Doctoral Dissertation Research: The Socioeconomic and Spatio-Temporal Dimensions of the Geography of Food Access

该博士论文研究项目将通过评估人们的日常活动、城市出行的时空维度以及人口和社会经济特征如何影响不同人群获取食物的方式，来研究食物获取和粮食安全问题。将特别注意低收入和处境不利人口获得粮食和营养援助服务的能力。该项目将提供有关食物获取地理学、时间地理学和地理位置科学的新知识，为更好地理解食物获取的复杂性提供新的视角，明确地将旅行模式与社会经济特征结合起来，而不是依赖于更传统、更简单的方法，即侧重于家庭与食物商店之间的空间接近度和距离。该项目将为低收入人群、老年人和其他有特殊需求的弱势群体获得食物和营养援助服务的相关旅行问题提供新的见解，新的空间优化模型将有助于定位科学文献的研究，这些文献主要关注空间背景，而忽略了空间供需的时间变化。该项目将为服务和设施规划提供一个更合适的规划机制，其中包括人口需求的空间和时间格局。该项目的重点是低收入和其他弱势群体的粮食获取，这将为寻求改善粮食获取和服务的机构、团体和政策制定者提供见解。由于这位博士生正在与当地政府机构合作，她将提供易于获取的模型和研究结果，帮助该机构确定提供食品和营养援助的最佳地点和时间窗口。虽然该项目是在亚利桑那州图森市进行的，但项目的发现和结果将适用于许多其他环境。作为博士论文研究改进奖，该奖项还将提供支持，使有前途的学生建立一个强大的独立研究生涯。在这个项目的过程中，博士生将调查人们的日常活动和旅行模式是如何影响他们对是否、在哪里、何时获取食物的决定的。她将研究低收入人口获得食品援助服务的时空模式，并将其与一般人口的食品获取模式进行比较。她还将开发和测试新的模式，将人们的日常旅行模式纳入食品和营养援助计划。她将使用一个独特的家庭旅行数据集，其中包含详细的时空旅行活动，以及由紧急食品援助计划赞助的紧急食品服务数据。紧急食品援助计划是一项联邦资助的计划，旨在帮助补充低收入人口的饮食，以在短期内缓解饥饿。学生将在不同的食物获取点进行问卷调查、访谈和焦点小组研究，以确定旅行模式和弱势群体的需求。在项目的最后阶段，她将开发空间优化模型，将出行动态纳入服务设施规划。

This doctoral dissertation research project will investigate food access and food security issues by assessing how people's daily activities, the spatial and temporal dimensions of their urban trip-making, and their demographic and socioeconomic characteristics affect the ways food is accessed by different populations. Special attention will be focused on the ability of low-income and disadvantaged populations to access food and nutrition-assistance services. The project will provide new knowledge regarding the geography of food access, time geography, and location science by providing a new perspective for better understanding the complexity of food access that explicitly incorporates travel patters with socioeconomic characteristics rather than relying on more traditional, simplistic measures that focused on spatial proximity and distance between homes and food stores. The project will provide new insights into travel-related issues associated with access to food and nutrition-assistance services for the low-income population, the elderly, and other disadvantaged groups with special needs, and the new spatial optimization model will contribute to the literature in location science that largely has focused on the spatial context and ignored the temporal variation of supply and demand across space. The project will yield a more suitable planning mechanism for service and facility planning that incorporates the spatial and temporal patterns of the population demand. The project's emphasis on food access for low-income and other disadvantaged populations will offer insights to agencies, groups, and policy makers seeking to improve access and service to food. Because the doctoral student is working with a local government agency, she will make readily accessible models and findings that can help the agency determine the best sites and time windows for providing food and nutrition assistance. Although this project is being conducted in Tucson, Arizona, project findings and outcomes will be adaptable for many other settings. As a Doctoral Dissertation Research Improvement award, this award also will provide support to enable a promising student to establish a strong independent research career.During the course of this project, the doctoral student will investigate how people's decisions about whether, where, and when to obtain food are affected by their daily activities and travel patterns. She will examine the space-time access patterns of low-income population for food-assistance services, and she will compare them with the food-access patterns of the general population. She also will develop and test new models that incorporate people's daily travel patterns into planning for food and nutrition assistance. She will use a unique household travel dataset with detailed space-time travel activities as well as data on emergency food services sponsored by The Emergency Food Assistance Program, a federally sponsored program that helps supplement the diets of low-income population in order to relieve hunger on a short-term basis. The student will conduct questionnaires, interviews, and focus group studies at diverse food-access points to identify travel patterns and the needs of the disadvantaged populations. In the final stage of the project, she will develop spatial optimization models will be developed that incorporate travel dynamics into service-facility planning.