Improving obesogenic environmental assessments with advanced geospatial methods

This thesis explores the intricate connections between the envir- onment and obesity. It develops and applies advanced geospatial methods to enhance the assessment of obesogenic environments and obesity risks. Its primary objective is to evaluate obesogenic environments and explore potential associations between environ- mental factors and obesity, crucial for effective obesity prevention. The thesis is structured around four key objectives. The first sub-objective involves an investigation into the current literature on the measurement of the built environment. Street View Imagery (SVI) and advanced urban visual intelligence technologies have transformed Built Environment Auditing (BEA) substantially, enabling large-scale auditing at a detailed geographical level. A me- ticulous review of 96 articles published before September 15, 2023, reveals key areas for improvement in SVI-based BEA. Recommend- ations include standardized datasets for more accurate audits, the integration of multi-source SVI for comprehensive assessments, and the design of auditing tools tailored to developing countries. Ad- dressing these areas enhances the potential of SVI in environmental auditing, as they contribute to a better understanding of the built environment’s health impact and facilitate informed decision-making in urban planning and public health initiatives. The second sub-objective focuses on analyzing exposure to in- creasing PM2.5 pollution, associated with rising morbidity and mor- tality. An ensemble machine learning model, integrating multi-source geospatial data, is presented to map hourly street-level PM2.5 concen- trations in the city of Nanjing, China, at a 100 m spatial resolution. The study concludes that mapping these concentrations reveals spati- otemporal trends, supporting the establishment of exposome studies. The third sub-objective addresses the development of a framework to evaluate Physical Activity (PA) opportunities (bikeability) in urban environments, aiming to enhance sustainable urban transportation planning. A framework is proposed that comprises safety, comfort, accessibility, and vitality sub-indices. It uses open-source data, ad- vanced deep neural networks, and GIS spatial analysis, to eliminate subjective evaluations and enhance efficiency. Experimental results in the city of Xiamen, China, demonstrate the framework’s effectiveness in identifying areas for improvement and enhancing cycling mobility. The fourth sub-objective investigates the associations between PA opportunities, specifically walkability, and obesity. Using a cross- sectional cohort from Nanjing, China. A Logistic regression model with a double robust estimator estimates the effects of walkability on obesity risks. A newly developed walkability index shows a sig- nificant negative association with obesity, particularly when using a data-based-buffer derived from web-mapping navigation that better represents individual activity spaces. These findings provide evidence for developing explicit strategies for obesity prevention. In summary, this thesis contributes to addressing the knowledge gap in health geography between obesogenic environments and obesity risks, employing advanced geospatial methods. The integration of multisource geospatial data, machine learning methods like deep learning in a GIS environment, and spatial statistics presents a major step forward

Geo-Information Technology and Its Applications

Geo-information technology has been playing an ever more important role in environmental monitoring, land resource quantification and mapping, geo-disaster damage and risk assessment, urban planning and smart city development. This book focuses on the fundamental and applied research in these domains, aiming to promote exchanges and communications, share the research outcomes of scientists worldwide and to put these achievements better social use. This Special Issue collects fourteen high-quality research papers and is expected to provide a useful reference and technical support for graduate students, scientists, civil engineers and experts of governments to valorize scientific research

Graduate Course Catalog [2006/09]

Graduate Course Catalog, 2006/09https://repository.stcloudstate.edu/gradcat/1033/thumbnail.jp

New Perspectives on Geothermal Energy Exploration and Evaluation of Geothermal Potential

This book describes interesting case studies of the exploration, characterization, and use of geothermal resources in Spain, Sweden, Italy, Croatia, China, Djibouti, and Canada. A new open-source software, with an easy-to-use graphical user interface, is applied to assess the deep geothermal potential of the Reus-Valls sedimentary basin in Spain. Then, a high-temperature borehole thermal energy storage facility at Linköping, Sweden, is described to shift excess heat generated from a waste incineration plant during the summer to the winter season. Next, a plastic plate heat exchanger was geometrically and thermodynamically modeled, optimized, and applied to a direct geothermal heating system for a building in Southern Italy. In the last European study, in Croatia, an unconventional hydrocarbon gas reservoir is analyzed (geothermal gradient of 49°C/km), in the geothermal field Velika Ciglena. Going down to Africa, the assessment of the geothermal resources in the Asal Rift (Djibouti) through multiphase flow and heat transfer simulations is presented. Moving to Asia, in the Chinese province of Guangdong, magnetotelluric profiles are used to interpret the crust and upper mantle structure and its geothermal implications. Then, in the remote Canadian Northern regions, uncertainty and risk evaluation of deep geothermal energy resources (> 4 km) for heat production and electricity generation are described. Finally, a literature review provides a comparison of geothermal projects in unconventional reservoirs in United Kingdom (Cornubian Batholith), Canada (Williston Sedimentary Basin), and Italy (Campi Flegrei Caldera)