Browsing by Author "Thapa, Bhuwan"

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    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., III
    Food 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.
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    Comparison of Sky View Factor Estimates using Digital Surface Models
    (2022-02) Adhikari, Bikalpa; Wilson, Jeffrey S.; Dwyer, Owen J.; Banerjee, Aniruddha; Thapa, Bhuwan
    Better 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).
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    Strategic placement of urban agriculture: A spatial optimization approach
    (Wiley, 2021) Thapa, Bhuwan; Banerjee, Aniruddha; Wilson, Jeffrey S.; Hamlin, Samantha; Geography, School of Liberal Arts
    Strategic placement of urban agriculture such as community gardens can expand alternate food supply, support physical activity, and promote social interactions. While social and health benefits are critical priorities when planning new urban agriculture locations, no widely accepted site selection methods have been established. We developed a spatial optimization model to identify new urban agriculture locations in the City of Indianapolis, Marion County, Indiana. Considering block groups with vacant parcels as potential locations, the study uses p-median optimization to identify the 25 best locations that would minimize travel from any block group in the city to potential garden locations. We weighted each block group based on food access and prevalence of obesity, where food access was characterized on three dimensions: economic, geographical, and informational. The model was simulated for three policy scenarios with equal, stakeholder-driven, and obesity-driven weights, and the results were compared with randomly selected locations. We found that optimally selected locations were 52% more efficient than randomly chosen locations in terms of the average distance traveled by residents based on the p-median solution. However, there was no significant difference in travel distance among the three policy scenarios. The spatial optimization model can help policymakers and practitioners strategically locate urban agriculture sites.