretto a causa dell’impossibilità di operare in acque basse, in quanto le aree di interesse sono quasi sempre all’interno di lagune chiuse con fondali che sono molto spesso al disotto di un metro di profondità. Il presente lavoro di tesi è stato svolto in concomitanza ad un progetto firb che individuava al suo interno alcune aree di interesse archeologico con caratteristiche che rispecchiano quanto esposto poc’anzi. Tale progetto aveva lo scopo di provare vari metodi geofisici per verificarne l’applicabilità in condizioni così estreme e di verificare sui siti indagati l’eventuale esistenza di reperti archeologici sepolti. Per quanto riguarda le strumentazioni utilizzate si è testato l’utilizzo di un ecoscandaglio ad altissima risoluzione (multi beam Reason 8125), un profilatore sismico a riflessione o sub bottom profiler (Innomar Ses 2000 Compact) e di un georesistivimetro equipaggiato con elettrodi galleggianti per rilievi in acqua (Iris Syscal Pro), che verranno descritti nei capitoli successivi. Analizzando in dettaglio la struttura del presente lavoro di tesi, i capitoli sono di seguito descritti. Nel secondo capitolo sono stati trattati i metodi geofisici tradizionalmente utilizzati per la ricerca archeologica a terra, nel terzo capitolo sono stati descritti i metodi indiretti utilizzati in mare per la prospezione archeologica, mentre nel quarto capitolo si spiega come si è tentato di coniugare diversi metodi: di mare e di terra ed applicarli in zone di fondali bassi, difficilmente rilevabili con imbarcazioni convenzionali. Nel quinto capitolo si affronta in particolare il progetto e la costruzione di un prototipo sperimentale di imbarcazione adatto ai rilievi in acque basse. Nel capitolo sesto invece si entrerà in dettaglio dei vari metodi utilizzati nelle campagne di rilievo eseguite. Infine nel settimo capitolo verranno presentati i risultati dei rilievi e nell’ottavo capitolo le conclusioni del presente lavoro di tesi.

In the present work we present first results of ground deformation measurements inferred through repeat-pass Synthetic Aperture Radar (SAR) Interferometry (InSAR) in C- and X-band over an Italian Alpine area, in Lombardia region. The activity was carried out in the framework of the MORFEO (MOnitoraggio e Rischio da Frana mediante dati EO) project founded by the Italian Spatial Agency (ASI) and dedicated to landslide risk assessment. A number of areas affected by hydrogeological instabilities have been selected and studied in detail by processing both C- and X-band SAR data through SPINUA, a Persistent Scatterer like algorithm. In particular, two stacks of 30 Ascending ENVISAT SAR images (October 2004 - January 2009) and 32 Descending ENVISAT SAR images (December 2004 - January 2009) have been independently processed to ensures the detection of movements occurring along both west and east facing slopes. Moreover, further deformation measurements have been obtained by processing a set of 12 COSMO-SkyMED ascending HIMAGE interferometric acquisitions (Satellite CSKS1; Beam HI-03; POL: HH; Incidence Angle: 29°) provided by ASI. After a proper tuning of the interferometric algorithmic solutions, even with very high normal baselines, we are able to appreciate the potentials of X-band interferometry. Although the number of COSMO-SkyMED acquisitions is quite limited, spanning a period of only 10 months (August 2008 - June 2009), SPINUA was capable to retrieve preliminary ground displacement patterns that are in good agreement with those previously estimated in C-band. Quite impressive is to realize that, because of the tenfold improved resolution of X-band images, multi-temporal InSAR techniques may be successfully applied for the estimation of the displacement maps with a number of acquisitions much lower than in C-band. InSAR-derived displacements provided on areas of hydrogeological interest are going to be validated in the framework of MORFEO project by the geological partnership thanks to the availability of ground truths. In the present work, we present the results obtained on the towns of Garzeno, Catasco and Germasino which are affected by landslide phenomena. We provide a first validation by comparing the deformation maps derived from ENVISAT C-band data, from COSMO-SkyMED X-band data as well as from ERS and RADARSAT C-band data freely available on the GeoIFFI web-catalogue.

Hydrological and hydrogeological dynamics along mountain slopes control many important phenomena, such as shallow landslide triggering and flood generation. The governing factors include: soil thickness, slope and bedrock morphology, rainfall pattern and subsurface groundwater conditions, both in the vadose zone and under the water table. We present the results of a monitoring project undertaken on a large slope parcel in the Alpine region of northern Italy. Both direct (piezometers, tensiometers, etc.) and indirect (geophysical) methods have been used to characterize slope and bedrock morphology as well as changes in soil moisture content over time. In this note, we focus on the use of the ground-penetrating radar (GPR) in surface-to-surface configuration. Recently, the use of multi- and single-offset GPR has been advocated for intermediate scale monitoring of moisture content changes in agricultural soils, e.g. in vineyards. We investigate the applicability of similar techniques to hillslopes. The monitoring has been performed using a PulseEkko 100 radar system. The estimation of the soil moisture content is based on the differential arrival time of direct waves through the air and the soil itself. GPR data can also provide information about the bedrock morphology, with special regard to the degree of fracturing. Care must be taken in data interpretation, because the GPR signal propagates in the soil layer as a guided wave, having a dispersive character (phase velocity is function of frequency) and possibly different modes. Consequently, the wave¿s first arrival at a different offset cannot be simply interpreted as a direct wave through the shallow soil layer. Inversion of the dispersion curve ¿ phase velocity versus frequency ¿ must be performed to yield velocity and thickness of the soil layer as well as velocity of the bedrock. We show that GPR data, properly processed and inverted, carry significant information about the site structure and hydrological dynamics of mountain slopes

Borehole and surface geophysical methods can assist hydrogeological site characterization by providing efficiently and cost-effectively information on the continuity of permeable or less permeable zones, and by delineating the geometry of an aquifer. The use of time lapse geophysical surveying offers an effective tool for monitoring dynamic processes within the aquifer (e.g., effect of pumping or recharge of the aquifer), mapping 2D/3D evolution of water infiltration, and estimating the hydraulic parameters of the aquifer. Coupled hydrogeological and geophysical investigations were performed to characterize at small-scale an aquifer at shallow depth (less than 30 m). Highly heterogeneous aquifers consisting of discontinuous sequences of gypsum-marls and carbonates represent a challenging environment for the remediation of a diffuse contamination of chlorinated solvents. The clean-up design by means of injection of a suitable reagent requires an accurate prediction of the aquifer geometry to detect the main productive levels and to estimate their hydrodynamic parameters. The hydro-geophysical characterization was aimed at i) detecting the most permeable and porous level within the gypsum-calcareous formation in a depth range between 10 and 20 m from the surface, ii) observing the hydraulic connection of the main productive levels, and iii) estimating the hydrodynamic properties of the aquifer. The hydro-geophysical characterization involved several approaches. Geophysics aimed at estimating the lateral continuity of the most permeable layers and also estimating the water content of the main productive layers. Ground penetrating radar (GPR) deployed in cross-hole mode between three boreholes and in single-hole configuration allowed the detection of the main productive levels in the gypsum and calcareous formation. Radar signals did not transmit through the high electrical conductivity of marl and clay levels. Electrical resistivity tomography (ERT) in cross-hole configuration confirmed the presence of low resistivity layers (in the order of 10-20 ohm m), responsible for the low penetrating distance of the GPR survey. ERT surveys identified the presence of three main productive levels at depths between 13 m to 19 m. Specifically, the ERT in time lapse configuration showed the sensitivity of the uppermost permeable layer (13-14 m) to the effect of pumping of the aquifer; an abrupt increase of resistivity was noted after pumping, demonstrating the high transmissivity of that level. Single-well flowmeter logs and conventional pumping tests determined the different inflow-outflow zones along each borehole betweeen 15 and 22 m and the vertical profile of aquifer hydraulic conductivity. A characteristic very high vertical ambient flow into the boreholes (up to 3 l/min), due to a strong head difference between the productive levels, was observed. Cross-well flowmeter logs under stressed conditions provided a check of the connections between the productive levels. Moreover, the flowmeter log was also essential for planning and evaluating a dye tracer test. The tracer test involved the injection of dye tracers and the use of a downhole fluorometer, and allowed us to estimate the local aquifer flow velocity of 148 m/d in the most permeable layer. This information is critical to correctly plan the subsequent site remediation activity by means of reagent injection. We demonstrated that in the specific case, the complete hydrogeophysical characterization (hydraulic and geophysics) detects with good accuracy the spatial heterogeneity of the aquifer, permitting to improve the reliability of the design of the remediation activity.

The use of GPR waves for the measurement of soil moisture content has become increasingly popular both in surface and borehole antenna configurations. Advantages of GPR over other more traditional techniques, such as TDR, are: (a) that the scale of measurement is larger (about a cubic metre at 100 MHz, smaller at higher frequencies) and the estimated moisture content is therefore representative of a larger support volume; (b) measurements are fast and totally non invasive; (c) a large area can be covered in a limited time, so that spatial variations of moisture content can be reliably mapped with no need for (uncertain) interpolation of TDR point measurements. Disadvantages emerge as a consequence of the free propagation of electromagnetic waves that are not, unlike in the case of TDR, bounded by a man-made waveguide. Consequently some care must be taken in the data interpretation. In this work we plan to demonstrate that the measurement of moisture content along Alpine mountain slopes is one of the cases that require more sophisticated processing and inversion techniques to yield representative results. The hydrological dynamics along mountain slopes control many important phenomena, such as shallow landslide triggering and flood generation. The governing factors include: soil thickness, slope and bedrock morphology, rainfall pattern and subsurface groundwater conditions, both in vadose zone and under the water table.We present the results of a monitoring project currently undertaken on a large slope plot in the Alpine region of Northern Italy. Both direct (piezometers, tensiometers, etc.) and indirect (geophysical) methods are being used to characterize slope and bedrock morphology and changes in soil moisture content. The site is located at an elevation of 1150ma.s.l. The slope facesWSW, with a dip varying between 30_ and 40_. The soil cover, 1-2 m thick, is characterized by extended unconsolidated deposits, with decimetric to metric blocks of different nature (serpentinites, granites, limestones) in a sandy-gravelly matrix, usually interpreted as moraine deposits. The bedrock is made of paragneiss with subvertical foliation and highly friable. The GPR monitoring has been performed using a PulseEkko 100 radar system. Given the small soil thickness and the limited porosity of the underlying bedrock, the soil layer behaves as a low-velocity waveguide sandwiched between air and the high velocity bedrock. This fact gives rise to the propagation of dispersive guide waves (velocity is a function of frequency) that obey a modal equation. We present a methodology to process and interpret the data to yield radar velocity of soil and bedrock, and soil thickness. The amount of additional information that can be derived from GPR data collected in the process is assessed, and we compare the results of GPR monitoring with other information on moisture content dynamics and geological structure of the site.

The wave scattered by the unknown obstacle is approximated by two different representations, one in the far zone, the other on the obstacle boundary. Each of these representations contains expansion coefficients which can be related by an approximate back propagator (ABP). The latter depends non-linearly on the parameters which describe the obstacle shape, and yields the boundary scattered wave from knowledge of the far field data. Reconstruction is carried out by minimising the L^2 norm of the boundary defect with respect to the shape parameters and other auxiliary unknowns. A numerical reconstruction from the Ipswich data is presented. A convergence propert of the approximate forward propagator is stated.

The inverse problem considered herewith consists of determining the shape of a two dimensional, perfectly conducting obstacle from knowledge of the incident monochromatic plane electromagnetic wave and of a set of laboratory measurements related to the scattered wave: the Ipswich data. The solution algorithm and its numerical implementation rely on approximate back propagation (ABP). The latter is an algebraic transformation, which is deduced from the properties of complete families of base functions and relates the far field scattering coefficients to those on the obstacle boundary. The features presented herewith for the first time are: a) a consistency result for a forward propagator, which transforms least squares boundary coefficients into far field scattering coefficients; b) the development and testing of a scalar ABP method for two dimensional electromagnetic problems, where polarization is vertical; c) the outline and the implementation of a vector ABP method for horizontal polarization; d) the application of both methods to the inversion of experimental data. Since general conditions for the well posedness of ABP methods are still unknown, the main related open problems are also stated.

Electrical networks containing a (countable) infinity of components provide a modelling challenge that involves both functional analysis and graph theory.

Catchment and hillslope hydrology is a major research area in geoscience and the understanding of its underlying processes is still poor. Direct investigation of steep hillslopes via drilling is often infeasible. In this paper, we present the results of non-invasive time-lapse monitoring of a controlled infiltration test at a site in the Italian Central Alps. The hillslope considered is steep (30–35°), covered with grass and a soil layer 1–1.5 m thick above a variably fractured metamorphic bedrock. The key hydrologic question is whether rainfall infiltrates mainly into the underlying fractured bedrock, thus recharging a deeper hydraulic system, or flows in the soil layer as interflow towards the stream channel a few hundred metres downhill. In order to respond to this question, we applied 2200 mm of artificial rain on a 2 m × 2 m slope box over about 18 hours. We estimated the effective infiltration by subtracting the measured runoff (7% of total). Due to the limited irrigation time and the climate conditions, the evapotranspiration was considered as negligible. The soil moisture variation and the underlying bedrock were monitored via a combination of electrical resistivity tomography (ERT), TDR probes and tensiometers. A small-scale 3D cross-hole ERT experiment was performed using 2 m deep boreholes purposely drilled and completed with electrodes in the irrigated plot. A larger scale (35 m long) 2D surface ERT survey was also continuously acquired across the irrigated area. Monitoring continued up to 10 days after the experiment. As a result, we observed a very fast vertical infiltration through the soil cover, also favoured by preferential flow patterns, immediately followed by infiltration into the fractured bedrock. The surface layer showed a fast recovery of initial moisture condition nearly completed in the first 12 hours after the end of irrigation. The lateral transmission of infiltrating water and runoff were negligible as compared to the vertical infiltration. These experiment results confirm that the fractured bedrock has a key role in controlling the fast hydrological dynamics of the small catchment system under study. We concluded that deep water circulation is the key pathway to hillslope processes at this site.important