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<p> A common method to identify or model the dominant directional reflective properties of a surface is the bidirectional reflectance distribution function (BRDF). BRDF describes the angular behavior by which light interacts with surfaces. Remote sensing technology has advanced to the stage where hyperspectral sensors, with hundreds of separate wavelength bands, are fairly common. This necessitates examining BRDF in the hyperspectral regime, which implies examining the directional reflective properties of hundreds of narrowly spaced wavelength bands. </p><p> In this dissertation I hypothesize that beach sand BRDF is wavelength dependent. Principal component analysis (PCA) and correlation matrix analysis of in situ measurements were used to test whether the spectral variability in the visible, near-infrared and shortwave directional reflectance factor of beach sands with and without freshwater surface films are wavelength dependent. The hyperspectral BRDF of beach sands exhibit weak spectral variability, the majority of which can be described with three to four broad spectral bands. These occur in the absence of a water layer on top of the sand in three wavelength ranges of 350-450 nm, 700-1350 nm, and 1450-2400 nm. When observing sheet flow on sand, a thin layer of water enhances reflectance in the specular direction at all wavelengths, and that spectral variability may be described using four spectral band regions of 350-450 nm, 500-950 nm, 950-1350 nm, and 1450-2400 nm. Spectral variations are more evident in sand surfaces of greater visual roughness than in smooth surfaces, regardless of sheetflow.</p>

<p> This dissertation presents new studies of waves and turbulence in the Arctic middle atmosphere. The study has a primary focus on wintertime conditions when the large-scale circulation of the middle atmosphere is disrupted by the breaking of planetary waves associated with sudden stratospheric warming (SSW) events. We used ongoing Rayleigh lidar measurements of density and temperature to conduct a multi-year study of gravity waves in the upper stratosphere-lower mesosphere (USLM) over Poker Flat Research Range (PFRR) at Chatanika, Alaska. We analyzed the night-to-night gravity wave activity in terms of the wind structure and the ageostrophy. We find that the weak winds during disturbed conditions block the vertical propagation of gravity waves into the mesosphere. The gravity wave activity is correlated with the altitudes where the winds are weakest. During periods of weak winds we find little correlation with ageostrophy. However, during periods of stronger winds we find the USLM gravity wave activity is correlated with the ageostrophy in the upper troposphere indicating that ageostrophy in this region is a source of the gravity waves. Inter-annually we find the wintertime gravity wave activity is correlated with the level of disturbance of the middle atmosphere, being reduced in those winters with a higher level of disturbance and weaker winds. We used rocket-borne ion gauges to measure turbulence in the wintertime middle atmosphere while documenting the larger meteorological context from Rayleigh lidar and satellites. This investigation of turbulence was called the Mesosphere-Lower Thermosphere Turbulence Experiment (MTeX). During MTeX we found a highly disturbed atmosphere associated with an SSW where winds were weak and gravity wave activity was low. We found low levels of turbulence in the upper mesosphere. The turbulence was primarily found in regions of convective instability in the topside of mesospheric inversion layers (MILs). The strongest and most persist turbulence was found in a MIL that is associated with the breaking of a monochromatic gravity wave. These MTeX observations indicate that turbulence is generated by gravity wave breaking as opposed to gravity wave saturation. These MTeX findings of low levels of turbulence are consistent with recent model studies of vertical transport during SSWs and support the view that eddy transport is not a dominant transport mechanism during SSWs.</p>

<p> In this thesis, we aim to systematically understand the relationship between cloud spatial structure and its radiation imprints, i.e., three-dimensional (3D) cloud effects, with the ultimate goal of deriving accurate radiative energy budget estimates from space, aircraft, or ground-based observations under spatially inhomogeneous conditions. By studying the full spectral information in the measured and modeled shortwave radiation fields of heterogeneous cloud scenes sampled during aircraft field experiments, we find evidence that cloud spatial structure reveals itself through spectral signatures in the associated irradiance and radiance fields in the near-ultraviolet and visible spectral range.</p><p> The spectral signature of 3D cloud effects in irradiances is apparent as a domain- wide, consistent correlation between the magnitude and spectral dependence of net horizontal photon transport. The physical mechanism of this phenomenon is molecular scattering in conjunction with cloud heterogeneity. A simple parameterization with a single parameter &epsiv; is developed, which holds for individual pixels and the domain as a whole. We then investigate the impact of scene parameters on the discovered correlation and find that it is upheld for a wide range of scene conditions, although the value of &epsiv; varies from scene to scene.</p><p> The spectral signature of 3D cloud effects in radiances manifests itself as a distinct relationship between the magnitude and spectral dependence of reflectance, which cannot be reproduced in the one-dimensional (1D) radiative transfer framework. Using the spectral signature in radiances and irradiances, it is possible to infer information on net horizontal photon transport from spectral radiance perturbations on the basis of pixel populations in sub-domains of a cloud scene.</p><p> We show that two different biases need to be considered when attempting radiative closure between measured and modeled irradiance fields below inhomogeneous cloud fields: the remote sensing bias (affecting cloud radiances and thus retrieved properties of the inhomogeneous scene) and the irradiance bias (ignoring 3D effects in the calculation of irradiance fields from imagery-based cloud retrievals). The newly established relationships between spatial and spectral structure lay the foundation for first-order corrections for these 3D biases within a 1D framework, once the correlations are explored on a more statistical basis.</p>

Populations of the least killifish, Heterandria formosa are found in a wide variety of habitats, including habitats that differ widely in average temperature and in range of seasonal temperatures. To determine whether this ability to exist in thermally different sites is owing to phenotypic plasticity or to population differentiation I raised fish from a spring site and a pond site under common laboratory conditions. Fish were raised at one of two temperatures during gestation and at one of two temperatures from birth to sexual maturity. Gestation temperature, rearing temperature, population of origin, and gender had complex, interacting effects on critical thermal maximum and minimum at sexual maturity, on offspring survival, and on time to maturity. In particular, the populations were strongly differentiated for offspring survival and time to maturity, although the magnitude of the differences depended on the environment. Females performed better than males when genders differed. / H. formosa also exhibit superfetation, the presence of embryos in different developmental stages in the ovary at one time. There have been few comparative studies of interspecific variation in superfetation, and there have been no surveys of population variation in reproductive traits within a superfetating species. In this study I followed seasonal changes in reproductive parameters of four populations of H. formosa for all or part of 4 years. / The four populations differed in breeding phenology, level of superfetation, total volume of embryos carried, and brood size. This variation does not correspond to either general habitat similarities among the populations (ponds versus rivers), or to habitat stability. I also discovered that first, females must hold back some same-stage embryos while advancing others and second, that size of females, as measured by standard length, clearly influences the total number of embryos, brood size, and number of embryos carried in each stage. Yet despite this relationship between body size and embryo capacity, brood size is not constrained by space available for late-stage embryos. / Source: Dissertation Abstracts International, Volume: 51-02, Section: B, page: 0549. / Major Professor: Joseph Travis. / Thesis (Ph.D.)--The Florida State University, 1989.

<p> This study implemented LiDAR (Light Detection and Ranging) remote sensing technology and applied ITD (Individual Tree Detection) methods as an approach to estimate some essential tree variables, such as DBH (Diameter at Breast Height), height, volume, and biomass for Ford Forest Research Center in Upper Peninsula, Michigan. There were 34 deciduous (1 bigtooth aspen, 9 red oaks, 20 sugar maples, 2 white birches, and 2 yellow birches) and 17 coniferous (2 eastern hemlocks, 11 red pines, and 4 white pines) subject tree species. There were two different available LiDAR datasets from the same area that were collected in 2011 and 2017. Height measurements were done at 96% and 97% accuracy for hardwood and softwood tree species, respectively. </p><p> Several other tree variables derived from LiDAR point cloud were used to estimate DBH by using regression analysis for both 2017 and 2011 datasets. Estimation equations were tested on the other dataset. The best-fitted formula was 2017&rsquo;s, with 0.55 adjusted R&sup2; and less than 0.0001 p-values on 2017 LiDAR data while 0.42 adjusted R&sup2; and less than 0.0001 p-values on 2011&rsquo;s dataset. Some additional analysis that includes calculating PRMSE (Predicted Root Mean Square Error), BIAS (Mean Error), and MAD (Mean Absolute Difference) have been applied. The equation that was generated by using data from 2017 has &ndash;0.57 BIAS for Hardwood and 1.13 BIAS for softwood. That result indicates that the equation has &ndash;0.57 centimeters (cm) estimation error for hardwood and 1.13 cm for softwood on DBH estimations. </p><p>

<p> In California, natural vegetation is experiencing an increasing amount of stress due to prolonged droughts, wildfires, insect infestation, and disease. Remote sensing technologies provide a means for monitoring plant species presence and function temporally across landscapes. In this his dissertation, I used hyperspectral visible shortwave infrared (VSWIR), hyperspectral thermal (TIR), and hyperspectral VSWIR + broadband TIR imagery to derive key observations of plant species across a gradient of environmental conditions and time frames. In Chapter 2, I classified plant species using hyperspectral VSWIR imagery from 2013&ndash;2015 spring, summer, and fall. Plant species maps had the highest classification accuracy using spectra from a single date (mean kappa 0.80&ndash;0.86). The inclusion of spectra from other dates decreased accuracy (mean kappa 0.78&ndash;0.83). Leave-one-out analysis emphasized the need to have spectra from the image date in the classification training, otherwise classification accuracy dropped significantly (mean kappa 0.31&ndash;0.73). In Chapter 3, I used hyperspectral TIR imagery to determine the extent that high precision spectral emissivity and canopy temperature can be exploited for vegetation research at the canopy level. I found that plant species show distinct spectral separation at the leaf level, but separability among species is lost at the canopy level. However, species&rsquo; canopy temperatures exhibited different distributions among dates and species. Variability in canopy temperatures was largely explained by LiDAR derived canopy structural attributes (e.g. canopy density) and the surrounding environment (e.g. presence of pavement). In Chapter 4, I used combined hyperspectral VSWIR and broadband TIR imagery to monitor plant stress during California&rsquo;s 2013&ndash;2015 severe drought. The temperature condition index (TCI) was calculated to measure plant stress by using plant species&rsquo; surface minus air temperature distributions across dates. Plant stress was not evenly distributed across the landscape or time with lower elevation open shrub/meadows, showing the largest amount of stress in June 2014, and August 2015 imagery. Plant stress spatial variability across the study area was related to a slope&rsquo;s aspect with highly stressed plants located on south or south-southwest facing slopes. Overall, this dissertation quantifies the ability to temporally study plant species using hyperspectral VSWIR, hyperspectral TIR, and combined VSWIR+TIR imagery. This analysis supports a range of current and planned missions including Surface Biology and Geology (SBG), Environmental Mapping and Analysis Program (EnMAP), National Ecological Observatory Network (NEON), Hyperspectral Thermal Emission Spectrometer (HyTES), and ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS). </p><p>

Landsat images are analyzed to investigate the causes of turbidity variations in lower Chesapeake Bay surface water. Visual analysis and image enhancement are used in association with optical film density data obtained along selected Bay transects. The optical density data of all images, inversely related to surface turbidity, are used to produce residual turbidity profiles showing turbidity above and below average conditions. meteorological conditions have Images with similar tidal or their residual optical density data averaged to identify probable causes of above average turbidity levels. Freshwater discharge does not directly contribute suspended sediment to Chesapeake Bay, except from the Potomac River during times of high freshwater flow. Much of the detected surface turbidity is associated with resuspension by tidal currents. Flood currents cause higher surface turbidity along the Eastern Shore frorn the Bay mouth to off the Rappahannock River mouth. High ebb-related turbidity occurs north of the Rappahannock River and in the western half of Chesapeake Bay south of Wolf Trap Shoals. Currents during spring tide produce higher surface turbidity south of the Rappahannock River than currents during other portions of the lunar cycle. Strong wind causes greater surface turbidity than low wind except when wind direction opposes tidal currents. A large fetch (20 km) parallel to wind direction results in higher surface turbidity downwind. A correlation exists between surface turbidity and water depth. Surface turbidity is lower in deeper water due to the weaker effect of tidal and wind resuspension. Resuspension of bottom sediment affects surface in waters as deep as 40 feet.

Elevated water levels and large waves during storms cause beach erosion, overwash, and coastal flooding, particularly along barrier island coastlines. While predictions of storm tracks have greatly improved over the last decade, predictions of maximum water levels and variations in the extent of damage along a coastline need improvement. In particular, physics based models still cannot explain why some regions along a relatively straight coastline may experience significant erosion and overwash during a storm, while nearby locations remain seemingly unchanged. Correct predictions of both the timing of erosion and variations in the magnitude of erosion along the coast will be useful to both emergency managers and homeowners preparing for an approaching storm. Unfortunately, research on the impact of a storm to the beach has mainly been derived from "pre" and "post" storm surveys of beach topography and nearshore bathymetry during calm conditions. This has created a lack of data during storms from which to ground-truth model predictions and test hypotheses that explain variations in erosion along a coastline. We have developed Coastal Lidar and Radar Imaging System (CLARIS), a mobile system that combines a terrestrial scanning laser and an X-band marine radar system using precise motion and location information. CLARIS can operate during storms, measuring beach topography, nearshore bathymetry (from radar-derived wave speed measurements), surf-zone wave parameters, and maximum water levels remotely. In this dissertation, we present details on the development, design, and testing of CLARIS and then use CLARIS to observe a 10 km section of coastline in Kitty Hawk and Kill Devil Hills on the Outer Banks of North Carolina every 12 hours during a Nor'Easter (peak wave height in 8 m of water depth = 3.4 m). High decadal rates of shoreline change as well as heightened erosion during storms have previously been documented to occur within the field site. In addition, complex bathymetric features that traverse the surf-zone into the nearshore are present along the southern six kilometers of the field site. In addition to the CLARIS observations, we model wave propagation over the complex nearshore bathymetry for the same storm event. Data reveal that the complex nearshore bathymetry is mirrored by kilometer scale undulations in the shoreline, and that both morphologies persist during storms, contrary to common observations of shoreline and surf-zone linearization by large storm waves. We hypothesize that wave refraction over the complex nearshore bathymetry forces flow patterns which may enhance or stabilize the shoreline and surf-zone morphology during storms. In addition, our semi-daily surveys of the beach indicate that spatial and temporal patterns of erosion are strongly correlated to the steepness of the waves. Along more than half the study site, fifty percent or more of the erosion that occurred during the first 12 hours of the storm was recovered within 24 hours of the peak of the storm as waves remained large (>2.5 m), but transitioned to long period swell. In addition, spatial variations in the amount of beach volume change during the building portion of the storm were strongly correlated with observed wave dissipation within the inner surf zone, as opposed to predicted inundation elevations or alongshore variations in wave height.

The Gulf of California and its surrounding land areas provide a classic example of recently rifted continental lithosphere. The recent tectonic history of eastern Baja California has been dominated by oblique rifting that began at ~12 Ma. Thus, extensional tectonics, bedrock lithology, long-term climatic changes, and evolving surface processes have controlled the tectono-geomorphological evolution of the eastern part of the peninsula since that time. In this study, digital elevation data from the Shuttle Radar Topography Mission (SRTM) from Baja California were corrected and enhanced by replacing artifacts with real values that were derived using a series of geostatistical techniques. The next step was to generate accurate thematic geologic maps with high resolution (15-m) for the entire eastern coast of Baja California. The main approach that we used to clearly represent all the lithological units in the investigated area was objectoriented classification based on fuzzy logic theory. The area of study was divided into twenty-two blocks; each was classified independently on the basis of its own defined membership function. Overall accuracies were 89.6 %, indicating that this approach was highly recommended over the most conventional classification techniques. The third step of this study was to assess the factors that affected the geomorphologic development along the eastern side of Baja California, where thirty-four drainage basins were extracted from a 15-m-resolution absolute digital elevation model (DEM). Thirty morphometric parameters were extracted; these parameters were then reduced using principal component analysis (PCA). Cluster analysis classification defined four major groups of basins. We extracted stream length-gradient indices, which highlight the differential rock uplift that has occurred along fault escarpments bounding the basins. Also, steepness and concavity indices were extracted for bedrock channels within the thirty-four drainage basins. The results were highly correlated with stream length-gradient indices for each basin. Nine basins, exhibiting steepness index values greater than 0.07, indicated a strong tectonic signature and possible higher uplift rates in these basins. Further, our results indicated that drainage basins in the eastern rift province of Baja California could be classified according to the dominant geomorphologic controlling factors (i.e., faultcontrolled, lithology-controlled, or hybrid basins).