VTechWorks Repository :: Browsing by Author "Carstensen, Laurence W."

Browsing by Author "Carstensen, Laurence W."

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Accumulated Surfaces & Least-Cost Paths: GIS Modeling for Autonomous Ground Vehicle (AGV) Navigation
Stahl, Christopher Wayne (Virginia Tech, 2005-05-11)
The Geographic Information System (GIS) is a crucial part of any land navigation system. Autonomous ground vehicles should have access to stored geographic data and the ability to manipulate it for routing purposes. Since there is no human interaction involved in operating these vehicles, data that a human driver would use to make decisions must be stored in the GIS. The data which represent the earth's surface become a series of factors and constraints which translate to friction in terms of mobility. Factors need to be weighted appropriately, but require a sensitivity analysis before designating these weights. Constraints do not require any weight because they represent absolute barriers which cannot be traveled upon. All GIS layers are incorporated into the raster environment, so that an accumulated surfaces can be built on which a least-cost path can be located. The sensitivity analysis allows generation of many routes which can be field tested for the appropriate weight selection for each factor. Ultimately, the entire process would select an optimal path and output closely spaced waypoints which the vehicle can follow.
Administrative and Political Implications of GIS Implementation within the Fire Service: A Case Study of Norfolk, VA
Bloom, Paul Sean (Virginia Tech, 1998-04-24)
The advent of faster, cheaper, and more powerful computer hardware has led to the widespread integration of GIS technologies into decision making processes within local governments. Most GIS literature has focused on the models and benefits that the technology can produce and not on the impacts that GIS has on the organization. This research explores the political and administrative implications of utilizing a GIS to address a resource allocation problem within the Fire Service Administration of the City of Norfolk, VA. A network model is employed to allocate rescue resources throughout the city in various configurations. The goal of NFPS (Norfolk Fire and Paramedical Services) is to be able to cover the entire City of Norfolk within five minutes of travel time. City and NFPS administrators evaluate various models based upon a provided questionnaire that focuses on the administrative and political viability of each of the models produced.
Alternative health care in the 1990's: the influence of legal constraints on the locational behavior of acupuncturists, chiropractors, and homeopaths
Baer, Leonard (Virginia Tech, 1994-04-22)
This study showed that state laws and policies constrain the locational preferences of alternative health care providers to varying degrees, depending on the particular profession and level of legal status. Three separate surveys were conducted, focusing on acupuncturists, chiropractors and homeopaths in Maryland, Virginia, North Carolina, and the District of Columbia. The acupuncture findings revealed intraprofessional divisions that lead to a strong influence of legal constraints on the locational behavior of non-MD acupuncturists. Results from the chiropractic survey reflected an established profession with a less pronounced, but moderate, influence of state laws and policies on location and mobility. The homeopathy findings, while based on a much smaller sample, did not reveal a strong relationship between legal constraints and spatial characteristics, except in the extreme case of North Carolina's recent prohibition. This study also postulated a model to explain the progression of alternative health care professions toward legitimation. The variables of public acceptance and legal constraints on location were plotted on the model to identify particular levels of progression. The importance of this research is highlighted by impending health care reforms, the need for access to professional health services, skyrocketing biomedical costs, and the documented utilization of alternative health care in this country.
An Analysis of Shoreline Change at Little Lagoon, Alabama
Gibson, Glen R. (Virginia Tech, 2006-06-20)
In Alabama, the term "coastal shoreline" applies to the Gulf shoreline and the shorelines of estuaries, bays, and sounds connected to the Gulf of Mexico and subject to its tides. However, Alabama shoreline studies have yet to include Little Lagoon, which has been connected to the Gulf of Mexico for most of the last 200 years, according to historical charts. This study used historical nautical charts, aerial photographs, and LIDAR derived shorelines from 1917 to 2004 to analyze shoreline change on Little Lagoon and its adjacent Gulf shoreline. The high water line was used as the common reference feature, and all shorelines were georeferenced, projected, and digitized in a Geographic In-formation System. Between 1917 and 2001, the Gulf shoreline eroded an average of 40 m over 12.7 km, with some transects eroding almost 120 m while others accreted almost 60 m. The greatest changes to the Gulf shoreline were found near natural inlets, downdrift of jetties, and coincident with nourishment projects. Between 1955 and 1997, Little Lagoon shrank 0.5%, or 51.4 km², from 10,285.9 km² to 10,234.5 km². The greatest changes to Little Lagoon were found on its southern shoreline and near inlets, human development, and hurricane overwash fans. A correlation analysis conducted on the Gulf shoreline and Little Lagoon' s southern shoreline indicated that although weak overall correlation values exist when the entire 12.7 km study area is compared, strong correlation values are obtained in some areas when compared over one kilometer sections. The strongest correlations were found in the same locations as the greatest changes.
Analysis of technological change and relief representation in U.S.G.S. topographic maps
Mahoney, Patricia (Virginia Tech, 1991-01-15)
In 1882, the United States Geological Survey began its National Mappping Program designed to map the nation using a series of several thousand topographic quadrangles. Since that date, the program and the maps themselves have undergone many changes due mainly to technological advances in mapping methods. The use of data collected from historic U.S.G.S. topographic maps in modem day applications necessitates a general knowledge of the potentials and limitations of these data. This study compares representations of terrain features on historic maps compiled using plane table methods with the same features as represented on more accurate modem maps compiled using photogrammetry. Using the modem map as a standard, errors in the old maps were identified and defined using statistical procedures. Measures of closed contour lines recorded the angularity of the line, the length of the line, the area within the contour, the shape of the feature and spatial relationships between contour pairs. The analysis attempts to relate errors to these geometric components of contour lines and to predict the occurrence of error. Due to practices of smoothing and generalization of contour lines in plane table surveys, measures of both angularity and shape were significantly different between older and newer maps. Systematic errors, a consistent displacement of contour lines in a similar direction, were also identified on the historic maps. Based on these results, several suggestions for continuation of the research are given.
Analysis of Viewshed Accuracy with Variable Resolution LIDAR Digital Surface Models and Photogrammetrically-Derived Digital Elevation Models
Miller, Matthew Lowell (Virginia Tech, 2011-10-28)
The analysis of visibility between two points on the earth's terrain is a common use of GIS software. Most commercial GIS software packages include the ability to generate a viewshed, or a map of terrain surrounding a particular location that would be visible to an observer. Viewsheds are often generated using "bare-earth" Digital Elevation Models (DEMs) derived from the process of photogrammetry. More detailed models, known as Digital Surface Models (DSMs), are often generated using Light Detection and Ranging (LIDAR) which uses an airborne laser to scan the terrain. In addition to having greater accuracy than photogrammetric DEMs, LIDAR DSMs include surface features such as buildings and trees. This project used a visibility algorithm to predict visibility between observer and target locations using both photogrammetric DEMs and LIDAR DSMs of varying resolution. A field survey of the locations was conducted to determine the accuracy of the visibility predictions and to gauge the extent to which the presence of surface features in the DSMs affected the accuracy. The use of different resolution terrain models allowed for the analysis of the relationship between accuracy and optimal grid size. Additionally, a series of visibility predictions were made using Monte Carlo methods to add random error to the terrain elevation to estimate the probability of a target's being visible. Finally, the LIDAR DSMs were used to determine the linear distance of terrain along the lines-of-sight between the observer and targets that were obscured by trees or bushes. A logistic regression was performed between that distance and the visibility of the target to determine the extent to which a greater amount of vegetation along the line-of-sight impacted the target's visibility.
Application of Ancillary Data In Post-Classification to Improve Forest Area Estimates In A Landsat TM Scene
Holoviak, Brent Matthew (Virginia Tech, 2002-07-15)
In order to produce a more current inventory of forest estimates along with change estimates, the Forest Inventory Analysis (FIA) program has moved to an annual system in which 20% of the permanent plots in a state are surveyed. The previous system sampled permanent plots in 10-year intervals by sampling states sequentially in a cycle (Wayman 2001, USDA FIA). The move to an annual assessment has introduced the use satellite technology to produce forest estimates. Wayman et al (2001) researched the effectiveness of satellite technology in relation to aerial photo-interpretation, finding the satellite method to do an adequate job, but reporting over-estimations of forest area. This research extends the satellite method a step further, introducing the use of ancillary data in post-classification. The US Forest Service has well-defined definitions of forest and nonforest land-use in its (FIA) program. Using these definitions as parameters, post-classification techniques were developed to improve forest area estimates from the initial spectral classification. A goal of the study was to determine the accuracy of using readily available ancillary data. US Census data, TIGER street files, and local tax parcel data were used. An Urban Mask was created based on population density to mask out Forested pixels in a classified image. Logistic Regression was used to see if population density, street density, and land value were good predictors of forest/nonforest pixels. Research was also conducted on accuracy when using contiguity filters. The current filter used by the Virginia Department of Forestry (VDoF) was compared to functions available in ERDAS Imagine. These filters were applied as part of the post-classification techniques. Results show there was no significant difference in map accuracies at the 95% confidence interval using the ancillary data with filters in a post-classification sort. However, the use of ancillary data had liabilities depending on the resolution of the data and its application in overlay.
Application of Spectral Change Detection Techniques to Identify Forest Harvesting Using Landsat TM Data
Chambers, Samuel David (Virginia Tech, 2002-07-11)
The main objective of this study was to determine the spectral change technique best suited to detect complete forest harvests (clearcuts) in the Southern United States. In the pursuit of this objective eight existing change detection techniques were quantitatively evaluated and a hybrid method was also developed. Secondary objectives were to determine the impact of atmospheric corrections applied before the change detection, and the affect post-processing methods to eliminate small groups of misclassified pixels ("salt and pepper" effect) had on accuracy. Landsat TM imagery of Louisa County, Virginia was acquired on anniversary dates in both 1996 and 1998 (Path 16, Row 34), clipped to the study area boundary, and registered to one another. Previous to the change detection exercise, two levels of atmospheric corrections were applied to the imagery separately to produce three data sets. The three data sets were evaluated to determine what level of pre-processing is necessary for harvest change detection. In addition, eight change detection techniques were evaluated: 1) the 345 TM band differencing, 2) 35 TM band differencing, 3) NDVI differencing, 4) principal component 1 differencing, 5) selection of a change band in a multitemporal PCA, 6) tasseled cap brightness differencing, 7) tasseled cap greenness differencing, and 8) univariate differencing using TM band 7. A hybrid method that used the results from the eight previous techniques was developed. After performing the change detection, majority filters using window sizes of 3x3 pixels, 5x5 pixels, and 7x7 pixels were applied to the change maps to determine how eliminating small groups of misclassified pixels would affect accuracies. Accuracy assessments of the binary (harvested or not harvested) change maps were used to evaluate the accuracies of the various methods described using 256 validation points collected by the Virginia Department of Forestry. The atmospheric corrections did not seem to significantly benefit the change detection techniques, and in some cases actually degraded accuracies. Of the eight techniques applied to the original dataset, univariate differencing using TM band 7 performed the best with a 90.63% overall accuracy, while Tasseled Cap Greenness returned the worst result with an overall accuracy of 78.91%. Principal component 1 differencing and 35 differencing also performed well. The hybrid approach returned good results, but at its best returned an overall accuracy of 90.63%, matching the TM band 7 method. The majority filters using the 3x3 and 5x5 window sizes increased the accuracy in many cases, while the majority filter using the 7x7 window size degraded overall accuracy.
An ArcView tool for simulating Land Subdivision for Build Out Analysis
Wakchaure, Ashwini S. (Virginia Tech, 2001-05-22)
The objective of this paper is to develop a tool in ArcView for simulating the land subdivision process in order to simplify the process of build out analysis. Build out analysis is a valuable tool for evaluating the effectiveness of land regulations and performing impact analysis of development on the environment and other natural resources. The process involved in carrying out build out analysis involves dealing with various layers of spatial information, maps and tabular data. Geographical information systems (GIS) are very effective in handling spatial and tabular data. Analysis of various layers of information at the city level can be done simultaneously using GIS. However, GIS does not possess necessary tools to model future development on buildable land. Hence modeling of development is done using AutoCAD or similar drafting software. In addition, the modeling of development has to be done at a single parcel level, as parcel characteristics like size, shape, terrain, land use and zone greatly influence the probable pattern of subdivision of land parcel. This paper looks at the process of developing a subdivision layout in AutoCAD at a single parcel level. Based on the understanding of this process, a tool has been developed in ArcView, which enables a user to draw different arrangements of lots in gridiron pattern of development. This tool has been developed using Avenue. The layout developed using ArcView program is not as precise as the AutoCAD generated layout, however it is sufficient to simulate a probable subdivision layout pattern for a land parcel in less time.
Areal Modeling of Erosion for Environmental Nonpoint Applications (AMEENA)
Al-Smadi, Mohammad Ahmed (Virginia Tech, 2007-08-10)
Erosion and sediment delivery from upland areas to waterbodies is a major problem impacting water quality in the United States and elsewhere. Measures to reduce these impacts are either targeted at reducing erosion on-site or at reducing delivery of sediment to waterbodies. AMEENA (Areal Modeling of Erosion for Environmental Nonpoint Applications) is a spatially distributed model that estimates erosion and deposition on a watershed scale by predicting erosion and transport over the landscape surface. Erosion is predicted based on the Revised Universal Soil Loss Equation (RUSLE), and sediment transport capacity is estimated as a function of upslope flow volume, local gradient, and land use. Gross erosion is routed to edge-of-stream with a routing algorithm that iteratively compares available sediment with transport capacity on a cell by cell basis from ridge cells to stream cells. The model is implemented completely within a raster GIS to facilitate use of the model as a tool to readily evaluate impact of land use practices on sediment delivery to streams. AMEENA was validated using field data of net erosion and sediment deposition from three field studies. AMEENA predicted the spatial distribution of net erosion and deposition better than WaTEM/SEDEM which is a distributed parameter erosion model based on a similar modeling approach. AMEENA's suitability to simulate the impact of management practices such as filter strips and critical area planting was evaluated on plot (profile) scale and catchment scale simulations. Results of plot scale simulations were intuitive and the model proved more reasonable for these scenarios than did RUSLE2 and WEPP. The catchment scale study highlighted features of AMEENA that are not available in RUSLE2 and WEPP in terms of identifying erosion “hot spots” and the ability to utilize the explicit sediment flow path identification in locating best placement of off-site sediment control measures. Since AMEENA does not account for in-stream erosion processes, it is not suitable for simulating areas dominated by channel or gully erosion.
The Asian Tiger Mosquito (Aedes albopictus): Spatial, Ecological, and Human Implications in Southeast Virginia
Ratigan, Christopher William (Virginia Tech, 2000-01-28)
The overall theme that drove my research was the concern for public health and its possible compromise due to the colonization of large areas of the United States by the disease-vectoring Aedes albopictus. The main objective is to determine the elements that make an environment conducive to Aedes albopictus populations. Specifically, the objective of this research is to identify the socio-economic impact of Aedes albopictus on residents in the Hampton Roads area in southeast Virginia and determine if there is an identifiable environment in which A. albopictus could be found. Data were collected at the Census block group level (demographic variables) and at the single household level (survey and physical-cultural variables). The variables were then correlated (Pearson) and the results were analyzed. Only variables that were less than (.1) significance were examined. The following physical-cultural variables were found to be associated with the reduction of A. albopictus activity: having a sea breeze, being near an oceanfront, cutting the grass frequently, and keeping the overall neatness of a property high. Secondary variables that are related to the decrease in A. albopictus populations are sunny yards, yards with no containers that can hold water, and yards that contain coniferous trees versus deciduous trees. The primary socio-economic variables that can signify an environment with high A. albopictus activity are: lower house value and median rent value, lower levels of education, and a lower median income level. Other demographic variables that help determine the size of an A. albopictus population are (in order of significance): ethnicity (white or black), poverty/unemployed, owner/renter occupied, and the year a house was built. These secondary variables increase A. albopictus numbers if the following trends exist: high percent of persons in poverty and unemployed, higher percent of renter occupied homes, and older houses.
Assessing and Evaluating Recreation Resource Impacts: Spatial Analytical Approaches
Leung, Yu-Fai (Virginia Tech, 1998-02-09)
It is generally recognized that the magnitude of recreation resource impacts should be judged by their severity and spatial qualities, including extent, distribution, and association. Previous investigations, however, have primarily focused on assessing the severity of impacts, with limited examination of spatial qualities. The goal of this dissertation was to expand our understanding of the spatial dimension of recreation resource impacts and their assessment and evaluation. Two empirical data sets collected from a comprehensive recreation impact assessment and monitoring project in Great Smoky Mountains National Park provided the basis for the analyses. Three spatial issues were examined and presented as three papers, designed for journal submission. The purpose of the first paper was to improve our understanding of the dimensional structure and spatial patterns of camping impacts by means of multivariate analyses and mapping. Factor analysis of 195 established campsites on eight impact indicator variables revealed three dimensions of campsite impact: land disturbance, soil and groundcover damage, and tree-related damage. Cluster analysis yielded three distinctive campsite types that characterize both the intensity and areal extent of camping impacts. Spatial patterns and site attributes of these three campsite types and an additional group of primitive campsites were illustrated and discussed. The purpose of the second paper was to examine the influence of sampling interval on the accuracy of selected trail impact indicator estimates for the widely applied systematic point sampling method. A resampling-simulation method was developed and applied. Simulation results indicated that using systematic point sampling for estimating lineal extent of trail impact problems can achieve an excellent level of accuracy at sampling intervals of less than 100 m, and a reasonably good level of accuracy at intervals between 100 and 500 m. The magnitude of accuracy loss could be higher when the directions of loss are not considered. The responses of accuracy loss on frequency of occurrence estimates to increasing sampling intervals were consistent across impact types, approximating an inverse asymptotic curve. These findings suggest that systematic point sampling using an interval of less than 500 m can be an appropriate method for estimating the lineal extent, but not for estimating occurrence of trail impacts. Further investigations are called for to examine the generalizability of these results to other areas. The purpose of the third paper was to expand the scope of indices used for evaluating recreation resource impacts. Two specific objectives were to synthesize the recreation ecology and recreation resource management literature on the use of spatial indicators and indices, and to propose and apply selected spatial indices that are mostly lacking in the literature. Three spatial indices primarily adapted from the geography and ecology literature were proposed for application in recreation impact evaluation. Application results demonstrated that the Lorenz curve and associated Gini coefficient, and the linear nearest-neighbor analysis and associated LR ratio were effective in quantifying the spatial distribution patterns of trail impacts at landscape and trail scales, respectively. Application results of the third index, the impact association index, were less promising and require further refinements. Management implications and future directions of research were discussed in light of the findings of this dissertation. As the field of recreation ecology is emerging, this dissertation has demonstrated: (1) the value of recreation impact assessment and monitoring programs in providing data for examining the spatial dimension of impacts, and (2) the utility of spatial analytical approaches in understanding recreation impact assessment and evaluation.
Assessing and Evaluating Recreational Trails on Public Lands
Wimpey, Jeremy Felton (Virginia Tech, 2009-07-01)
This dissertation contains two journal articles; the first article (Chapter 2) evaluates the relative influences of use, managerial and environmental factors on trail width, from a survey of all formal trails in Acadia National Park, Maine, USA. Regression analyses of trail width data focus on increasing our understanding of the relationships among visitor use, environmental and managerial factors and trail width. In particular, regression modeling was used to evaluate the relative importance of factors that influence trail width along hiking trails. ANOVA analyses demonstrate differences in trail width based on trail surface type, and the presence or absence of trail borders. A novel approach of comparing intended widths to actual widths enabled us to look specifically at the avoidable and undesirable impacts associated with having a trail that is wider than intended. Informal trails (visitor created) represent a threat to the natural resources of protected natural areas around the globe. These trails can remove vegetation, displace wildlife, alter hydrology, alter habitat, spread invasive species, and fragment landscapes. The second article (Chapter 3) examines informal and formal trails within Great Falls Park, VA, a sub-unit of the George Washington Memorial Parkway, managed by the U.S. National Park Service. This study sought to answer three specific questions: 1) Are the physical characteristics and topographic alignments of informal trails significantly different from formal trails, 2) Can landscape fragmentation metrics be used to summarize the relative impacts of formal and informal trail networks on a protected natural area?, and 3) What can we learn from examining the spatial distribution of the informal trails within protected natural areas? Statistical comparisons between formal and informal trails in this park indicate that informal trails have less sustainable topographic alignments than their formal counterparts. Spatial summaries of the lineal and areal extent and fragmentation associated with the trail networks by park management zones compare park management goals to the assessed attributes. Hotspot analyses highlight areas of high trail density within the park and findings provide insights regarding potential causes for development of dense informal trail networks.
Assessing Coastal Plain Wetland Composition using Advanced Spaceborne Thermal Emission and Reflection Radiometer Imagery
Pantaleoni, Eva (Virginia Tech, 2007-05-03)
Establishing wetland gains and losses, delineating wetland boundaries, and determining their vegetative composition are major challenges that can be improved through remote sensing studies. In this study, we used the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) to separate wetlands from uplands in a study of 870 locations on the Virginia Coastal Plain. We used the first five bands from each of two ASTER scenes (6 March 2005 and 16 October 2005), covering the visible to the short-wave infrared region (0.52-2.185υm). We included GIS data layers for soil survey, topography, and presence or absence of water in a logistic regression model that predicted the location of over 78% of the wetlands. While this was slightly less accurate (78% vs. 86%) than current National Wetland Inventory (NWI) aerial photo interpretation procedures of locating wetlands, satellite imagery analysis holds great promise for speeding wetland mapping, lowering costs, and improving update frequency. To estimate wetland vegetation composition classs of the study locations, we generated a Classification and Regression Tree (CART) model and a Multinomial Logistic Regression (logit) model, and compared their accuracy in separating woody wetlands, emergent wetlands and open water. The overall accuracy of the CART model was 73.3%, while the overall accuracy of the logit model was 76.7%. Although the CART producer's accuracy (correct category classification) of the emergent wetlands was higher than the accuracy from the multinomial logit (57.1% vs. 40.7%), we obtained the opposite result for the woody wetland category (68.7% vs. 52.6%). A McNemar test between the two models and NWI maps showed that their accuracies were not statistically different. We conducted a sub-pixel analysis of the ASTER images to establish canopy cover of forested wetlands. The canopy cover ranged from 0 to 225 m2. We used visble-near-infrared ASTER bands, Delta Normalized Difference Vegetation Index, and a Tasselled Cap transformation in an ordinary linear regression (OLS) model. The model achieved an adjusted-R2 of 0.69 and an RMSE of 2.73% when the canopy cover is less than 16%. For higher canopy cover values, the adjusted-R2 was 0.4 and the RMSE was19.79%. Taken together, these findings suggest that satellite remote sensing, in concert with other spatial data, has strong potential for mapping both wetland presence and type.
Assessing the Long-term Impacts of White-nose Syndrome on Bat Communities Using Acoustic Surveys at Fort Drum Military Installation
Nocera, Tomas (Virginia Tech, 2018-06-12)
With declines in abundance and changing distribution of White-nose Syndrome (WNS)-affected bat species, increased reliance on acoustic monitoring is now the new "normal". As such, the ability to accurately identify individual bat species with acoustic identification programs has become increasingly important. Additionally, how bat distribution and habitat associations have changed at the local to sub-landscape scale in the post WNS environment is important to understand. The significance of these changes, relative to bat activity, may be based on the species-specific susceptibility to WNS. We used data collected from Fort Drum Military Installation, New York from the summers of 2003-2017 to analyze the accuracy of acoustic software programs, and assess the changes in relative bat activity, occupancy, and distribution induced by WNS. Our results indicate that continued acoustic monitoring of bat species, such as the little brown bat (Myotis lucifugus) in the Northeast, to assess ongoing temporal and spatial changes, habitat associations, and as a guide to direct future mist-netting should rely more on relative activity as the metric of choice. Furthermore, the continuous spread of WNS across North America will have strong negative effects on bat populations and communities, this study points to how individual species (both impacted and non-impacted) will respond to WNS. We believe that our results can help users choose automated software and MLE thresholds more appropriate for their needs to accurately address potential changes in communities of bat species due to impacts of WNS or other factors.
Assessing vulnerability and multi-hazard risk in the Nepal Himalaya
Aksha, Sanam Kumar (Virginia Tech, 2018-11-15)
Communities around the world are encountering unprecedented rates of change due to population growth, land use change, development, and increased social vulnerability to natural hazards. Understanding how physical processes and human vulnerability to natural hazards interact is a primary objective of researchers, policy makers, and disaster risk reduction practitioners in order to combat increases in natural hazard frequency and intensity. Nepal, a landlocked mountainous country spanning the central Himalayan region, has about 28 million inhabitants in 147,181 square kilometers. Nepal is exposed to a multitude of natural hazards, requiring individuals and communities to interact with and make decisions on risk acceptability on a day-to-day basis. In many cases, Nepal's geographic location, available resources (human, economic, and capital), and limited government capacity coalesce to turn natural hazards into disasters, resulting damaged infrastructure, economic disruptions, and death. This dissertation evaluates the geographic distribution of natural hazard mortality, quantifies social vulnerability to natural hazards, and models multi-hazard risk in the data deficient environment of Nepal. Chapter 1 conceptualizes relevant terms such as natural hazards, disaster, vulnerability, and risk before discussing the challenges associated with multi-hazard risk assessment in Nepal. Chapter 2 evaluates the spatial and temporal distribution of natural hazard mortalities at the village level using a publicly available disaster database. Results reveal that landslides were the deadliest disasters between 1971-2011. Chapter 3 identifies major social factors and processes that contribute to the vulnerability of individuals and communities using census data. Adapting the Social Vulnerability Index (SoVI) method developed for the US context, this chapter investigates the spatial distribution and clustering of various social vulnerabilities across the country. 'Renter and Occupation', 'Poverty and Poor Infrastructure', and 'Favorable Social Conditions' are three major components that influence social vulnerability in Nepal. Results indicate an interesting regional difference: the eastern and central Tarai are more vulnerable than western Tarai, whereas the eastern Hills and Mountains are less vulnerable than western Hills and Mountains. In Chapter 4, a model of risk from multiple natural hazards in the city of Dharan, Nepal, is presented. Freely available geospatial data in combination with socio-economic data collected from local government and secondary sources are used. Multi-hazard risk assessment is data intensive and requires considerable financial and human resources, which are lacking in Nepal. Results show that geospatial modeling techniques can be used to fill the gap and assist local officers and emergency managers in risk management. Cumulatively, this work offers new insights on natural hazards, vulnerability, risk, the use of geospatial technologies, and their inter-relationships. Research findings advance scholarly understandings of multi-hazard risk in general and particularly in the Nepali context. Additionally, this work is valuable to disaster practitioners who seek to implement more effective disaster risk reduction programs and policies.
Autonomous Vehicle Path Planning with Remote Sensing Data
Dalton, Aaron James (Virginia Tech, 2008-12-02)
Long range path planning for an autonomous ground vehicle with minimal a-priori data is still very much an open problem. Previous research has demonstrated that least cost paths generated from aerial LIDAR and GIS data could play a role in automatically determining suitable routes over otherwise unknown terrain. However, most of this research has been theoretical. Consequently, there is very little literature the effectiveness of these techniques in plotting paths of an actual autonomous vehicle. This research aims to develop an algorithm for using aerial LIDAR and imagery to plan paths for a full size autonomous car. Methods of identifying obstacles and potential roadways from the aerial LIDAR and imagery are reviewed. A scheme for integrating the path planning algorithms into the autonomous vehicle existing systems was developed and eight paths were generated and driven by an autonomous vehicle. The paths were then analyzed for their drivability and the model itself was validated against the vehicle measurements. The methods described were found to be suitable for generating paths both on and off road.
Beyond the Bezel: Utilizing Multiple Monitor High-Resolution Displays for Viewing Geospatial Data
Luebbering, Candice Rae (Virginia Tech, 2007-04-13)
Computers have vastly expanded capabilities for storing, creating, and manipulating spatial data, yet viewing area is still generally constrained to a single monitor. With this viewing window limitation, panning and zooming are required to view the full details of a map or image and, because of the large sizes of typical database, usually only in small portions. Multiple monitor configurations provide an attainable, low cost way for individuals to create large, high-resolution desktop displays. This increased screen real estate is particularly useful for viewing and interpreting rich and complex geospatial datasets because both context and amount of detail can be simultaneously increased, reducing reliance on virtual navigation to obtain the desired balance between context and scale. To evaluate the utility of multiple monitor displays for geospatial data, this experiment involved a variety of map and image reading tasks using both raster and vector data under three different monitor conditions: one monitor (1280 x 1024 pixels), four monitors (2560 x 2048 pixels), and nine monitors (3840 x 3072 pixels). Fifty-seven subjects took the test on one of the three display configurations. A computer program captured each subject's performance by recording answers, mouse click locations, viewing areas, tool usage, and elapsed time. A post-experiment questionnaire obtained additional qualitative feedback about subjects' experience with the tasks and display configuration. Overall, subjects did perform more efficiently on the larger display configurations as evidenced by a reduction in test completion time and in the amount of virtual navigation (mouse clicks) used to finish the test. Tool usage also differed among monitor conditions with navigation tools (zooming and panning) dominating on the single monitor while selecting tools (tools used to provide answers) predominated on the nine monitor display. While overall test results indicated the effectiveness of the larger displays, task-level analyses showed that specific performance varied considerably from task to task. The larger displays were the most efficient on some tasks, while other tasks showed similar results among all displays or even the single monitor as the most efficient. The best performance improvements occurred between the one and four monitor conditions, with the nine monitor condition mostly providing only modest additional improvement. Subjects rated the four monitor display size as the most ideal.
Calibration of an Artificial Neural Network for Predicting Development in Montgomery County, Virginia: 1992-2001
Thekkudan, Travis Francis (Virginia Tech, 2008-06-11)
This study evaluates the effectiveness of an artificial neural network (ANN) to predict locations of urban change at a countywide level by testing various calibrations of the Land Transformation Model (LTM). It utilizes the Stuttgart Neural Network Simulator (SNNS), a common medium through which ANNs run a back-propagation algorithm, to execute neural net training. This research explores the dynamics of socioeconomic and biophysical variables (derived from the 1990 Comprehensive Plan) and how they affect model calibration for Montgomery County, Virginia. Using NLCD Retrofit Land Use data for 1992 and 2001 as base layers for urban change, we assess the sensitivity of the model with policy-influenced variables from data layers representing road accessibility, proximity to urban lands, distance from urban expansion areas, slopes, and soils. Aerial imagery from 1991 and 2002 was used to visually assess changes at site-specific locations. Results show a percent correct metric (PCM) of 32.843% and a Kappa value of 0.319. A relative operating characteristic (ROC) value of 0.660 showed that the model predicted locations of change better than chance (0.50). It performs consistently when compared to PCMs from a logistic regression model, 31.752%, and LTMs run in the absence of each driving variable ranging 27.971% – 33.494%. These figures are similar to results from other land use and land cover change (LUCC) studies sharing comparable landscape characteristics. Prediction maps resulting from LTM forecasts driven by the six variables tested provide a satisfactory means for forecasting change inside of dense urban areas and urban fringes for countywide urban planning.
Canopy, terrain, and distance effects on Global Positioning System position accuracy
Deckert, Christopher J. (Virginia Tech, 1994-04-15)
A number of tests were conducted to determine the realizable accuracies of the Global Positioning System for natural resource conditions. The effects of terrain, forest canopy, number of consecutive position fixes, and PDOP on accuracy were evaluated. Position accuracies were determined for a total of 27 sites: three replicate sites selected for each of nine distinct conditions: three canopy (deciduous, coniferous, open) and three terrain (ridge, slope, valley) in all possible combinations. Each site was visited ten times over a span of eight months to collect position data, for ten replicates of 60, 100, 200, 300, and 500 position fixes. The mean differentially corrected positional accuracy for all sites was 4.35 meters with 95 percent of the positions estimated within 10.2 meters of the true value. The least accurate differential position data were observed at coniferous sites. Positional accuracy was higher for deciduous sites and the most accurate differential position data was collected at open sites. Accuracy increased with increasing number of position fixes. When the number of position fixes increased from 60 to 500, mean accuracy increased 46.7% at deciduous sites, 32.8% at coniferous sites, and 44.5% at open sites. The average time required by the GPS receiver to lock onto four satellites and begin collecting positions varied from one to two minutes. The most time was spent collecting position fixes at coniferous sites. No correlation was found between accuracy and the receiver's distance from the base-station. Nine replicates of 300 position fixes were averaged for six sites, which ranged from 43 kilometers to 247 kilometers from a Virginia Tech base-station. Mean accuracy ranged from 1.48 meters to 2.43 meters. GPS position data were evaluated for ease of conversion to GIS formats. Conversion was accomplished without problems.

Browsing by Author "Carstensen, Laurence W."

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