Investigating the neighborhood effect averaging problem (NEAP) in greenspace exposure: A study in Beijing

Abstract

Urban greenspaces are pivotal in enhancing the well-being and health of city residents. Accurate assessment of an individual's exposure to these natural settings is thus crucial in urban greenspace planning. However, the dynamic nature of human mobility, which determines the amount of greenspace exposure accessed over time and space, often leads to a divergence between the actual Mobility-Based Exposure (MBE) and the traditional Residence-Based Exposure (RBE). This discrepancy, encapsulated as the neighborhood effect averaging problem (NEAP), prompted us to examine the bias introduced by such discrepancy and its association with various human-based factors. This study delves into the complex interplay among the NEAP, individual mobility patterns, and demographic characteristics with fine-resolution estimations in Beijing, aiming to provide a nuanced understanding of the NEAP's influence. Uncovering heterogeneous patterns of disparity between RBE and MBE across distinct geographical realms and sociodemographic cohorts, and how such effects are mediated by populations with diverse mobility traits, the study illuminates the prevalence and complexity of the NEAP. Younger individuals, the employed population, those with larger activity spaces, high visitation diversity, and travel frequency, and residents living in areas with significant deviations from mean RBE levels experience a more pronounced NEAP impact. These insights contribute to a holistic grasp of the NEAP and underscore the imperative of inclusive greenspace urban planning that caters to the diverse mobility patterns and disparities among residents from different demographic groups, offering invaluable guidance for policy interventions to amplify greenspace exposure and address health disparities.