Browsing by Subject "Remote sensing"
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Item An analysis of radiometric correction effects on Landsat thematic mapper imagery(1991-05) Waits, David Allan; Fish, Ernest B.; Wanjura, Donald F.; Wester, David B.; Davidson, Claud M.; Templer, Otis W.Land-use classifications and spectral indices are commonly created from raw radiance satellite data. These data are known to be distorted due to sensor instrumentation errors and atmospheric contributions. The overall objective of this study was to evaluate different radiometric corrections of Thematic Mapper (TM) data on land-use classification results and the derivation of spectral indices. A Landsat-4 TM digital image of a diverse agricultural area in the High Plains region of eastern New Mexico was the primary data source. Ancillary data incorporated into the study included: extensive field verification data for a study area of approximately 1,820 square kilometers; ground-based radiometer derived spectral response data for commonly grown agricultural crops; and meteorological data used as input parameters for atmospheric modeling using the Lowtran-7 atmospheric correction program. Four different geometrically corrected image data sets were analyzed. The first was raw radiance data in radiometrically uncorrected form. The other three images were radiometrically corrected transforms created using procedures that adjusted the raw data for radiometric calibration and atmospheric correction. All four images were classified in terms of land-use using identical training fields. Supervised classifications were developed using ground truth data, and quantitative analyses were performed on all resulting classifications. Ground-based spectral response data for various land-use types were compared qualitatively to response data derived from the raw and radiometrically corrected image data for the same land-use types. Four spectral index models were applied to each of the four image data sets. The derived spectral indices were transforms that emphasized the quantitative differences among image data sets. The results showed no material differences in classification accuracy among the four image data sets. Thus, it does not appear necessary to perform radiometric corrections on raw radiance data to improve classification accuracy. Spectra derived from atmospherically corrected image data sets more closely approximated "true" spectral response patterns as obtained by a ground-based radiometer. Each of the various components of the radiometric correction process was found to contribute significantly to the derivation of spectral index values.Item Development of onboard digital elevation and relief databases for the advanced topographic laser altimeter system(2013-12) Leigh, Holly Wallis; Schutz, Bob E.; Magruder, Lori Adrian, 1971-The Ice, Cloud, and land Satellite-2 (ICESat-2) is planned to launch in 2016 carrying the Advanced Topographic Laser Altimeter System (ATLAS). ATLAS will be the first space-based photon-counting laser altimeter to be put into operation, and is tasked with observing the Earth’s ice sheets, sea ice, and vegetation. The environment in which ATLAS will be operating is expected to introduce a significant amount of noise into the received signal; this necessitates that a set of onboard Receiver Algorithms be developed to reduce the data volume and data rate to acceptable levels while still transmitting the relevant ranging data. The algorithms make use of signal processing techniques, along with three databases, the Digital Elevation Model (DEM), the Digital Relief Map (DRM), and the Surface Reference Mask (SRM), to find the signal and determine the appropriate dynamic range of vertical data surrounding the surface for downlink. The focus of this study is the development of the DEM and DRM databases. A number of elevation data sets are examined for use as inputs for the databases. No global data sets of sufficient quality and resolution are available for the development of the project, so best-available regional elevation data sets were selected instead. Software was developed in MATLAB to produce the DEM and DRM data bases from the input data sets. A method for calculating relief from a gridded elevation data set along the flight path of a satellite was developed for the generation of relief maps used to create the DRM. Global DEM and DRM databases were produced by mosaicking individual DEM and DRM tiles from each input data set into global grids. A technique was developed to determine the accuracy of the DRM by using ICESat ground elevations to evaluate the accuracy of an input elevation data set. By comparing values of DRM accuracy to values of DRM relief, estimates of DRM accuracy as a function of relief magnitude were determined and used to define values of DRM padding in the receiver algorithm.Item Dissolved organic matter in major rivers across the Pan-Arctic from remote sensing(2016-05) Griffin, Claire Genevieve; McClelland, James W.; Frey, Karen E; Gardner, Wayne S; Liu, Zhanfei; Shank, Gerald CClimate-driven changes in Arctic hydrology and biogeochemistry are impacting transport of water and water-borne material from land to ocean. This includes massive amounts of organic matter that are mobilized and exported from the pan-Arctic watershed via rivers each year. Dissolved organic matter (DOM), an important part of the Arctic carbon cycle, has received growing attention in recent years, yet long-term studies of riverine biogeochemistry remain rare in these remote and logistically challenging regions. Remote sensing of chromophoric dissolved organic matter (CDOM, the portion of the DOM pool that absorbs light), provides a unique opportunity to investigate variations in DOM in major Arctic rivers over multiple decades. CDOM is a useful proxy for dissolved organic carbon (DOC) and is essential to photochemical processes in surface waters. This dissertation presents the development and application of remote sensing regression models across six major Arctic rivers: the Kolyma, Lena, Mackenzie, Ob’, Yenisey and Yukon. Frozen, archival samples of CDOM were used to develop calibration data for remote sensing regressions. Remote sensing methods estimated CDOM with R2 of 85% across all rivers, although individual rivers varied in their predictability in association with sediment loading and hydrology. As with previous studies of Arctic systems, concentrations and export of CDOM and DOC were highest during spring freshet in most of these rivers. Interannual variability in DOM export may be linked to the Arctic Oscillation. Within the Mackenzie, Ob’, and Yenisey rivers, observations of DOM concentration and export were extended back to the 1980s, the first known empirical records of this length for Arctic rivers that span both continents. Although no pan-Arctic trends in CDOM export were detected, there is some evidence of long-term changes in riverine DOM. For example, discharge-specific CDOM concentrations decreased in the Yenisey River and increased in the Ob’ River. Additionally, CDOM concentrations increased over the past ~30 years within the Mackenzie River. This dissertation also includes results from experiments used to quantify the effects of cryopreservation on CDOM analyses, and potential approaches for ameliorating freezing effects. These experiments showed that freezing for preservation introduces some error into CDOM measurements, although these effects vary between river systems. Sonication may improve CDOM measurements in some river systems, but the effects of both cryopreservation and sonication should be quantified on a case-by-case basis. Overall, this dissertation work demonstrates that 1) remote sensing of CDOM is a viable tool for tracking fluvial DOM in the major Arctic rivers, 2) only the Mackenzie River showed significant increases in CDOM concentration from the 1980s to present and 3) long-term changes in discharge-specific CDOM concentrations have occurred in the Yenisey and Ob’ rivers. These long-term trends cannot be definitively linked to climate change, but may be related to effects of warming on permafrost, hydrology, and biogeochemistry within in Arctic watersheds with consequences for carbon cycling on both regional and global scales.Item The effects of vegetation on island geomorphology in the Wax Lake Delta, Louisiana(2014-05) Smith, Brittany Claire; Moffett, Kevan B.; Mohrig, DavidUnderstanding how deltas build and maintain themselves is critical to predicting how they will respond to perturbations such as sea level rise. This is especially an issue of interest in coastal Louisiana, where land loss is exacerbated due to subsidence and decreased sediment supply. Feedbacks between ecology and geomorphology have been well documented in tidal environments, but the role of vegetation in delta morphodynamics is not well understood. This study investigates spatial and temporal correlations between vegetation succession and sediment accumulation at the Wax Lake Delta in Louisiana. I established a 2500 m long transect along the western levee of Pintail Island, capturing the full range of island elevations and the transition from bare sediment to herbaceous plants and trees. Shallow (50-100 cm deep) sediment cores taken along this transect were analyzed for particle size, organic matter content, and bulk density, and dated using ²¹⁰Pb. The resulting sedimentation rates and composition trends over time were compared to remote sensing-based analyses of temporal changes in island topography and flooding frequency derived from historical Landsat images. We found that the topography of Pintail Island has developed from a non-systematic arrangement of elevations to a discrete set of levees and intra-island platforms with distinct vegetation types, designated as high marsh, low marsh, and mudflat habitat. This elevation zonation is consistent with alternative stable state theory as so far applied to tidal salt marsh systems. At all but the youngest sampling site, sediment cores showed a significant decrease in organic matter content and a significant increase in grain size with depth. The total organic matter contribution to vertical growth was not sufficient to account for all the elevation change required to achieve the differentiation from low marsh to high marsh deduced from the time-lapse Landsat imagery analysis. Mineral sediment accumulation rates suggested that elevation growth was accelerating or holding steady over time, in contrast to theory suggesting rates should slow as elevation increases. These results provide an empirical foundation for future mechanistic models linking mineral sedimentation, organic sedimentation, vegetation succession, elevation change, and flood frequency in the delta.Item Estimating high resolution atmospheric phase screens from differential InSAR measurements(2010-05) Yang, Dochul; Buckley, Sean M.; Tapley, Byron D.; Schutz, Bob E.; Lightsey, Glenn; Wilson, Clark R.Atmospheric artifacts superimposed on interferometric synthetic aperture radar (InSAR) measurements have the potential to greatly impede the accurate estimation of deformation signals. The research presented in this dissertation demonstrates a novel InSAR time series algorithm, called HiRAPS algorithm, for effectively estimating high resolution atmospheric phase screens (APS) from differential InSAR measurements. In summary, the HiRAPS algorithm utilizes short time span differential interferograms and rearranges components of existing advanced InSAR techniques to identify a higher density of scatterers used to create the APS. The improved scatterer density allows one to estimate high spatial frequency atmospheric signals not recovered from existing InSAR time series techniques. The HiRAPS algorithm was tested with simulated and actual data, which contain phase contributions from linear and nonlinear deformation, topographic height errors, and atmospheric artifacts. Simulated differential interferograms were generated to have the same spatial and temporal baselines as the actual differential interferograms formed from RADARSAT-1 data over Phoenix, Arizona. The APS superimposed on simulated differential interferograms were then estimated and compared to simulated APS. The root mean square error (RMSE) between the estimated and simulated APS was calculated to qualitatively assess the different values obtained. The RMSE was 0.26 radians when utilizing the HiRAPS algorithm, compared to an RMSE value of 0.39 radians using an implementation of the permanent scatterer (PS) algorithm. The HiRAPS algorithm also showed its applicability for estimating high spatial frequency atmospheric signals for actual data. Sixty-six SAR images, starting from October 5, 2002 and spanning 5 years, were processed for this research. The APS pixel density obtained using the HiRAPS algorithm was 253 pixels per square kilometer, compared to 14 pixels per square kilometer utilizing the PS algorithm. The APS superimposed on the differential interferograms were estimated with both the proposed and PS algorithms. High resolution APS were estimated with the HiRAPS algorithm, whereas only low resolution APS were obtained with the PS algorithm. After estimating and removing estimated APS, the phase stability of APS-free differential interferograms was examined by identifying the permanent scatterers (PS). The final density of identified PS obtained with the HiRAPS algorithm was 453 PS per square kilometer, whereas the density of detected PS using the generic PS algorithm was 381 PS per square kilometer. The maximum difference in the deformation time series between the HiRAPS algorithm and the PS algorithm was less than 6 mm. However, the HiRAPS algorithm resulted in less apparent noise in the time series than the PS algorithm due to the precise estimation of APS.Item Estimation of crop water use for different cropping systems in the Texas High Plains using remote sensing(Texas Tech University, 2007-12) Rajan, Nithya; Maas, Stephan J.; Allen, Vivien G.; Nagihara, Seiichi; Mauget, StevenThe spectral crop coefficient (Ksc) is a novel approach for estimating the water use of field crops. In this study, Ksc is evaluated from remote sensing observations (satellite or aircraft imagery) of the field in question and, thus, is specific to the crop growth characteristics in the field. This approach assumes that the crop is acclimated to its environment and determines crop water use (CWU) based on the product of potential evapotranspiration and remotely sensed crop ground cover (GC). Because the remotely sensed measurements of GC are infrequent over the growing season, these measurements are used in a crop model to simulate values of GC for each day of the growing season, resulting in a crop coefficient curve (known as the spectral crop coefficient – Ksc) that is specific to the field, crop, and growing conditions. The method used for estimating the GC from remote sensing data involves the Perpendicular Vegetation Index (PVI). GC is calculated by dividing the average PVI for a field by the value of PVI for full canopy point. Statistical analysis of estimated and field-measured GC from a large number of fields indicates that the procedure for estimating crop GC from remote sensing imagery is accurate so that, on average, estimates of GC determined using this procedure should be within 6 percent of their true values. The seasonal CWU estimated by this method showed differences in water utilization by individual fields. Comparison of these seasonal CWU values among the fields in the study was effective in showing differences related to year, crop, and irrigation type. Comparing daily values of CWU estimated using the Ksc method and the regular crop coefficient method recommended for crops in the Texas High Plains with actual measurements of evapotranspiration made using the eddy covariance method showed that the Ksc method was consistently more accurate than the regular crop coefficient method.Item Explicitly linking field- and satellite- derived measurements for improved vegetation quantification and disturbance detection(2014-12) Christiansen, Thomas Brandt; Crews, Kelley A.; Miller, Jennifer A; Young, Kenneth RArid and semi-arid ecosystems have been recognized as critical in supporting over one-third of the world's populations, notably those more dependent on the natural resource base for their livelihoods. These systems, and especially savannas within them, are highly vulnerable to predicted fluctuations in climatic change, disturbances, and management regimes. This research posits these areas in a social-ecological system (SES) framework that encompasses human, governance, and recourse units. A challenge in both SES and CHANS (coupled human and natural systems) research is how to explicitly and empirically link the social and the ecological, and further how to extrapolate from sets of case studies to the greater region, supra-system, or SES / CHANS theory and practice. This work leverages Landsat and IKONOS imagery as well as field-based vegetation sampling (structure and species) through the use of IDL (interactive data language) visualizations, both pixel- and object-based classifications, and CART (classification and regression tree) analysis. The longer term goal of this work is to produce a protocol and classification scheme modified from the 1976 Anderson scheme to include both structure and disturbance explicitly in processing, mapping, monitoring, and management. In creating SVCs (Structural Vegetation Categories) built from field data there is strong potential for extracting 3-D data from 2-D imagery once the protocol produces robust results with high enough accuracies. As hypothesized, the object-based classifications produced higher overall accuracy (70.83%), though the pixel-based classification performed better in the detection of woodlands (90.91%). Given the spatial scales of the imagery as compared to the size of the field plots and transect spacing, it is important to remember that when extrapolating to other areas a critical part of spatial scale is extent (not just grain). That is, the inherent clumping of trees versus shrubs may be driving the better performance of pixel-based for woodlands but not so for shrublands. Sensitivity to placement of plots and especially plot sizes across future sites will help explore this question and move SES research into a realm whereby remote sensing and vegetation sampling can provide improved empirical linkages among the subsystems and their feedbacks.Item Forest diversity and conservation in the western Amazon based on tree inventory and remote sensing data(2011-12) Wang, Yung-ho Ophelia; Young, Kenneth R.; Crews, Kelley A.; Miller, Jennifer A.; Sarkar, Sahotra; Pitman, Nigel C.This dissertation contributes to debates in conservation biogeography by examining the spatial heterogeneity of local and regional tree diversity feature using ground and remotely sensed data, and by taking approaches to design a spatially explicit landscape zonation map for future conservation planning in western Amazon, one of the most biodiverse regions on Earth. Fine scale tree diversity and conservation-related studies took place in tropical rainforests in southeastern Ecuador, whereas coarse scale tree diversity research was conducted using data from eastern Ecuador and northern Peru. The lack of species assemblages within three 1-ha tree inventory plots in southeastern Ecuador and the weak correlations with biophysical environment implied that neutral processes may contribute to species diversity. In contrast, differences in species assemblages between plots corresponded to relative geographic locations of the plots, indicating that geographic distance or dispersal limitation may play an important role influencing diversity patterns at a regional scale. Species of high local abundance was found in 1-ha tree inventory plots in western Amazon. Changes in density of locally abundant species between western and eastern plots indicated that some species may have limited distributions. Shifts in species dominance and the significant relationship between floristic variation and geographic distances between plots implied dispersal limitation. Variation in rainfall showed significant relationship with species composition. Therefore, dispersal limitation and precipitation seasonality are potentially the most significant factors that contribute to spatial differences in tree diversity in western Amazon. Characteristics of canopy shadows and palm stem density based on fine-resolution aerial photographs were characterized as exploratory analyses to extract alpha and beta diversity features using remotely sensed data. A zonation map design using multispectral habitat classification and other remote sensing data performed well in its spatial arrangement when potential indigenous land use was integrated. Based on the results of analyses for conservation biogeography, this dissertation concludes that local and regional tree diversity may be influenced by dispersal limitation and seasonality, and that the application of remote sensing for biodiversity conservation is feasible in very species-rich forests.Item Geographic Analysis of Current and Historical Vegetation of East Texas(2017-04-12) Hoffpauir, David R.; Adu-Prah, Samuel; Chapman, Brian R.; Leipnik, Mark; Pascarella, John B.This study uses two sources of secondary data to compare vegetation communities in East Texas and analyze how they have changed in the past eight decades. The first data source is a hand-drawn timber survey map generated by the U.S. Department of Agriculture circa 1935. The second data source is the Texas Parks and Wildlife Department’s Ecological Mapping Systems of Texas (EMS-T) finished in 2014. A third data source is used to crosswalk between the two principal sources. Using digital mapping techniques, classification boundaries of the historic map were digitized creating an overall area of interest. This was used to extract attribute data from the second data source creating a data extent defined by the digitized boundaries of the 1935 map. Although identical, their resulting attribute data contained no mechanism for a data join. The third data source, McMahon’s The Vegetation Types of Texas, Including Cropland provided this attribute bridge. This study found that 2.49% of the overall area has been converted to urban use. This shift in land use underscores an overall rise in population, which, in turn, drives the need for natural resources and conversion of ecosystems to other land uses. For example, 34% of the ’Shortleaf, Loblolly, Hardwood’ classification is now exclusively devoted to timber production. In the ‘Bottomland Hardwood’ classification, reservoirs now account for 13% of its total area. Today only 0.07% of the 1935 longleaf pine extent is exclusively longleaf pine and 56% of areas that once were longleaf pine are now pine plantation. Areas of urban growth have had the greatest impact on the ‘Loblolly, Hardwood’ classification where 10.3% has been converted to urban cover. Invasive species are evident as well. For example, of the ‘Loblolly, Hardwood’ classification, 3.7% is now invasive Chinese Tallow (Triadica sebifera). The resulting analysis allows for comparisons based on “Common Name” attributes, LU/LC value, and associated area values. Beneficially, such comparison allows for general assumptions about environmental impact and provides an analytical mechanism by which to mitigate future loss due to human or natural influences.Item GIS-based multiple scale study of Rio Grande wild turkey habitat in the Edwards Plateau of Texas(Texas A&M University, 2006-10-30) Perotto Baldiviezo, Humberto LauroRio Grande wild turkey (RGWT) abundance in portions of the Edwards Plateau has declined steadily since the late 1970s as compared to other areas of the Edwards Plateau where populations have exhibited no trend. The reasons for this decline remain unclear. Possible factors include changes in habitat, and increased human population. The overall objective of this study was to identify landscape changes and habitat characteristics that affect RGWT populations using spatial analysis and modeling at multiple spatial scales. Specific objectives for this study included the quantification of flood-induced landscape changes between 1972 and 1995 along the Medina River bottomlands and their impact on RGWT habitat, the quantification of landscape characteristics of stable and declining study sites in the Edwards Plateau, and the development and evaluation of a GIS-based habitat-suitability model for female RGWTs during the breeding season that will allow the assessment of the spatial distribution of adequate habitat in the Edwards Plateau.The analysis of the landscape characteristics along the North Prong Medina River due to flooding in 1978 had a negative impact on RGWT habitat. Changes in the spatial distribution of woody cover in the bottomlands and the removal of woody cover along riparian zones most likely limited habitat use and dispersal of RGWT along the North Prong Medina River. The analysis of landscape characteristics in sites with stable and declining of RGWTs populations showed that disturbance and a high proportion of woody cover were important factors influencing RGWT populations in areas where turkey numbers had declined. Landscape attributes were used as habitat variables to develop a habitat-suitability model for female RGWTs during the breeding season. The model performed well in characterizing high-suitability habitat for adult female RGWT during the breeding season in the study areas. The use of two scales relevant to RGWT provided important information about the high-suitability areas for female RGWT in stable and declining sites in the Edwards Plateau.Item Human presence detection using millimeter-wave radiometry(2008-05) Nanzer, Jeffrey A. (Jeffrey Allan); Ling, Hao; Rogers, Robert Lowell, 1961-A novel method of human presence detection using passive millimeter-wave sensors is presented. The method focuses on detecting a standing human from a moving platform in a cluttered outdoor environment using millimeter-wave radiometry, which has not been attempted before. Ka-band radiometers are used in total power mode as well as correlation mode, which ideally responds well to self-luminous objects such as humans. The intrinsic radiative power from a human is derived as well as the responses of the total power and correlation mode. The application of correlation radiometer theory to the detection of self-luminous objects at close range is presented in the context of human presence detection. Modifications and additions to techniques developed in radio astronomy and remote sensing for close range terrestrial situations are developed and discussed. The correlation radiometer fringe frequency is analyzed in the context of the scanning beam detection system and is estimated using MUSIC and ESPRIT. Detection and classification of humans is accomplished using a Naïve Bayesian classifier. The performance of the classifier is measured using the F1-measure and the receiver operating characteristic.Item Improved Modeling of Evapotranspiration using Satellite Remote Sensing at Varying Spatial and Temporal Scales(2012-10-19) Long, DiThe overall objective of the dissertation was to improve the spatial and temporal representation and retrieval accuracy of evapotranspiration (ET) using satellite imagery. Specifically, (1) aiming at improving the spatial representation of daily net radiation (Rn,24) under rugged terrains, a new algorithm, which accounts for terrain effects on available shortwave radiation throughout a day and utilizes four observations of Moderate-resolution Imaging Spectroradiometer (MODIS)-based land surface temperature retrievals to simulate daily net longwave radiation, was developed. The algorithm appears to be capable of capturing heterogeneity in Rn,24 at watershed scales. (2) Most satellite-based ET models are constrained to work under cloud-free conditions. To address this deficiency, an approach of integrating a satellite-based model with a large-scale feedback model was proposed to generate ET time series for all days. Results show that the ET time series estimates can exhibit complementary features between the potential ET and the actual ET at watershed scales. (3) For improving the operability of Two-source Energy Balance (TSEB) which requires computing resistance networks and tuning the Priestley-Taylor parameter involved, a new Two-source Trapezoid Model for ET (TTME) based on deriving theoretical boundaries of evaporative fraction (EF) and the concept of soil surface moisture availability isopleths was developed. It was applied to the Soil Moisture and Atmosphere Coupling Experiment (SMACEX) site in central Iowa, U.S., on three Landsat TM/ETM imagery acquisition dates in 2002. Results show the EF and latent heat flux (LE) estimates with a mean absolute percentage difference (MAPD) of 6.7 percent and 8.7 percent, respectively, relative to eddy covariance tower-based measurements after forcing closure by the Bowen ratio technique. (4) The domain and resolution dependencies of the Surface Energy Balance Algorithm for Land (SEBAL) and the triangle model were systematically investigated. Derivation of theoretical boundaries of EF for the two models could effectively constrain errors/uncertainties arising from these dependencies. (5) A Modified SEBAL (M-SEBAL) was consequently proposed, in which subjectivity involved in the selection of extreme pixels by the operator is eliminated. The performance of M-SEBAL at the SMACEX site is reasonably well, showing EF and LE estimates with an MAPD of 6.3 percent and 8.9 percent, respectively.Item Knowledge-based learning for classification of hyperspectral data(2007-05) Chen, Yang-Chi, 1973-; Crawford, Melba M.; Ghosh, JoydeepItem Liquefaction-induced lateral displacements from the Canterbury earthquake sequence in New Zealand measured from remote sensing techniques(2016-05) Secara, Sorin S.; Rathje, Ellen M.; Cox, Brady RLiquefaction is a significant earthquake hazard that can generate large horizontal displacements associated with lateral spreading and these displacements cause considerable damage. To improve our understanding of liquefaction-induced lateral spreading and the models that can be used to predict the associated displacements, the collection of high quality field data on lateral spreading displacements is essential. Remote sensing techniques, in particular optical image correlation using satellite imagery, can be used for this purpose. This thesis investigates optical image correlation of satellite images as a remote sensing technique for this purpose using images from the 2010-2011 Canterbury earthquake sequence in New Zealand. Optical image correlation uses two optical images – one before and one after the investigated event – to measure displacements that have occurred between the time of the two image acquisitions. The correlation analysis calculates the horizontal displacement at a specified spacing, and the displacements are post-processed and filtered to attain the final displacement field. The displacement results from optical image correlation agreed favorably with qualitative field observations of the severity of liquefaction and lateral spreading, as well as the general crack patterns along the Avon River. A more quantitative comparison was performed using field measured displacements along four linear transects that extended perpendicular from the Avon River. The displacements from optical image correlation also agreed favorably with the field measured displacement profiles, although the optical image correlation displacements somewhat larger than the field measurements. This discrepancy occurs because field measurements are based on discrete measurements of crack width, while the optical image correlation are based on average displacements over larger areas and include displacements associated with ductile movements that may not result in cracking. The results from this research show that optical image correlation of satellite imagery pairs can provide accurate and detailed measurements of horizontal displacements due to liquefaction and lateral spreading. This approach can be used to create more complete and detailed databases of liquefaction-induced movements, which can be used to improve current predictive models for lateral spread displacements. Future post-earthquake investigations and research should make use of optical image correlation to document the displacements associated with liquefaction.Item On a class of two-dimensional inverse problems: wavefield-based shape detection and localization and material profile reconstruction(2006) Na, Seong-Won; Kallivokas, Loukas F.In this dissertation we discuss the numerical treatment of two classical inverse problems: firstly, we are interested in the shape detection and localization problem that arises when it is desirable to identify the location and shape of an unknown object embedded in a host medium using response measurements at remote stations. Secondly, we are concerned with the reconstruction of a medium’s material profile given, again, scant response data. For both problems we use acoustic (or equivalent) waves, to illuminate the interrogated object/medium; however, the mathematical/numerical treatment presented herein extends directly to other wave types. There is a wide, and ever widening, spectrum of possible applications that stand to benefit: of particular interest here are geotechnical applications that arise during site characterization efforts. To tackle both inverse problems we adopt the systematic framework of governing-equation-constrained optimization. Accordingly, misfit functionals are augmented with appropriate regularization terms, and with the weak imposition of the equations describing the physics of the wave interrogation. The governing equations may be either of the partial-differential or integral kind, subject only to user preference or problem bias. The framework is flexible enough to accommodate various misfit norms and regularization terms. We seek solutions that minimize the augmented functional by requiring that the first-order optimality conditions vanish at the optimum, thereby giving rise to Karush-Kuhn-Tucker-type systems. We then solve the associated state, adjoint, and control problems with a reduced-space approach. To alleviate the theoretical and numerical difficulties inherent to all inverse problems that are present here as well, we seek to narrow the solution feasibility space by adopting special schemes. In the shape detection and localization problem we adopt amplitude-based misfit functionals, and a frequencyand directionality-continuation scheme, somewhat akin to multigrid methods, that, thus far, have lend robustness to the inversion process. The mathematical details are based on integral equations, where, in addition, the control problem is cast in the elegant framework of total or material derivatives that allow computational speed-up when compared to finite-difference-based gradient schemes. Similarly, in the material profile reconstruction problem we adopt a time-dependent regularization scheme that exhibits superior performance to classical Tikhonov-type regularizations and is shown to be capable of recovering both sharp and smooth material distributions, while being relatively insensitive to the choice of initial guesses and regularization factors. These schemes constitute particular contributions of this work. We describe the mathematical framework and report numerical results. Specifically, with respect to the shape detection and localization problem we report on the two-dimensional case of sound-hard objects embedded in fullspace; with respect to the material profile reconstruction problem, we report results on the one-dimensional case of horizontally-layered systems, and on the two-dimensional case of finite or infinite-extent domains. We discuss the algorithmic performance in the presence of both noise-free and noisy data and provide recommendations for possible extensions of this work.Item Optimized band elimination and dimensionality reduction of hyperspectral images(Texas Tech University, 2003-12) Borra, SandhyaDimensionality reduction is a very important step in the anahsis of hyperspectral images. There should be an optimal tradeoff between the reduction in dimensionality and loss of information. Principal component analysis (PCA) is used as the main approach for the dimensionality reduction of hyperspectral data. PCA is basically an orthogonal projection of the data onto a subspace of lower dimensionality. An important preprocessing step before performing PCA is the registration of the individual bands of the hyperspectral image. Spatial image registration is performed using the properties of power cepstmm and the Fourier shift theorem. It is also unwise in terms of computational efficiency to use all the bands of the hyperspectral image for PCA. Therefore, an efficient hierarchical dimensionality reduction technique is implemented. It is used in conjunction with an entropy measure to pre-select the bands of the image, which are to be used for performing PCA. PCA relies heavily on second order moments, which result in a high sensitivity of the algorithm to outliers in the data. Hence, an efficient version of principal component analysis is also implemented, using a robust estimate of the covariance matrix to do the transformation. The scree plots and performance measures for PCA are analyzed for the given hyperspectral imagery.Item Principles of evaluation of telemetry systems for oilfield applications.(Texas Tech University, 1974-12) Loyd, George RichardNot availableItem Remote sensing, geochemistry, geochronology, and cathodoluminescence imaging of the Egrigoz, Koyunoba, and Alacam plutons, Northern Menderes Massif, Turkey(2011-05) Jacob, Lauren Rolston; Catlos, Elizabeth Jacqueline; Cloos, Mark; Barker, DanielThe Egrigoz, Koyunoba, and Alacam plutons are located in the Northern Menderes Massif of western Turkey between the Simav normal fault to the south and the Izmir-Ankara-Erzincan suture to the north. Although much attention has focused on their geochemical and geochronological history, their relationship to each other and other major structures in the region is still debated. Some geologic maps show the Egrigoz and Koyunoba pluton bounded to the west by the low-angle Simav detachment fault. In contrast, other regional maps show no offsets between the plutons and surrounding metamorphic rocks. Yet other studies indicate thrust faults may be present near the Egrigoz pluton, between Menderes metamorphic rocks and a meta-rhyolite unit. To gain a better understanding of the history of the Egrigoz, Koyunoba, and Alacam plutons, ArcGIS digital elevation data from the region, geochronological data, geochemical analyses, and cathodoluminescence (CL) images were acquired to search for effects of micro- to macro-scales of deformation. Numerous ~E-W trending extension lineations that parallel the Simav graben and cut the plutons were observed in relief images. These lineations, likely due to large-scale ~N-S extension, continue across plutons inferring that extension continued after the exhumation of these rocks. The Simav graben and its associated high-angle fault are evident in the elevation data, but no other significant detachment-related basins or structures are shown, including the low-angle Simav detachment. U-Pb zircon ages, ranging from 29.9±3.9 Ma to 14.6±2.6 Ma, suggest the plutons crystallized over a ~15 m.y. time frame. Samples from the plutons are peraluminous S-type granite to granodiorites. The plutons were emplaced in a post-collisional volcanic-arc setting and range from magnesian to ferroan with increasing silica contents. Geochemical analyses show little difference between the three plutons, consistent with the rocks arising from a similar source. To document microstructures that might help explain these heterogeneities, CL images were obtained. CL images document a complicated tectonic history including magma mixing, multiple episodes of brittle deformation, and fluid alteration. The CL images constitute evidence of a complex multi-stage tectonic history for the region that includes water-mediated brittle deformation.Item Remote-sensing applications to windstorm damage assessment(Texas Tech University, 2005-12) Womble, James A.; Mehta, Kishor C.The collection and study of windstorm damage information is critical for the understanding of wind effects on the built environment, for measuring progress in construction technologies and mitigation measures, and for (ultimately) helping to build disaster-resilient communities. Rapid and thorough documentation of damage is crucial but has not generally been possible in the past due to limited time (prior to cleanup and repair efforts), manpower, and access to affected areas. Modern remote-sensing technologies, including high-resolution satellite imagery, have proven effective for the documentation and study of damage caused by multiple hazards, such as earthquakes. In conjunction with traditional forensic damage assessments, these technologies also provide a means for enhancing the speed, thoroughness, coverage area, and consistency of windstorm damage documentation. Ongoing developments in the fields of remote sensing and digital image processing can eventually lead to the computer-automated detection of multi-hazards damage. Each individual hazard has unique damage mechanisms and, therefore, unique remote-sensing signatures that must be identified and quantified for use in eventual automation. This research examines the use of remote-sensing technologies for damage assessment in multiple hazards and presents a framework for the automated application of remote-sensing technologies specifically to the windstorm hazard. This study utilizes remote-sensing data and corresponding ground-truthing field data from recent significant windstorms to demonstrate the use of remote-sensing technologies in collecting windstorm damage data. This study also examines the remote-sensing signatures of windstorm damage to buildings and demonstrates the use of remote-sensing and digital-image-processing technologies for making quantitative assessments of windstorm damage to buildings. This research finally provides suggestions for future developments in the remote-sensing assessment of windstorm damage.Item Soil moisture modeling and scaling using passive microwave remote sensing(Texas A&M University, 2007-04-25) Das, Narendra N.Soil moisture in the shallow subsurface is a primary hydrologic state governing land-atmosphere interaction at various scales. The primary objectives of this study are to model soil moisture in the root zone in a distributed manner and determine scaling properties of surface soil moisture using passive microwave remote sensing. The study was divided into two parts. For the first study, a root zone soil moisture assessment tool (SMAT) was developed in the ArcGIS platform by fully integrating a one-dimensional vadose zone hydrology model (HYDRUS-ET) with an ensemble Kalman filter (EnKF) data assimilation capability. The tool was tested with dataset from the Southern Great Plain 1997 (SGP97) hydrology remote sensing experiment. Results demonstrated that SMAT displayed a reasonable capability to generate soil moisture distribution at the desired resolution at various depths of the root zone in Little Washita watershed during the SGP97 hydrology remote sensing experiment. To improve the model performance, several outstanding issues need to be addressed in the future by: including "effective" hydraulic parameters across spatial scales; implementing subsurface soil properties data bases using direct and indirect methods; incorporating appropriate hydrologic processes across spatial scales; accounting uncertainties in forcing data; and preserving interactions for spatially correlated pixels. The second study focused on spatial scaling properties of the Polarimetric Scanning Radiometer (PSR)-based remotely sensed surface soil moisture fields in a region with high row crop agriculture. A wavelet based multi-resolution technique was used to decompose the soil moisture fields into larger-scale average soil moisture fields and fluctuations in horizontal, diagonal and vertical directions at various resolutions. The specific objective was to relate soil moisture variability at the scale of the PSR footprint (800 m X 800 m) to larger scale average soil moisture field variability. We also investigated the scaling characteristics of fluctuation fields among various resolutions. The spatial structure of soil moisture exhibited linearity in the log-log dependency of the variance versus scale-factor, up to a scale factor of -2.6 (6100 m X 6100 m) irrespective of wet and dry conditions, whereas dry fields reflect nonlinear (multi-scaling) behavior at larger scale-factors.