Modern bike share systems (BSSs) allow users to rent from a fleet of bicycles at hubs across the designated service area. With clear evidence of cycling being a health-positive form of active transport, furthering our understanding of the underlying processes that affect BSS ridership is essential to continue further adoption. Using 286,587 global positioning system (GPS) trajectories over a 12-month period between January 1st, 2018 and December 31st, 2018 from a BSS called SoBi (Social Bicycles) Hamilton, the number of trips on every traveled link in the service area are predicted. A GIS-based map-matching toolkit is used to generate cyclists’ routes along the cycling network of Hamilton, Ontario to determine the number of observed unique trips on every road segment (link) in the study area. To predict trips, several variables were created at the individual link level including accessibility measures, distances to important locations in the city, proximity to active travel infrastructure (SoBi hubs, bus stops), and bike infrastructure. Linear regression models were used to estimate trips. Eigenvector spatial filtering (ESF) was used to explicitly model spatial autocorrelation. The results suggest the largest positive predictors of cycling traffic in terms of cycling infrastructure are those that are physically separated from the automobile network (e.g., designated bike lanes). Additionally, hub-trip distance accessibility, a novel measure, was found to be the most significant variable in predicting trips. A demonstration of how the model can be used for strategic planning of road network upgrades is also presented. / Thesis / Master of Science (MSc)

This descriptive research used the Health Belief Model (HBM) to assess HIV/AIDS knowledge, perceived severity, perceived susceptibility, and behavioral practices within the population throughout the State of Sonsonate, El Salvador. Geographic Information Systems (GIS) was also utilized to display the results of this population study. The study population was composed of 15-39 year olds consisting of a total sample size of 1,500 (250 participants from each of the six cities). The basis of this study was to evaluate where this population fit within the Health Belief Model (HBM) and also to practically represent the results pictorially. Also, this information was collected so that the government of El Salvador could see and understand where their educational deficits existed so that future programs could be established to alleviate these discrepancies. An instrument consisting of 65 items including demographics, knowledge, perceived severity, perceived susceptibility, and behavioral practices was used for the general population. The analysis of the data was two-fold using Geographic Information Systems (GIS) mapping and statistical analysis. GIS mapping was used to graphically pinpoint areas of knowledge deficit and misinformation about HIV/AIDS. Results were based on a general population of 1,454. Various indices were created to show the level of knowledge or frequency of safe behavioral practices. The Perceived Severity and Perceived Susceptibility sections were not aggregated into an index but rather treated as individual variables. An item analysis of the questionnaire found that on average the general population responded correctly to 78% of the knowledge questions. However, a total of 11 questions in the knowledge section had less 75% (n=385) of the general population answering correctly. Another 3 questions in the behavior section were also found to have less than 75% (n=385) indicating safe behavioral practices. Linear regression analyses were performed to explore correlations between the areas of demographics, knowledge level, perceived severity, and perceived susceptibility to safe behavior. GIS maps were created to pictorially show where this population's deficiencies were in regard to the HBM. This research helped to pinpoint where this population fits within the construct of the Health Belief Model so that future educational efforts can be targeted in geographic areas with the greatest need. This will help to move this sample toward behavioral change. / Ph. D.

The Rockfall Management System developed for Tennessee DOT (TennRMS)integrates a customized rockfall risk rating system, web-based GIS application, and rockfall database to provide a robust single interface for interacting with rock slope information. The system should prove to be a valuable tool for the proactive management of rock slopes. The most important use of the system will be to identify and prioritizing rock slopes with the greatest potential for rockfall in order to provide decision makers with all the necessary information they need to plan remediation efforts. Over time, TennRMS can be used to track costs and effectiveness of different remediation methods used on problem rock slopes. Three papers have been developed for publication in peer reviewed journals. The papers describe the work done in support of developing Tennessee's Rockfall Management System (TennRMS) and its components. The system can be described by its conceptual framework and actual implemented components. Asset management incorporating risk & decision analysis and knowledge management makes up the conceptual framework. The system components include a field data collection system using PDA's, a rockfall database and a web-based GIS interface. The papers articulate the development and implementation of the various components and to provide a detailed review of rockfall management systems as implemented over the past 15 years. / Ph. D.

This research involves the development of a comprehensive decision support system for energy planning through the increased use of renewable energy sources, while still considering the role of existing electricity generating facilities. This dissertation focuses on energy planning at the regional level, with the Greater Southern Appalachian Mountain region chosen for analysis due to the dependence on coal as the largest source of generation and the availability of wind and solar resources within the region. The first stage of this planning utilizes a geographic information system (GIS) for the discovery of renewable energy sources. This GIS model analyzes not just the availability of wind and solar power based on resource strength, but also considers the geographic, topographic, regulatory, and other constraints that limit the use of these resources. The model determines potential wind and solar sites within the region based on these input constraints, and finally the model calculates the cost and generation characteristics for each site. The results of the GIS model are then input into the second section of the model framework which utilizes a multi-objective linear programming (MOLP) model to determine the optimal mix of new renewable energy sources and existing fossil fuel facilities. In addition to the potential wind and solar resources discovered in the GIS, the MOLP model considers the implementation of solid wood waste biomass for co-fire at coal plants. The model consists of two competing objectives, the minimization of annual generation cost and the minimization of annual greenhouse gas emissions, subject to constraints on electricity demand and capital investment, amongst others. The model uses the MiniMax function in order to find solutions that consider both of the objective functions. The third major section of this dissertation analyzes three potential public policies — renewable portfolio standard, carbon tax, and renewable energy production tax credit — that have been used to foster increased renewable energy usage. These policies require minor modifications to the MOLP model for implementation. The results of these policy cases are then analyzed to determine the impact that these policies have on generation cost and pollution emissions within the region. / Ph. D.

This thesis presents an application of a geographical information system (GIS) in propagation prediction. The motivating force behind this work is the need for accurate and efficient site-specific propagation prediction tools for personal communication system (PCS) design. Site-specific information including terrain and building attributes is vast and complex, and needs specialized handling. A geographical information system provides these capabilities, and relieves the propagation analysis tools of the burden of data management. This work focused on harnessing the relevant abilities of a GIS for aiding the current propagation prediction software. GRASS (Geographical Resources Analysis Support System) GIS has been used for data handling, transformation, and analysis. Schemes and techniques were developed for operations on site-specific data as used in propagation prediction. Attention was paid to the types of data needed, available data sources and their formats, and the needs of the propagation analysis software. These schemes were implemented in the form of several new programs that have been integrated with GRASS. Data interfacing is the major function performed by these programs. Building and terrain data may now be exchanged between GRASS and AutoCAD, a computer-aided design software package. The data analysis powers of the GIS were used for estimating diffraction path loss over terrain. The results of propagation prediction can be displayed in a graphical manner through the GIS, and hardcopy outputs are possible. The work presented here sets the framework for the integration of various software modules that can combine to form a propagation prediction tool. / Master of Science

Recent research has indicated that submarine groundwater discharge (SGWD) occurs in the Chesapeake Bay, and that discharged groundwater can be contaminated with nutrients and toxic substances. Although discharge has been measured directly on a local level, a convenient method for determining the spatial distribution of SGWD on a large scale has not yet been devised. Although current watershed mass balance approaches have been used to estimate gross SGWD, this method cannot identify areas at high risk for contaminant input. A family of innovative computer mapping programs called Geographic Information Systems (GIS) have emerged from the software industry that serve not only as mapping tools but also as databases designed to manage spatial data) The GIS approach allows straightforward manipulation and presentation of data that is spatially related. In the research presented here, a GIS was applied to the problem of large-scale determination of SGWD and nutrient loads for the Eastern Shore of Virginia. Computerized data layers including land use, hydraulic gradient and soil permeability were used to create a GIS model of SGWD on Virginia's Eastern Shore. The model was used to predict spatial distribution of SGWD as well as the nutrient loading from nearshore agriculture and on-site waste treatment technologies. While sufficient field data for reliable calibration and verification of the model did not exist, the available data and the output of the GIS model were consistent. The methodology developed predicts that 90% of the impact from nearshore land use occurs in the southwestern quadrant of the Eastern Shore. In addition, the model determined locations where urban land use (septic tanks) may present a nutrient and coliform contamination danger. The model identified areas susceptible to contamination through discharge to a resolution of about 33 meters, showing that GIS can function as a local as well as regional management tool. The GIS framework is also expandable. The model can be modified to accommodate new data as research continues into the phenomenon of submarine groundwater discharge. This synthesis represents the first large-scale groundwater discharge analysis of the Eastern Shore and exists as part of an ongoing investigation to characterize groundwater-surface water interactions of the Eastern Shore. / Master of Science

Geographical Information Systems (GIS) is a worldwide growing technology, however it is not yet completely accepted. Of all of the business processes in an organization, marketing is perhaps one of the natural fitting-processes to apply GIS. Even though there is recent research regarding applications of GIS in the wood products industry, those applications are mostly related to biomass mapping and logistics issues. Little research has been conducted on the utilization of GIS as part of the marketing strategic plan in this industry. Thus, the main goal of this project is to understand GIS uses on marketing application in the wood products industry, specifically in the marketing mix strategic plan. The approach of this project consisted of the collection and analysis of data from secondary wood products industries in the state of Virginia. In addition, a case of study on current users of GIS applications was conducted. Once the data from the survey and the case study were collected, validated, and analyzed; applications and guidelines for the use of GIS in marketing activities were developed. The first application was the creation of a relational database to organize the information and to create an industry directory for secondary wood products industries. Secondly, clustering techniques were used to test if wood products companies cluster around certain geographical regions. Confirmation of the clustering led to the construction of an online map. Finally, guidelines were developed to describe how to use GIS in the marketing process of wood products firms. By increasing the knowledge and developing guidelines on GIS uses on marketing mix applications this study will help the wood products industry, other practitioners and the academic community, by providing insight of the industry, possible uses to simplify the strategic process and gain understanding of the environment among other. / Master of Science

Single digital-photo correction using the collinearity condition equations for a GIS application was investigated by control and test data from digital photos and USGS 1:24,000 topographic maps and by USGS 7.5-minute DEMs of two study areas, Prentiss, North Carolina and Blacksburg, Virginia. The collinearity equations were used to remove geometric errors caused by image tilt and relief, displacement. In addition to the study of geometric error in uncorrected and corrected digital photos, the impact of error in ground control points and error in DEM data on the accuracy of rectification was analyzed in terms of errors in point position, line length, and polygon area. Computer programs for single digital-photo correction using the collinearity equations and for impact analysis of errors in ground control and DEM data were developed. Point errors in uncorrected photos were tested by the affine transformation from UTM to photo coordinates by control points. Estimated error for the Prentiss photo was 14.599 meters and that for the Blacksburg photo was 11.252 meters. Due the poor distribution of control and test points, estimated errors in uncorrected photos were underestimated. Estimated error for the corrected photo of the Prentiss area was 11.397 meters and that for the Blacksburg area was 7.071 meters. Geometric errors in corrected digital photos were clearly not significantly greater than 12.192 meters. Error removed for the Blacksburg photo was significantly greater than zero and that for the Prentiss photo was not significantly greater than zero. Estimated removed errors were also underestimated. Errors in point position, line length, and polygon area of corrected digital photos were positively related to error in ground control points for photo orientation and error in DEM data for registration. The accuracy of ground control points has greater impact on point position and polygon area, and the accuracy of DEM data has greater impact on line length. The point position error, line length change, and polygon area change caused by random error within ±15 meters in ground control points were within 4 meters, 0.12% and 0.3% and those caused by random error within ±10 meters in DEM data of test features were within 2 meters, 0.11% and 0.0065%. It is both practical and accurate to use ground control points obtained from USGS 7.5-minute topographic maps and USGS 7.5-minute DEMs for single digital-photo correction by the collinearity equations for most GIS applications with spatial data layers obtained from USGS 1:24,000 topographic maps or smaller-scale maps for areas such as those studied here. / Master of Science

Water powered mills were a very important part of life in early America, and Augusta County, Virginia had an abundance of milling activity. Excellent records of milling activity, farm production, and road and farm locations for the period of 1880-1885 allowed a geographic information system (GIS) database to be formed so that spatial patterns could be verified and identified in the Riverheads district of the county. Service areas of 21 mills were identified by using a GIS to calculate the shortest road distance to surrounding farms. It was found that wheat, the main crop, was most likely shipped from the 369 farms to the closest mills. A correlation was also found between wheat production and distance from the mill, thus farmers closer to a mill were more likely to grow wheat. The study also demonstrates the usefulness of GIS analysis and computer cartography in historical, geographic research which has traditionally used theoretical approaches or lacked adequate data for GIS analysis. / Master of Science

The goal of the Aquatic Indicators of Land Condition (AILC) project is to develop analytical tools that integrate land condition information with stream condition for improved watershed management within the United States Bureau of Land Management (BLM). Based on the goal of the AILC, two objectives for this study were: to determine the effect of four GIS-derived distance measurements on potential relationships between common BLM landscape stressors (mining and grazing) and changes in benthic macroinvertebrate community structure; and to assess the effectiveness of individual questions on a commonly-used Bureau-wide qualitative stream assessment protocol, the proper functioning condition (PFC) assessment. The four GIS distance measurements assessed for biotic relevance included: straight-line distance, slope distance, flow length, and travel time. No significant relationships were found between the measured distance to stressor and macroinvertebrate community structure. However, the hydrological relevance of flow length and travel time are logically superior to straight-line and slope distance and should be researched further. Several individual questions in the PFC assessment had statistically significant relationships with the final reach ratings and with field-measured characteristics. Two of the checklist questions were significantly related to the number of cow droppings. This may indicate a useful and efficient measure of stream degradation due to grazing. The handling and use of the PFC assessment within the BLM needs further documentation and examination for scientific viability, and the addition of quantitative measurements to the PFC in determining restoration potential would be desirable. / Master of Science