Remote sensing of Earth terrain

Research findings are summarized for projects dealing with the following: application of theoretical models to active and passive remote sensing of saline ice; radiative transfer theory for polarimetric remote sensing of pine forest; scattering of electromagnetic waves from a dense medium consisting of correlated Mie scatterers with size distribution and applications to dry snow; variance of phase fluctuations of waves propagating through a random medium; theoretical modeling for passive microwave remote sensing of earth terrain; polarimetric signatures of a canopy of dielectric cylinders based on first and second order vector radiative transfer theory; branching model for vegetation; polarimetric passive remote sensing of periodic surfaces; composite volume and surface scattering model; and radar image classification

Full Wave 2D Modeling of Scattering and Inverse Scattering for Layered Rough Surfaces with Buried Objects.

Efficient and accurate modeling of electromagnetic scattering from layered rough surfaces with buried objects finds applications ranging from detection of landmines to remote sensing of subsurface soil moisture. In this dissertation, the formulation of a hybrid numerical/analytical solution to electromagnetic scattering from layered rough surfaces is first developed. The solution to scattering from each rough interface is sought independently based on the extended boundary condition method (EBCM), where the scattered fields of each rough interface are expressed as a summation of plane waves and then cast into reflection/transmission matrices. To account for interactions between multiple rough boundaries, the scattering matrix method (SMM) is applied to recursively cascade reflection and transmission matrices of each rough interface and obtain the composite reflection matrix from the overall scattering medium. The validation of this method against the Method of Moments (MoM) and Small Perturbation Method (SPM) will be addressed and the numerical results which investigate the potential of low frequency radar systems in estimating deep soil moisture will be presented. Computational efficiency of the proposed method is also addressed. In order to demonstrate the capability of this method in modeling coherent multiple scattering phenomena, the proposed method has been employed to analyze backscattering enhancement and satellite peaks due to surface plasmon waves from layered rough surfaces. Numerical results which show the appearance of enhanced backscattered peaks and satellite peaks are presented. Following the development of the EBCM/SMM technique, a technique which incorporates a buried object in layered rough surfaces is proposed by employing the T-matrix method and the cylindrical-to-spatial harmonics transformation. Validation and numerical results are provided. Finally, a multi-frequency polarimetric inversion algorithm for the retrieval of subsurface soil properties using VHF/UHF band radar measurements is developed. The top soil dielectric constant is first determined using an L-band inversion algorithm. For the retrieval of subsurface properties, a time-domain inversion technique is employed together with a parameter optimization for the pulse shape of time delay echoes from VHF/UHF band radar observations. Some numerical studies to investigate the accuracy of the proposed inversion technique in presence of errors are shown.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/58459/1/kuoch_1.pd

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

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

Passive Microwave Remote Sensing of Snow Layers Using Novel Wideband Radiometer Systems and RFI Mitigation

Climate change can reduce the availability of water resources in many regions, and it will affect agriculture, industry, and energy supply. Snowpack monitoring is important in water resource management as well as flood and avalanche protection. The rapid melting process due to global warming changes the snowpacks' annual statistics, including the extent, and the snow water equivalent (SWE) of seasonal snowpacks, which results in non-stationary annual statistics that should be monitored in nearly daily intervals. The development of advanced radiometric sensors capable of accurately measuring the snowpack thickness and SWE is needed for the long-term study of the snowpack parameters' statistical changes. Passive microwave radiometry provides a means for measuring the microwave emission from a scene of snow and ice. A Wideband Autocorrelation Radiometer (ac{WiBAR}) operating from 1-2~GHz measures spontaneous emission from snowpack at long wavelengths where the scattering is minimized, but the snow layer coherent effects are preserved. By using a wide bandwidth to measure the spacing between frequencies of constructive and destructive interference of the emission from the soil under the snow, it can reveal the microwave travel time through the snow, and thus the snow depth. However, narrowband radio frequency interference (RFI) in the WiBAR's frequency of operations reduces the ability of the WiBAR to measure the thickness accurately. In addition, the current WiBAR system is a frequency domain, FD-WiBAR, system that uses a field-portable spectrum analyzer to collect the data and suffers from high data acquisition time which limits its applications for spaceborne and airborne technologies. In this work, a novel frequency tunable microwave comb filter is proposed for RFI mitigation. The frequency response of the proposed filter has a pattern with many frequencies band-pass and band rejection that preserves the frequency span while reducing the RFI. Moreover, we demonstrate time-domain WiBAR, TD-WiBAR, which presented as an alternative method for FD-WiBAR, and is capable of providing faster data acquisition. A new time-domain calibration is also developed for TD-WiBAR and evaluated with the frequency domain calibration. To validate the TD-WiBAR method, simulated laboratory measurements are performed using a microwave scene simulator circuit. Then the WiBAR instrument is enhanced with the proposed comb filter and showed the RFI mitigation in time-domain mode on an instrument bench test. Furthermore, we analyze the effects of an above snow vegetation layer on brightness temperature spectra, particularly the possible decay of wave coherence arising from volume scattering in the vegetation canopy. In our analysis, the snow layer is assumed to be flat, and its upward emission and surface reflectivities are modeled by a fully coherent model, while an incoherent radiative transfer model describes the volume scattering from the vegetation layer. We proposed a unified framework of vegetation scattering using radiative transfer (RT) theory for passive and active remote sensing of vegetated land surfaces, especially those associated with moderate-to-large vegetation water contents (VWCs), e.g., forest field. The framework allows for modeling passive and active microwave signatures of the vegetated field with the same physical parameters describing the vegetation structure. The proposed model is validated with the passive and active L-band sensor (PALS) acquired in SMAPVEX12 measurements in 2012, demonstrating the applicability of this model.PHDElectrical and Computer EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169653/1/maryamsa_1.pd

Electromagnetic Waves

This book is dedicated to various aspects of electromagnetic wave theory and its applications in science and technology. The covered topics include the fundamental physics of electromagnetic waves, theory of electromagnetic wave propagation and scattering, methods of computational analysis, material characterization, electromagnetic properties of plasma, analysis and applications of periodic structures and waveguide components, and finally, the biological effects and medical applications of electromagnetic fields

Remote Sensing Observations of Tundra Snow with Ku- and X-band Radar

Seasonal patterns of snow accumulation in the Northern Hemisphere are changing in response to variations in Arctic climate. These changes have the potential to influence global climate, regional hydrology, and sensitive ecosystems as they become more pronounced. To refine our understanding of the role of snow in the Earth system, improved methods to characterize global changes in snow extent and mass are needed. Current space-borne observations and ground-based measurement networks lack the spatial resolution to characterize changes in volumetric snow properties at the scale of ground observed variation. Recently, radar has emerged as a potential complement to existing observation methods with demonstrated sensitivity to snow volume at high spatial resolutions (< 200 m). In 2009, this potential was recognized by the proposed European Space Agency Earth Explorer mission, the Cold Regions High Resolution Hydrology Observatory (CoReH2O); a satellite based dual frequency (17.2 and 9.6 GHz) radar for observation of cryospheric variables including snow water equivalent (SWE). Despite increasing international attention, snow-radar interactions specific to many snow cover types remain unevaluated at 17.2 or 9.6 GHz, including those common to the Canadian tundra. This thesis aimed to use field-based experimentation to close gaps in knowledge regarding snow-microwave interaction and to improve our understanding of how these interactions could be exploited to retrieve snow properties in tundra environments. Between September 2009 and March 2011, a pair of multi-objective field campaigns were conducted in Churchill, Manitoba, Canada to collect snow, ice, and radar measurements in a number of unique sub-arctic environments. Three distinct experiments were undertaken to characterize and evaluate snow-radar response using novel seasonal, spatial, and destructive sampling methods in previously untested terrestrial tundra environments. Common to each experiment was the deployment of a sled-mounted dual-frequency (17.2 and 9.6 GHz) scatterometer system known as UW-Scat. This adaptable ground-based radar system was used to collect backscatter measurements across a range of representative tundra snow conditions at remote terrestrial sites. The assembled set of measurements provide an extensive database from which to evaluate the influence of seasonal processes of snow accumulation and metamorphosis on radar response. Several advancements to our understanding of snow-radar interaction were made in this thesis. First, proof-of-concept experiments were used to establish seasonal and spatial observation protocols for ground-based evaluation. These initial experiments identified the presence of frequency dependent sensitivity to evolving snow properties in terrestrial environments. Expanding upon the preliminary experiments, a seasonal observation protocol was used to demonstrate for the first time Ku-band and X-band sensitivity to evolving snow properties at a coastal tundra observation site. Over a 5 month period, 13 discrete scatterometer observations were collected at an undisturbed snow target where Ku-band measurements were shown to hold strong sensitivity to increasing snow depth and water equivalent. Analysis of longer wavelength X-band measurements was complicated by soil response not easily separable from the target snow signal. Definitive evidence of snow volume scattering was shown by removing the snowpack from the field of view which resulted in a significant reduction in backscatter at both frequencies. An additional set of distributed snow covered tundra targets were evaluated to increase knowledge of spatiotemporal Ku-band interactions. In this experiment strong sensitivities to increasing depth and SWE were again demonstrated. To further evaluate the influence of tundra snow variability, detailed characterization of snow stratigraphy was completed within the sensor field of view and compared against collocated backscatter response. These experiments demonstrated Ku-band sensitivity to changes in tundra snow properties observed over short distances. A contrasting homogeneous snowpack showed a reduction in variation of the radar signal in comparison to a highly variable open tundra site. Overall, the results of this thesis support the single frequency Ku-band (17.2 GHz) retrieval of shallow tundra snow properties and encourage further study of X-band interactions to aid in decomposition of the desired snow volume signal.4 month

Physics-based Modeling for High-fidelity Radar Retrievals.

Knowledge of soil moisture on a global scale is crucial for understanding the Earth's water, energy, and carbon cycles. This dissertation is motivated by the need for accurate soil moisture estimates and focuses on the improvement of soil moisture retrieval based on active remote sensing over vegetated areas. It addresses important, but often neglected, aspects in radar imaging: effects related to the ionosphere, multispecies vegetation (heterogeneity at pixel level), and heterogeneity at landscape level. The first contribution is the development of a generalized radar scattering model as an advancement of current radar modeling techniques for vegetated areas at fine-scale pixel level. It consists of realistic representations of multispecies and subsurface soil layer modeling, and includes terrain topography. This modeling improvement allows greater applicability to different land cover types and higher soil moisture retrieval accuracy. Most coarse-scale satellite pixels (km-scale or coarser) contain highly heterogeneous scenes with fine-scale (100 m or finer) variability of soil moisture, soil texture, topography, and vegetation cover. The second contribution is the development of spatial scaling techniques to investigate effects of landscape-level heterogeneity on radar scattering signatures. Using the above radar forward scattering model, which assumes homogeneity over fine scales, tailor-made models are derived for the contribution of fine-scale heterogeneity to the coarse-scale satellite pixel for effective soil moisture retrieval. Finally, the third contribution is the development of a self-contained calibration technique based on an end-to-end radar system model. The model includes ionospheric effects allowing the use of spaceborne radar signals for accurate soil moisture retrieval from lower frequencies, such as L- and P-band. These combined contributions will greatly increase the usability of low-frequency spaceborne radar data for soil moisture retrieval: ionospheric effects are mitigated, landscape level heterogeneity is resolved, and fine-scale scenes are better modeled. These contributions ultimately allow improved fidelity in soil moisture retrieval and are immediately applicable in current missions such as the ongoing AirMOSS mission that observes root-zone soil moisture with a P-band radar at fine-scale resolution (100 m), and NASA's upcoming SMAP spaceborne mission, which will assess surface soil moisture with an L-band radar and radiometer at km-scale resolution (3 km).PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107290/1/mburgin_1.pd