Three groups of variables (Digital Elevation Model [DEM]-derived variables, fieldwork-derived vegetation variables, and satellite imagery-derived vegetation variables) were combined in Classification and Regression Tree (CART) models to determine the utility of vegetation-based variables for mountain permafrost distribution modelling in the southern half of the Yukon Territory. Four variables were measured in the field: canopy openness, vegetation height, organic mat thickness, and dominant species. Using Landsat TM and ETM+ imagery, three variables were calculated: a Normalized Difference Vegetation Index (NDVI), a vegetation classification, and a canopy closure classification. Individual variables were also examined to determine the one most useful for representing vegetation when modelling permafrost presence or absence. Additionally, models for each of five study areas spread across 5° of latitude were compared to examine the transferability of each variable. The addition of vegetation variables to the CART models created with DEM-derived variables resulted in only a minimal increase in the overall accuracy. Dominant species proved to be the most useful variable, but the relationship between permafrost and each species differed among study areas. Only black spruce (Picea mariana) was consistently classified as permafrost probable and lodgepole pine (Pinus contorta var. latifolia) and trembling aspen (Populus tremuloides) were classified as permafrost improbable over all study areas. These results indicate that models of permafrost distribution across large areas are not likely to be enriched sufficiently by the inclusion of vegetation variables while models covering smaller areas may benefit from the inclusion of vegetation variables. The CART models tended to show a high accuracy in the prediction of areas with no permafrost which could be useful for the purposes of infrastructure development. CART models have not previously been used in permafrost modelling and the high accuracies they produced may indicate their utility for modelling the complex relationships among the variables affecting permafrost.

<p> Light Detection and Ranging (LiDAR) technology combined with high-resolution differential Global Positioning Systems (dGPS) provide the ability to measure coastal elevation with high precision. This study investigates the use of LiDAR data and GIS to conduct time-series analyses of coastal sediment volume shifts during the 2006-2007 El Ni&ntilde;o winter, Summer of 2007 and following 2007-2008 La Ni&ntilde;a winter in the Oceanside Littoral Cell (OLC). The OLC, located in Southern California, spans from Dana Point to La Jolla and includes over 84 km of coastline. The ability to quantify sediment volume changes contributes to the scientific understanding of the role El Ni&ntilde;o storms play in the OLC sand budget. This study provides a method to analyze LiDAR data to evaluate coastal geomorphologic changes over time. Additionally, identifying specific areas of coastal beach erosion associated with historical El Ni&ntilde;o events can aid beach managers, planners, and scientists in protecting the valuable coastline. LiDAR datasets were prepared and formatted which included ground classifying millions of elevation points. Formatted datasets were inputted into an Empirical Bayesian Kriging (EBK) model, creating high-resolution, 1-meter grid cell, Digital Elevation Models (DEMs). The EBK model also incorporated uncertainty into the workflow by producing prediction error surfaces. LiDAR-derived DEMs were used to calculate sediment volume changes through a technique called DEM differencing. Results were visualized through a series of maps and tables. Overall results show that there was a higher rate of beach sediment erosion during the 2006-2007 El Ni&ntilde;o winter than the 2007-2008 La Ni&ntilde;a winter. Sediment accretion was evident during the intermediary Summer of 2007. Future applications of this study include incorporating bathymetric datasets to understand near-shore sediment transport, evaluating sediment contribution through cliff erosion, and conducting decadal scale studies to evaluate long-term trends with sea level rise scenarios. </p>

This research examines the use of remote sensing techniques to quantify rill erosion in two agricultural fields in the Lower Fraser Valley. Soil erosion during the winter is particularly problematic in some of the sloping soils developed from loess over glacio-marine parent materials. New techniques are needed to quantify rill erosion on a timely basis, and this research focuses on measuring the extent and rate of rill erosion from field and aerial photograph measurements. A model which used rill measurements as input, was used to determine the rill plan areas, rill volumes, and thus rill erosion rates in the test area. Using field rillometer measurements of rills as input into the model resulted in a soil loss estimate of 49m³ /ha/yr or 38.4 t/ha/yr for the test site. This soil loss estimate is deemed to be more reliable than erosion plot and Universal Soil Loss Equation estimates of soil loss for the test area. The rill volume and plan area of three main rills, using three different rill measurement methods for input into the model, were compared. Using field measuring tape measurements of rills as input into the model, resulted in a soil loss estimate which was 16 % greater than the estimate from rillometer measurements. Using photo rill width measurements and an estimation of rill depths and bottom widths from field data as model input, resulted in a soil loss estimate which was 22 % less than the estimate from rillometer measurements. Spectral reflection measurements made in rill, interrill and depositional areas were found to be significantly different, confirming that rill erosion could be assessed in a quantitative manner using digital image analysis techniques. The spectral separation was largely due to differences in organic matter, surface roughness and imaging geometry. The latter is of particular importance in creating darker shadowed rill sides opposite bright sun-facing rill sides within a single rill. A maximum likelihood classifier, used as part of the computer based image analysis, determined the rill plan area for a sample area to be 9 % less than the rill plan area obtained from the model using rillometer input. This indicates the potential of digital analysis to quickly determine the plan area of larger rills. Digital elevation and moisture content data confirmed that the topographic shape of the field is important in determining the spatial pattern of rill formation. The combination of such data with image analysis and geographic information systems (GIS) have great potential in the timely quantification of erosion in the future. / Land and Food Systems, Faculty of / Graduate

The verification of the Electrically Scanned Thinned Array Radiometer (ESTAR) sensor for remote sensing of soil moisture is presented, and its ability to measure ocean salinity is examined. The research and development that led to verification are presented, beginning with the development of a linearly polarized thinned array, and continuing with the reconstruction of complex correlators, calibration signal distribution, and instrument packaging. Experimental results from two airborne soil moisture campaigns are presented: the first serves to quantitatively verify ESTAR soil moisture capability by comparison with an accepted model and by comparison with another operational sensor; the second demonstrates qualitatively the continuing utility of ESTAR for soil moisture under a variety of soil conditions. Salinity data are presented that suggest an ability to resolve changes in ocean salinity. As the second soil moisture experiment and the salinity experiment are quite recent, full analysis is deferred until more complete in situ data become available. Practical comments on ESTAR experimentation are included in the appendices.

The Turbulent Eddy Profiler (TEP) developed at the University of Massachusetts Microwave Remote Sensing Laboratory (MIRSL) provides three dimensional fine-scale imagery of the intensity of clear-air backscatter and motion of the air with 30 meter resolution between 200 m and 2.0 km altitude. This dissertation presents the design and operation of the updated TEP system deployed in Leon, Kansas during CASES'99 experiment. Both Doppler Beam Swinging (DBS) techniques and Spaced Antenna (SA) techniques for estimating horizontal winds were applied to TEP data collected during CASES'99 experiment. This dissertation compares the results from both techniques with the simultaneous in situ Tethered Lifting System (TLS) data. Good agreement between both methods is observed at intermediate altitudes, however, DBS appears to be preferable to SA at higher altitudes where SNR is low; while SA appears to perform better at the low altitudes, where ground clutter competes with the clear-air echo.

CDOM (chromophoric dissolved organic matter) plays an important role in determining underwater light field and aquatic photochemical and biological processes. Knowing CDOM properties, origin, sink, content, and distribution is able to provide us not only a useful approach to evaluate, but also a new perspective to understand water quality, carbon cycle, as well as the climate change. Remote sensing inversion of CDOM bears the potential capability to assess CDOM at large scale, but it has not been fully investigated yet. Particularly, the previous approaches cannot meet the accuracy and spatial resolution requirement for analyzing complex waters in estuarine and coastal regions. Therefore, a new scheme, which combines a newly developed inversion algorithm and hyperspectral remote sensing, is proposed to solve problems encountered in CDOM evaluation. This research covers three study sites, in the estuarine and coastal regions of the Mississippi River, Hudson River, and Neponset River. Very high resolution in situ data were collected in these sites and EO-1 Hyperion satellite images were also acquired accordingly. Based on a quasi-analytical algorithm (QAA), a QAA-CDOM algorithm was developed, by which CDOM absorption coefficient ag(440) is separated from adg(440)(total absorption coefficient of CDOM and non-algal particles). Some QAA's parameters and functions were also optimized, using available datasets (in situ, IOCCG, and NOMAD). Result validation in the Atchafalaya plume has proved that QAA-CDOM is capable of estimating ag(440) in excellent accuracy (RMSE=0.11 m−1 and R2=0.73 in the Atchafalaya River plume region). More importantly, applying QAA-CDOM to other locations, including the Mississippi River, Amazon River, and Moreton Bay, also derived very reasonable and accurate ag(440), covering a wide range from 0.01 to 15 m −1. This confirms that our method is applicable to a wide range of estuarine regions. The uncertainties involved in CDOM inversion were also analyzed, aiming to know the origin, magnitude, and propagation of uncertainty in different inversion phases. This work strongly indicates that the proposed scheme, QAA-CDOM hyperspectral remote sensing inversion, is robust and reliable to quantify CDOM's concentration, distribution and dynamic for diverse waters, and hence can be applied to other regions.

Aperture synthesis is applied to passive microwave remote sensing of the earth in an effort to attain high resolution images at low microwave frequencies. An L-band (1.4 GHz) synthetic aperture radiometer, dubbed the Electronically Scanned Thinned Array Radiometer, is tested and calibrated. The instrument is modeled after radio telescopes, and utilizes a thinned array of correlation interferometers to measure the Fourier Transform of the Brightness temperature image. The antenna hardware of such an array is reduced by comparison with real aperture antenna systems, which renders this technique relevant to future spaceborne remote sensing applications that require high resolution. In particular, it is the scientific applications at L-band, including the spaceborne remote sensing of soil moisture and ocean salinity, which have motivated this research. Aperture synthesis concepts are developed and applied to the theoretical ESTAR system in chapter II. Chapter II also includes a description of the prototype which was designed constructed at the University of Massachusetts. Practical calibration algorithms are developed in chapter III, and the synthesis technique is refined in chapter IV to reduce side lobes. Chapter V presents the first known images by this class of remote sensing radiometer, and the concluding chapter suggests avenues for future research.

Polymer electrolytes, ionic monomers catenated into a macromolecule, have received a considerable attention in the past decade as they combine the mechanical benefits of flexible chain with the ionic properties of liquid electrolytes. For this reason, they have been widely accepted as potential ion conducting membrane candidates for electrolyzers, energy storage devices, and desalination applications. In efforts to improve the efficiency of polymer electrolyte separators a block copolymer paradigm has been employed. This material’s strategy allows for a spatial separation of the components that control the mechanical and electrochemical properties and thus enables independent engineering of each. Charge – neutral block copolymers (CN-BCPs), a diblock copolymer containing a polyelectrolyte block, attempt to leverage this paradigm, however, to date, the impact ions have on the CN-BCP self-assembly is still an open question. In this dissertation, we are devoted to uncovering the fundamental impact of ionic interactions on CN-BCP self-assembly in bulk and thin-films. First, we survey the literature and compile a list of thoroughly investigated CN-BCPs (derived from imidazolium, quaternary ammonium, and phosphonium motifs) with known dielectric properties. The ionic interaction strength for each CN-BCP was determine using the polyelectrolyte block’s static dielectric constant (ε_r) and the definition of the Bjerrum length (l_B=e^2⁄(4πε_0 ε_r k_b T)). The CN-BCPs studied in the literature, copolymers containing polyelectrolytes blocks with a high ε_r, display a morphology diagram akin to what is expected from the traditional block copolymer self-assembly. However, using a suite of experiment characterization techniques we show that CN-BCPs that contain a polyelectrolyte block with a low static dielectric constant (ε_r=2.5) produce an asymmetric morphology diagram. In this case, we find morphologies that would assemble the polyelectrolyte block into a discrete phase are suppressed if not completely absent. To explain this usual result, we invoke a simple free energy argument, geometric analysis, and a packing parameter model derived from small molecule surfactant principles to rationalize the asymmetry in the morphology diagram on a basis of long-range ionic correlations. Utilizing the packing parameter model we were able to quantitively capture the morphology diagrams of all known CN-BCPs using a single interaction energy parameter. Next, we explore the impact of film thickness on CN-BCP self-assembly via solvent vapor annealing thin-films. A complimentary CN-BCP morphology diagram is constructed for a constant film thickness (h=40 nm) and compared to the bulk phase behavior. Similar to the bulk morphology mapping, we found an asymmetric thin-film morphology diagram with only a singular ordered morphology – cylinders. The influences of film confinement are discussed and utilized to reversibly switch the CN-BCP domain orientation on demand. Finally, we use in-situ grazing incidence small angle x-ray scattering to explore the CN-BCP thin-film structural evolution during the solvent vapor annealing process. We find quantitively different processing pathways when nonselective or selective solvents are used to vapor anneal CN-BCPs. A wide range of annealing solvents spanning a ε_r=4.8-32.7 range was chosen to vapor anneal CN-BCP thin films and a relationship between CN-BCP periodicity (d) and ε_r was determined. We find d~1⁄√ε relationship suggesting the CN-BCP periodicity can be engineer by choice of annealing solvent. Additionally, in this dissertation, we explore the broader impact of morphology on the ion transport through polymer electrolyte membranes. In this vein, we propose structure – property relationships that will enable a rational design of single-ion conducting separators. Using in-house electrochemical techniques, nanoindentation, and gravimetric analysis we explore the relationship between ionic selectivity, quantified through the counterion transference number (t_c^m), the ionic conductivity (κ), and the separator hardness with respect to separator water volume fraction ( ϕ_(H_2 O)). We find t_c^m increases with increasing separator swollen-state charge density which is consistent with a donnan repulsion perspective. Additionally, as ϕ_(H_2 O) increases we find κ increases by orders of magnitude indicting that hydration plays an intimate role in improving ion diffusion in polymer electrolytes. Finally, we present a summary of the permselectivity, Ψ^m=(〖(t〗_c^m-t_c^aqu))⁄((1-t_c^aqu)) , where t_c^aquis equivalent to the aqueous transference number, to κ for a series of polymer electrolytes characterized in literature. We find that separators derived from polymers with rigid backbones (e.g. poly(phenyl sulfone) and poly(2,6-dimethyl-1,4-phenylene oxide)) tend to have a small tradeoff between Ψ^m and κ yet cannot access ideal counterion selectivity (Ψ^m=1) when κ→0. As the backbone flexibility increases the Ψ^m- κ tradeoff is more dramatic yet a Ψ^m=1 when κ→0 is recovered suggesting the importance of molecular packing in this regime. We thus conclude that designing separators with an ideal Ψ^m- κ relationship will require a simultaneous manipulation of molecular architecture, separator hydration state, and morphology.

The measurements from Microwave Sounding Unit (MSU) and Advanced Microwave Sounding Unit-A (AMSU-A) have been extensively used for atmospheric temperature trend study during last several decades. The existences of inter-sensor biases and orbital drift, orbital differences among different satellites are two major challenges for climate study using long-term time series of satellite measurements. In this study, the impacts of orbital drift and orbital differences of satellites on AMSU-A derived temperature trends over Amazon rainforest are investigated. The AMSU-A near-nadir observations from NOAA-15, NOAA-18, NOAA-19, and MetOp-A during 1998 - 2014 are employed. The double difference method is firstly applied to obtain the estimates of inter-sensor biases for each paired AMSU-A instruments, in which NOAA-18 is used as a reference satellite. The inter-calibrated observations from the four satellites mentioned above are used to calculate monthly mean diurnal cycles of brightness temperature for each of the 15 AMSU-A channels. The diurnal correction method is then applied to all AMSU-A data using the estimated diurnal-cycle variations in order to obtain corrected data valid at the same local time. Finally, it is shown that the inter-sensor bias correction and diurnal correction have significant impacts on the AMSU-A derived long-term atmospheric temperature trends. / A Thesis submitted to the Department of Earth, Oceanic and Atmospheric Sciences in partial fulfillment of the requirements for the degree of Master of Science. / Spring Semester, 2015. / February 26, 2015. / Advanced Microwave Sounding Unit-A, climate trend, diurnal correction, inter-sensor bias correction, orbital differences, orbital drift / Includes bibliographical references. / Ming Cai, Professor Directing Thesis; Peter S. Ray, Committee Member; Zhaohua Wu, Committee Member.

Region called "Sokolovsko" is an area in the Czech Republic in which a coal mining has caused a great interference with the appearance of the landscape. With a subsequent reclamation, the affected areas are recreated into new landscapes, however on the research base, the non-interference approach is applied in order to follow the principles of a natural succession. This diploma thesis examines the influence of the origin, respectively the relief of the dump area on the intensity of the spontaneous vegetation growth, within the example of the Velká podkrušnohorská spoil heap, based on the data collected by remote sensing techniques. The vegetation indices NDVI and SAVI were used to reveal the intensity of the vegetation cover on the area of the interest. It is clear from the results that the vegetation growth is considerably faster in the areas with the original, wavy relief. It was also found that the vegetation growth of the non reclaimed area of Velká podkrušnohorská spoil heap in the parts of which the relief was settled at the time of the origin differs from the non reclaimed area of which the relief was left in the original wavy surface and later over layered with a new material. Finally it was made a comparison between the non reclaimed part of the Velká podkrušnohorská spoil heap whose...