Browsing by Author "Heather M. Cheshire, Committee Member"

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Accuracy Evaluation of a 3-D Spatial Modeling Approach to Model Linear Objects and Predict Their Lengths
(2004-03-28) Cai, Hubo; Joseph E. Hummer, Committee Member; Hugh A. Devine, Committee Member; Heather M. Cheshire, Committee Member; William J. Rasdorf, Committee Chair
Real world objects are three-dimensional. Numerous applications in geographic information systems (GISs) require modeling spatial objects in a 3-D space, but many current GISs only represent two-dimensional information. The GIS community has been struggling with solving complex problems dealing with 3-D objects using a 2-D approach. This research focused on modeling linear objects in a 3-D space, predicting their 3-D distances, and evaluating the accuracy. A point model was developed, which modeled a 3-D line with a group of 3-D points (with X/Y/Z-coordinates) connected by straight lines. It required two input datasets, an elevation dataset and a planimetric line dataset. With elevation datasets in different formats (point data and digital elevation models (DEMs)), two approaches were proposed, differing in how the third dimension (elevation) was introduced. With point data, a snapping approach was developed. With DEMs, elevations for points uniformly distributed along planimetric lines were obtained via bilinear interpolations. Mathematical equations were derived to predict 3-D distances. A case study was designed in the transportation field because of the rich source of linear objects and the criticality of 3-D distances in GIS-T and LRS. Two elevation datasets were used: LIDAR and national elevation dataset (NED). LIDAR datasets were further categorized into point data and DEMs (20-ft and 50-ft resolutions). Two intervals were taken to locate points planimetrically along lines when using DEMs (full cell size and half cell size). Consequently, each line was associated with seven calculated 3-D distances (one from LIDAR point data, two from LIDAR 20-ft DEM, two from LIDAR 50-ft DEM, and two from NED). The accuracy of predicted 3-D distances was evaluated by comparing them to distance measurement instrument (DMI) measured distances. Errors were represented in two formats: difference and proportional difference (based on DMI measured distances) between the predicted 3-D distance and the DMI measured distance, taking road types into consideration. Evaluation methods included descriptive statistics, error distribution histograms, hypothesis tests, frequency analysis, and root mean square of errors (RMSE). The effects from the use of different elevation datasets and intervals on the accuracy were evaluated via a sensitivity analysis. The effects from the geometric properties of linear objects on the accuracy were evaluated via significant factor analyses. Factors under consideration included distance, average slope and weighted slope, average slope change and weighted slope change, and the number and density of 3-D points. The usefulness of this research was proved by applying the resulting 3-D road centerlines to determine flooded road segments under flooding scenarios. This research concluded that errors in the predicted 3-D distance varied with elevation datasets and road types, but not with the use of different intervals with the same elevation dataset, given the interval was less than or equal to the cell size. Using elevation datasets with higher vertical accuracies resulted in higher accuracies in predicted 3-D distances. In this research, using LIDAR point data improved the accuracy by 28% and using LIDAR DEMs improved the accuracy by 6%, compared to using NED data, with 100% RMSEs as the accuracy measure. It was also concluded that there was a positive association between the error and any one of these factors from the aspect of the difference but a negative association from the aspect of the proportional difference. Each factor had a threshold, above which effects from the increase of the factor value were insignificant.
Anthropogenic Drivers of Gypsy Moth Dispersal.
(2009-04-16) Bigsby, Kevin M; Erin O. Sills, Committee Chair; Fred P. Hain, Committee Member; Heather M. Cheshire, Committee Member; Patrick C. Tobin, Committee Member
Gypsy moth (Lymantria dispar: Linnaeus) is a polyphagous non-native forest pest first introduced to Medford, Massachusetts in 1869. It has since spread as far south as North Carolina and as far west as Wisconsin. Gypsy moth is responsible for defoliating approximately 100,000 hectares of forest annually, resulting in mortality in a small percentage of trees, averting behavior by recreators, and creating a nuisance to the general public. Limiting the spread of gypsy moth is beneficial because it delays the onset of costs and losses associated with quarantine, tree defoliation and mortality, and nuisance. Gypsy moth is believed to disperse naturally up to 2.5 km/yr (e.g. early instar ballooning) but has been observed to disperse much greater distances. The scientific consensus is that this longer distance dispersal occurs through anthropogenic vectors (e.g. egg masses being transported on firewood). Despite the resources that United States Department of Agriculture and state agencies dedicate to eliminating and managing new infestations resulting from long distance dispersal, there has been limited empirical research on the relationship between the dispersal of gypsy moth and the movement of people and their goods. This thesis develops a conceptual framework of the anthropogenic factors that could affect dispersal, measures these factors with secondary data at the county level from a variety of sources, and estimates the presence or absence of gypsy moth using logistic regression models. The dependent variable is drawn from trap catch records archived by the United States Department of Agriculture Forest Service program, Slow-the-Spread, in areas distal to the 1 moth/trap line between 1999 and 2007. Through step-wise logistic regression estimating sub-models that include variables representing each broad anthropogenic factor, a final empirical model is specified. The variables of the model are estimated independently for each year from 1999 to 2007, resulting in a mean Pseudo R square of 0.568. Consistently significant ( ) anthropogenic variables are the number of households using wood for heating fuel and mean household income. These findings are discussed with regard to invasion theory and quarantine policy. One key implication is the continual importance of regulating and raising awareness about the risk of moving firewood from infested to uninfested zones.
Assessing DNA Damage in Hemocytes of the Freshwater Mussel Elliptio complanata with the Comet Assay
(2007-12-21) Prochazka, Sharon Tencza; W. Gregory Cope, Committee Chair; Heather M. Cheshire, Committee Member; Leslie Recio, Committee Member; David B. Buchwalter, Committee Member
The single cell gel electrophoresis or comet assay is widely used to detect DNA damage following exposure to genotoxic compounds with cells isolated from tissue or circulatory fluids from various organisms. The cell sampling method can often lead to the fatality of the test organism, depending on the type of tissue sampled. The objective of this study was to assess genotoxicity with the comet assay from in vitro and in vivo studies using a non-lethal hemolymph sampling method on Elliptio complanata, a native freshwater mussel found abundantly in North Carolina. The hemolymph was withdrawn from the anterior adductor muscle sinus and exposed in vitro to various concentrations (previously tested for cell viability) of selected pesticide formulations, Aatrex 4L herbicide (atrazine), Roundup herbicide (glyphosate), Lorsban 4E insecticide (chlorpyrifos), and Thionex 3EC insecticide (endosulfan), technical grade copper sulfate and a mixture of 46 different PAHs for 4-hours at 4°C. After exposure, the hemocytes were isolated and the comet assay was performed on the treated cells, control cells, and positive control cells exposed to 160 uM hydrogen peroxide (H2O2). For quality assurance purposes, CometAssay Control Cells™ were analyzed throughout each comet assay procedure in the laboratory to ensure the validity of results. The levels of DNA damage measured were expressed as % tail DNA and olive tail moment (OTM). Of all the compounds and concentrations tested during the in vitro exposures, excluding the positive H2O2 controls, only the mixture of PAHs yielded statistically significant (P < 0.05) levels of DNA damage compared to the controls for both DNA damage parameters. The DNA damage was observed at 50 and 100 mg⁄L PAHs, with % tail DNA of 40.70 % and 38.55 %, and OTM of 12.41 and 11.03, respectively. The remaining test compounds yielded no detectable genotoxic effects, regardless of the DNA damage parameter, under the specified concentrations and test conditions. Because genotoxicity was detected during the in vitro exposure with PAHs, an in vivo exposure with PAHs was performed to assess the predictive capabilities of the in vitro test. The in vitro PAH exposure produced a much greater genotoxic response with both parameters then was detected in vivo, in which only the positive control yielded statistically significant levels of DNA damage. Thus, under the conditions tested in this study, in vitro exposures with freshwater mussel hemolymph were unable to predict a similar in vivo response, based on the presented data. Nonetheless, a method with a high degree of accuracy was demonstrated during this study with consistent and repeatable levels of DNA damage measured in the CometAssay Control cells™ and positive control treatments. Therefore, we are confident that if the chemicals tested had been genotoxic under the conditions tested, the effects would have been detected. This research investigated the use of a non-lethal genotoxicity screening tool using freshwater mussel hemolymph. Further testing and evaluation is needed before this tool could be widely implemented. Moreover, there is need for a better understanding of freshwater mussel hemolymph and the functions and capabilities of hemocytes in the defense of genotoxic compounds.
Breeding Biology of Swainson's Warblers in a Managed South Carolina Bottomland Forest
(2005-07-22) Thompson, Jennifer Laurie; Richard A. Lancia, Committee Chair; Kenneth H. Pollock, Committee Member; Heather M. Cheshire, Committee Member; Phillip D. Doerr, Committee Member
Conservation plans for the southeastern U.S. have identified Swainson's Warblers (Limnothlypis swainsonii) to be among the more vulnerable Neotropical migrants. However, a lack of life history information, in particular breeding, jeopardizes sound management decisions. My study examined a population in Britton's Neck, South Carolina on timberland owned by International Paper Co. From 1999-2001, I conducted a breeding biology study that examined nesting, territory, vegetative, and landscape characteristics. I discovered 98 SWWA nests, 63 of which were active. SWWA nesting success equaled 60% using the Mayfield success estimator. Contrary to the notion of SWWA requiring mature forests to breed, SWWA bred successfully in 20-year old regenerating clearcuts. Multiple brooding, where a pair initiates nesting attempts after their first is successful, was detected in 20% of the pairs. An individual's seasonal fecundity was doubled by multiple brooding, increasing the young per female from 1.5 to 3.7. Brown-headed Cowbirds (Molothrus ater) parasitized only 10% of nests. No SWWA chicks were observed fledging in the presence of Cowbirds. Apparent population density was 17 territories/km2, equaling the highest density ever recorded for SWWA. One-fifth the site contained 59 territories/km2, compared to the remaining four-fifths with 12 territories/km2. I examined vegetative differences between nests built in high- versus low-density areas using a discriminant function analysis (DFA). The DFA results indicated understory thickets accounted for the largest difference between high- and low-density nest sites. Nests in the high-density area were more associated with understory thickets.
Development and Assessment of Advanced Data Fusion Algorithms for Remotely Sensed Data
(2004-12-19) Cakir, Halil Ibrahim; Siamak Khorram, Committee Chair; Hugh A. Devine, Committee Member; Heather M. Cheshire, Committee Member; Montserrat Fuentes, Committee Member
The general objective of this study is to develop and implement data fusion methodologies for remotely sensed imagery. Utilization of multisource and multidate data sources in remote sensing studies has gained popularity with recent technological advances. From increases in spatial resolution to better change detection, data fusion processes have become an important part of remote sensing. Broadly defined, data fusion is a necessary step or component of most remote sensing studies. This research combines three studies in which new data fusion methodologies are developed and implemented for remotely sensed data. In the first study, utilization of a multiresolution approach is explored. Information gathered from the multiresolution analysis of multispectral and panchromatic images is used to increase the spatial resolution of multispectral imagery with minimal loss in the spectral integrity of the original input data. 30-meter Landsat 7 multispectral imagery is fused with 15-meter same-satellite panchromatic imagery to increase the spatial resolution of the former. In the second study, a multivariate analysis procedure called correspondence analysis (CA) is utilized to fuse 4-meter IKONOS multispectral imagery with 1-meter IKONOS panchromatic imagery. In this method, the last component of a correspondence analysis image is replaced with 1-meter panchromatic imagery before the CA image is transformed back to the original image space. An analysis of the fused image shows that this technique keeps most of the original image variance while distortion remains minimal. In the last study, CA is utilized to improve change detection accuracy when detecting changes between two dates of imagery. Before and after Landsat images of Raleigh, North Carolina are transformed into component space individually using CA. Then, an image-differencing method is applied to the individual components. It is concluded that using the first CA component with image differencing drastically improves the detection of change between two dates. Overall, these studies provide new methodologies for fusing the multisource and multidate images. Two methods to increase the spatial resolution of remotely sensed data and one method to perform change detection are proposed. All the proposed methodologies are an improvement over present commonly used techniques within their respective application areas.
The Effects of Internal Characteristics of Municipal Government Agencies and Environmental Factors of Municipalities on the Scope and the Quality of Municipal E-government Initiatives: Developing an Integrated Approach.
(2004-12-29) Pavlichev, Alexei; G. David Garson, Committee Chair; Heather M. Cheshire, Committee Member; Michael L. Vasu, Committee Member; Deborah L. Weisel, Committee Member
The objective of the research has been to determine which internal characteristics of municipal government agencies and which environmental factors of the municipalities across the U.S. affect the quality and the scope of adoption of municipal electronic government (e-government) initiatives. To accomplish this objective, an integrated approach was developed. The approach combined theoretical methodologies of three frameworks applied to the public sector agencies: innovation theory, information and communication technology, and e-government. It was hypothesized that theoretical premises of these frameworks complement each other in their ability to explain municipal e-government initiatives and their combination would help to address the drawbacks that characterize the present research on municipal e-government. The dependent variable in the present research is municipal e-government score. The dependent variable measures the scope and quality of municipal e-government initiatives. The research concentrates on two sets of predictor variables: internal municipal government agency characteristics and external environmental factors of municipalities. Correlation/regression analyses were performed to explore bivariate and multivariate relationships between the dependent and predictor variables and to accomplish the following goals: (1) describe the relationship between the dependent variable and the two sets of predictors (internal municipal agency characteristics and external environmental factors); (2) determine the effects of individual predictors in explaining the rate and the scope of adoption of e-government initiatives; and (3) compare the two sets of predictors in their power to explain the rate and the scope of adoption of e-government initiatives. The results of these analyses demonstrated that external environmental factors are significantly better predictors of the quality and the scope of local e-government initiatives, as measured by the e-government score, both individually and as a set.
Impact of hunting pressure on adult male white-tailed deer behavior
(2008-12-08) Karns, Gabriel Ryan; Mark C. Conner, Committee Member; Michael K. Stoskopf, Committee Member; Heather M. Cheshire, Committee Member; Christopher S. DePerno, Committee Co-Chair; Richard A. Lancia, Committee Co-Chair
The impact of hunting pressure on white-tailed deer behavior has been broadly studied, but specific examination of the interaction between adult males and hunters has not been conducted using global positioning system (GPS) technology. During 2006-2007 at Chesapeake Farms, a privately owned property in Kent County, Maryland, research focused on this interaction using GPS collars affixed to 19 adult male white-tailed deer. I looked for changes in home range and core area size, shifts in home range and core area, movement, activity, vulnerability, and refuge use using an analysis of variance (ANOVA) and Tukeyâ€™s honestly significant difference (HSD) test. Movement decreased during the dawn (F = 6.284, df = 24, P = 0.006) and day (F = 11.060, df = 24, P < 0.001) hours, and activity decreased during the day (F = 6.289, df = 24, P = 0.006). However, no other significant findings provided evidence that these changes were solely a function of Marylandâ€™s 2-week hunting season and not a by-product of temporal correlation with decreases in male activity that would be expected during the post-breed season. I concluded that hunters on Chesapeake Farms did not exert sufficient hunting pressure to induce noticeable behavioral change in adult male white-tailed deer. Combining data gathered from the GPS-collared adult males with a previous study (Tomberlin 2007), I analyzed adult male excursions outside of their home range during the fall and winter months. Documenting 30 excursions, the majority of adult males (53%) engaged in at least one excursion during study periods. Twenty-two excursions (73%) were made during the pre-breed 2 or breeding periods, and breeding-season related motives seemed to be the driving force behind most adult male excursions. By comparing excursions during hunting season with known hunter locations, it is not likely that hunting was an instigating factor for excursions at Chesapeake Farms. In addition to the GPS collar research, a catch-per-unit-effort (CPUE) estimator was improved by converting FORTRAN code (Bishir et al. 1996) to JMP scripting language (JSL). The method was validated by comparing previous (1981-1991) FORTRAN estimates of the antlered male population at Chesapeake Farms, MD, to JMP estimates. Also, I tested the CPUE-JMP estimatorâ€™s effectiveness with regards to varying length hunting seasons and traditional versus quality deer management (QDM) paradigms. The new method improved estimates by 25%, and different season lengths and deer management regimes did not have a significant impact on estimates. Long-term trends produced by the CPUE-JMP estimator were sufficient for most harvested big-game population management applications. Lastly, I examined the natural mortality factor of intracranial abscessation in the adult male white-tailed deer population at Chesapeake Farms, MD. From 2003-2007, mortality was documented for and necropsies performed on 26 GPS-collared adult males. Adult male mortality due to intracranial abscessation was disproportionately high (35%) compared to the national average (9%), and if additive to other natural mortality factors and hunter harvests in the population could pose a serious obstacle to achievement of QDM objectives.