Geography Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2773
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Item A DISCOURSE ON CHILD MALNUTRITION: ANTHROPOMETRY, EMERGENT THEMES, QUALITY CONTROL MAXIMS, AND CLIMATIC AND ECONOMIC DETERMINANTS(2021) Sandler, Austin; Sun, Laixiang; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Malnutrition is a detrimental and significant plight for young children, responsible for 45% of all deaths among children worldwide. The aim of my dissertation is to assess the history of the science of anthropometry, synthesize the cumulative findings within the contemporary child malnutrition literature, dispute certain quality control maxims of anthropometric child-health surveys, and quantify the responsible latent factors of child malnutrition. These efforts are in service of a better characterization of malnutrition, a more reliable estimate of how many children are malnourished, and a better understanding of the geographical distribution and dynamic stochastic characteristics of malnutrition. It is essential to better understand malnutrition and its causes to suggest appropriate corrective policy. This dissertation consists of four principal essays, each from a unique conceptual perspective. The first essay is a historical and epistemological perspective of the science of anthropometry. I contextualize the legacy of child malnutrition efforts, including the link between eugenics and contemporary notions of “normal” child growth, the institutional power-struggle for child growth chart superiority, the obfuscated distinction between growth references and standards of growth, and the consequences of universal standards that do not reflect observable populations. The second essay is a systematic review of the literature, the largest of its kind to date. I synthesize 184 disaggregate empirical studies of the determinants of child malnutrition in Africa published since 1990. I find numerous opportunities for development within this corpus, in particular opportunities to enrich the scope, scale, and quantification of the field. The third essay is an analytical perspective on the quality control mechanisms applied to anthropometric surveys. I challenge the practice of rejecting datasets based on overlarge z-score standard deviation values and offer an alternative approach. The fourth essay is an econometric empirical analysis in Kenya and Nigeria of child malnutrition determinants. I use spatial Bayesian kriging and four-level random intercept hierarchical logit models to show the spatial heterogeneity of malnutrition prevalence, and to quantify various socio-economic and climatic determinants of child malnutrition. I find significant spatial and hierarchical relationships and determinants, which can move malnutrition rates by over 50%.Item GLOBAL BARE GROUND GAIN BETWEEN 2000 AND 2012 AND THE RELATIONSHIP WITH SOCIOECONOMIC DEVELOPMENT(2020) Ying, Qing; Hansen, Matthew C; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Bare ground gain -- the complete removal of vegetation due to land use changes, represents an extreme land cover transition that completely alters the structure and functioning of ecosystems. The fast expansion of bare ground cover is directly associated with increasing population and urbanization, resulting in accelerated greenhouse gas emissions, intensified urban heat island phenomenon, and extensive habitat fragments and loss. While the economic return of settlement and infrastructure construction has improved human livelihoods, the negative impacts on the environment have disproportionally affected vulnerable population, creating inequality and tension in society. The area, distribution, drivers, and change rates of global bare ground gain were not systematically quantified; neither was the relationship between such dynamics and socioeconomic development. This dissertation seeks methods for operational characterization of bare ground expansion, advances our understanding of the magnitudes, dynamics, and drivers of global bare ground gain between 2000 and 2012, and uncovers the implications of such change for macro-economic development monitoring, all through Landsat satellite observations. The approach that employs wall-to-wall maps of bare ground gain classified from Landsat imagery for probability sample selection is proved particularly effective for unbiased area estimation of global, continental, and national bare ground gain, as a small land cover and land use change theme. Anthropogenic land uses accounted for 95% of the global bare ground gain, largely consisting of commercial/residential built-up, infrastructure development, and resource extraction. China and the United States topped the total area increase in bare ground. Annual change rates of anthropogenic bare ground gain are found as a leading indicator of macro-economic change in the study period dominated by the 2007-2008 global financial crisis, through econometric analysis between annual gains in the bare ground of different land use outcomes and economic fluctuations in business cycles measured by detrended economic variables. Instead of intensive manual interpretation of land-use attributes of probability sample, an approach of integrating a pixel- and an object- based deep learning algorithms is proposed and tested feasible for automatic attribution of airports, a transportation land use with economic importance.