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Geography Department Theses and Dissertations
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About the MS GIS Program
Rapid growth has occurred in the field of geographic information during the last two decades. Stimulated by advances in the collection, storage and analysis of data, a new discipline has emerged - Geographic Information Science. Geographic Information Science involves research both “on” and “with” spatial technologies including geographic information systems (GIS), remote sensing, and the global positioning system (GPS). At the core of Geographic Information Science is the integration of these technologies and their application to problems of spatial analysis. The foundational theory and principles of Geographic Information Science are based in the discipline of Geography. However, virtually all fields (from engineering, to medicine, science, business, social sciences and humanities) are now embracing Geographic Information Science in both theoretical and applied research.
Program Objectives
The Masters of Science in Geographic Information Science (MS GIS) integrates a suite of core courses with internship and independent research experiences to provide advanced training in the field of Geographic Information Science and its applications. Students completing the MS GIS will:
- develop, manage and analyze spatial data using field and laboratory techniques
- engage the rapidly expanding body of literature devoted to spatial data analysis and the application of geographic technologies
- apply geographic technologies creatively in real-world settings to answer questions about spatial patterns and processes
More on Masters in GIS requirements: http://www.iupui.edu/~geogdept/graduate/msgis.html
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Browsing Geography Department Theses and Dissertations by Title
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Item Augmenting Indiana's groundwater level monitoring network: optimal siting of additional wells to address spatial and categorical sampling gaps(2014-11-21) Sperl, Benjamin J.; Banerjee, Aniruddha; Lulla, Vijay O.; Bein, Frederick L. (Frederick Louis), 1943-Groundwater monitoring networks are subject to change by budgetary actions and stakeholder initiatives that result in wells being abandoned or added. A strategy for network design is presented that addresses the latter situation. It was developed in response to consensus in the state of Indiana that additional monitoring wells are needed to effectively characterize water availability in aquifer systems throughout the state. The strategic methodology has two primary objectives that guide decision making for new installations: (1) purposive sampling of a diversity of environmental variables having relevance to groundwater recharge, and (2) spatial optimization by means of maximizing geographic distances that separate monitoring wells. Design objectives are integrated in a discrete facility location model known as the p-median problem, and solved to optimality using a mathematical programming package.Item Availability of Supermarkets in Marion County(2010-07-20T15:32:53Z) Heintzelman, Asrah; Banerjee, Aniruddha; Wilson, Jeffrey S. (Jeffrey Scott), 1967-; Ottensmann, John R.Concern over significant increase in obesity has prompted interdisciplinary research to address the physical food environment in various regions. Empirical studies analyze units of geography independently of each other in studying the impact of the built environment in the health of a region. However, we know that geographical spaces have neighbors and these adjacent areas should be considered in analytical analysis that attempt to determine the effects present. This research incorporates the first neighbor influences by developing a refined hierarchical regression model that takes spatial autocorrelation and associated problems into account, based on Relative Risk of corporate supermarkets, to identify clustering of corporate supermarkets in Marion County. Using block groups as the unit of analysis, 3 models are run respectively incorporating population effect, environment effect, and interaction effects: interaction between population and environmental variables.Lastly, based on network distance to corporate supermarkets as a cost matrix, this work provides a solution to increase supermarkets in an optimal way and reduce access issues associated with these facilities. Ten new sites are identified where policy should be directed towards subsidizing entry of corporate supermarkets. These new sites are over and above the existing block groups that house corporate supermarkets. This solution is implemented using TransCAD™Item Beyond Food Deserts: Assessing the Impact of Public Transit Availability Change on Spatial Access to Food(2021-03) Katz, Brandon P.; Wilson, Jeffrey S.; Johnson, Daniel P.; Thapa, Bhuwan; Dwyer, Owen J., IIIFood access is a dimension of food security that many struggle with even in high- income countries, which is a contributing factor to chronic diet-related disease. Inequalities in economic access to food has been addressed in public policy for several decades, but spatial access to food has only been seriously studied and addressed by policy for the past twenty-five years. After the food desert metaphor emerged, it was promptly accepted as a standard measure of food access for governments and a basis for policies created to address inequalities. Conceptual criticisms and methodological limitations of the metaphor have led the study of spatial access to food towards newer methods that measure food access more realistically and assist in the development and assessment of intervention strategies to inform policy decisions. This thesis describes the history of the food desert metaphor from its emergence until its adoption in US public policy, the conceptual criticisms and methodological limitations that surround it, and offers an analysis that measures the impact of change in the availability of public transportation on spatial access to food for various population subgroups that are more at risk of food insecurity in Marion County, Indiana. Results demonstrate that policies and plans designed without consideration for food access have an impact on it nevertheless, and that policymakers and planners can leverage such strategies to better coordinate efforts across government to reduce inequalities in spatial access to food and food insecurity overall.Item Comparing Methods for Estimation of Daytime Population in Downtown Indianapolis, Indiana(2011-08-23) Bell, Karen Denise; Wilson, Jeffrey S. (Jeffrey Scott), 1967-; Banerjee, Aniruddha; Johnson, Daniel P. (Daniel Patrick), 1971-This paper compares two new methods for estimating daytime population against two existing models within downtown Indianapolis in Marion County, Indiana. The two existing models consist of the 2009 USA Daytime Population model created by ESRI and the LandScan Global Population Project developed by the Oak Ridge National Laboratory. A parking study of downtown Indianapolis, as prepared by the City of Indianapolis, Division of Metropolitan Development, is the basis of the first new method of estimating daytime population. The second method is a direct count of the daytime population using a methodology previously developed. Additionally, these four population estimates will be compared when applied to a scenario involving a hypothetical toxic gas plume.Item Comparing Spatial Measures of the Built Environment for Health Research(2008-03-07T13:35:29Z) Hoch, Shawn C.; Wilson, Jeffrey S. (Jeffrey Scott), 1967-; Liu, Gilbert; Wiehe, SarahResearch on the association between health and the built environment often delineates environmental exposure using different spatial forms and distances surrounding points of interest, such as residences or schools. Examples from the literature include Euclidian and network buffers, administrative and census boundaries, and other arbitrary geographies, such as grid cells. There is a lack, however, of reports that describe the justifications or implications for using different methods. This research compares different forms and distances for measuring environmental variables surrounding residential locations in the context of adult walking behavior in Marion County, Indiana. Walkability index and vegetation greenness variables were evaluated within 400-meter, 1-kilometer, and 2-kilometer Euclidian and network buffers, census block groups and tracts, and 805- X 805-meter grid cells. Results of analyses using each of these methods to test walkability and greenness as correlates of self-reported walking behavior were compared. Significant differences were observed in measurements of environmental variables as a function of both size and form. There were also significant differences between spatial measure methods when measuring components of walkability and NDVI. Census geographies, widely used in the public health literature, yielded environmental variable measurements differently than did similarly-sized residence-based measure methods. In logistic regressions, the walkability index did not exhibit a significant relationship with self-reported walking behavior. NDVI exhibited a negative relationship with self-reported walking, although the relationship was reversed and significant when stratifying by residential density.Item Comparison between high-resolution aerial imagery and lidar data classification of canopy and grass in the NESCO neighborhood, Indianapolis, Indiana(2014) Ye, Nan; Johnson, Daniel P. (Daniel Patrick), 1971-; Bein, Frederick L. (Frederick Louis), 1943-; Lulla, Vijay O.Urban forestry is a very important element of urban structures that can improve the environment and life quality within the urban areas. Having an accurate classification of urban forests and grass areas would help improve focused urban tree planting and urban heat wave mitigation efforts. This research project will compare the use of high – resolution aerial imagery and LiDAR data when used to classify canopy and grass areas. The high – resolution image, with 1 – meter resolution, was captured by The National Agriculture Imagery Program (NAIP) on 6/6/2012. Its coordinate system is the North American Datum of 1983 (NAD83). The LiDAR data, with 1.0 – meter average post spacing, was captured by Indiana Statewide Imagery and LiDAR Program from 03/13/2011 to 04/30/2012.The study area is called the Near East Side Community Organization (NESCO) neighborhood. It is located on the east side of downtown Indianapolis, Indiana. Its boundaries are: 65 interstate, East Massachusetts Avenue, East 21st Street, North Emerson Avenue, and the rail road tracks on the south of the East Washington Street. This research will also perform the accuracy assessment based on the results of classifications using high – resolution aerial imagery and LiDAR data in order to determine and explain which method is more accurate to classify urban canopy and grass areas.Item A comparison of geocoding baselayers for electronic medical record data analysis(2014-01-16) Severns, Christopher Ray; Wilson, Jeffrey S. (Jeffrey Scott), 1967-; Johnson, Daniel P. (Daniel Patrick), 1971-; Martin, Pamela A.Identifying spatial and temporal patterns of disease occurrence by mapping the residential locations of affected people can provide information that informs response by public health practitioners and improves understanding in epidemiological research. A common method of locating patients at the individual level is geocoding residential addresses stored in electronic medical records (EMRs) using address matching procedures in a geographic information system (GIS). While the process of geocoding is becoming more common in public health studies, few researchers take the time to examine the effects of using different address databases on match rate and positional accuracy of the geocoded results. This research examined and compared accuracy and match rate resulting from four commonly-used geocoding databases applied to sample of 59,341 subjects residing in and around Marion County/ Indianapolis, IN. The results are intended to inform researchers on the benefits and downsides to their selection of a database to geocode patient addresses in EMRs.Item Comparison of Sky View Factor Estimates using Digital Surface Models(2022-02) Adhikari, Bikalpa; Wilson, Jeffrey S.; Dwyer, Owen J.; Banerjee, Aniruddha; Thapa, BhuwanBetter comprehension of the Urban Heat Island study requires information on the natural as well as built characteristics of the environment at high spatial resolution. Sky View Factor (SVF) has been distinguished as a significant parameter for Local Climate Zone (LCZ) classification based on environmental characteristics that influence the urban climate at finer spatial scales. The purpose of this thesis was to evaluate currently available data sources and methods for deriving continuous SVF estimates. The specific objectives were to summarize the characteristics of currently available digital surface models (DSMs) of the study region and to compare the results of using these models to estimate SVF with three different raster-based algorithms: Horizon Search Algorithm in R-programming (Doninck, 2018), Relief Visualization Toolbox (RVT) (Žiga et al., 2016), and the Urban Multi-scale Environmental Predictor (UMEP) plugin in QGIS (Lindberg, et al., 2018).Item Comparison of Urban Tree Canopy Classification With High Resolution Satellite Imagery and Three Dimensional Data Derived From LIDAR and Stereoscopic Sensors(2008-08-22T13:59:51Z) Baller, Matthew Lee; Wilson, Jeffrey S. (Jeffrey Scott), 1967-; Tedesco, Lenore P.; Li, LinDespite growing recognition as a significant natural resource, methods for accurately estimating urban tree canopy cover extent and change over time are not well-established. This study evaluates new methods and data sources for mapping urban tree canopy cover, assessing the potential for increased accuracy by integrating high-resolution satellite imagery and 3D imagery derived from LIDAR and stereoscopic sensors. The results of urban tree canopy classifications derived from imagery, 3D data, and vegetation index data are compared across multiple urban land use types in the City of Indianapolis, Indiana. Results indicate that incorporation of 3D data and vegetation index data with high resolution satellite imagery does not significantly improve overall classification accuracy. Overall classification accuracies range from 88.34% to 89.66%, with resulting overall Kappa statistics ranging from 75.08% to 78.03%, respectively. Statistically significant differences in accuracy occurred only when high resolution satellite imagery was not included in the classification treatment and only the vegetation index data or 3D data were evaluated. Overall classification accuracy for these treatment methods were 78.33% for both treatments, with resulting overall Kappa statistics of 51.36% and 52.59%.Item CONFOUNDING CONSTITUENTS IN REMOTE SENSING OF PHYCOCYANIN(2008-08-22T13:53:38Z) Vallely, Lara Anne; Wilson, Jeffrey S. (Jeffrey Scott), 1967-; Tedesco, Lenore P.; Li, LinThis project examines the impact of confounding variables that have limited the accuracy of remotely predicting phycocyanin in three Indiana drinking and recreational water reservoirs. In-situ field reflectance spectra were collected from June to November 2006 over a wide range of algal bloom conditions using an ASD Fieldspec (UV/VNIR) spectroradiometer. Groundtruth samples were analyzed for chlorophyll a, phycocyanin, total suspended matter, and other water quality constituents. Previously published spectral algorithms for the detection of phycocyanin were evaluated against lab measured pigment concentrations using linear least squares regression. Algorithm performance varied across study sites (best performing models by reservoir resulted in r2 values of 0.32 to 0.84). Residuals of predicted versus measured pigment concentrations were analyzed against concentration of potential confounding water constituents. Residual analysis revealed optically active constituents contributed between 25% and 95% of original phycocyanin model errors. Inclusion of spectral variables into models to account for significant confounders resulted in improved spectral estimates of phycocyanin (r2 = 0.56 to 0.93).