Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China.
Int J Environ Res Public Health. 2018 Feb 27;15(3):405. doi: 10.3390/ijerph15030405.
With the growing interest in studying the characteristics of people's access to the food environment and its influence upon individual health, there has been a focus on assessing individual food exposure based on GPS trajectories. However, existing studies have largely focused on the overall activity space using short-period trajectories, which ignores the complexity of human movements and the heterogeneity of the spaces that are experienced by the individual over daily life schedules. In this study, we propose a novel framework to extract the exposure areas consisting of the localized activity spaces around daily life centers and non-motorized commuting routes from long-term GPS trajectories. The newly proposed framework is individual-specific and can incorporate the internal heterogeneity of individual activities (spatial extent, stay duration, and timing) in different places as well as the dynamics of the context. A pilot study of the GeoLife dataset suggests that there are significant variations in the magnitude as well as the composition of the food environment in different parts of the individual exposure area, and residential environment is not representative of the overall foodscape exposure.
随着人们对研究获取食物环境特征及其对个体健康影响的兴趣日益浓厚，人们越来越关注基于 GPS 轨迹来评估个体的食物暴露情况。然而，现有的研究主要集中在使用短期轨迹的整体活动空间上，这忽略了人类运动的复杂性和个体在日常生活时间表中所经历的空间异质性。在这项研究中，我们提出了一个新的框架，从长期 GPS 轨迹中提取由日常生活中心周围的局部活动空间和非机动通勤路线组成的暴露区域。新提出的框架是个体特定的，可以将个体活动的内部异质性（空间范围、停留时间和时间）以及环境动态纳入不同地点。对 GeoLife 数据集的试点研究表明，个体暴露区域的不同部分的食物环境在规模和组成上都存在显著差异，居住环境并不能代表整体食物景观的暴露情况。
