The rapid growth of online food delivery is transforming urban meal access, with drones emerging as a novel mobility solution capable of bypassing ground-level congestion and infrastructure constraints. While drones offer a potential complement to traditional riders, it remains unclear how this delivery mode affects spatial patterns of online meal accessibility and its equity implications, particularly under building constraints and varying drone service shares. To address this gap, this study develops an analytical framework that integrates building-constrained drone path planning with the Gaussian-based two-step floating catchment area (G2SFCA) method. Using Shenzhen as a case study, we model hypothetical drone service share scenarios, ranging from zero to full service contribution, to quantify resulting changes in the population distribution and equity of online meal accessibility. The simulation results indicate lower spatial inequality in modeled online meal accessibility under drone delivery, with the clearest advantages in peripheral areas and under short delivery time thresholds. Compared to rider delivery, drone delivery demonstrates greater potential to overcome ground-based limitations in areas with sparse road networks. Furthermore, as the assumed drone service share increases, the population share at the lower end of the reference accessibility distribution decreases, while the middle accessibility groups expand and overall accessibility inequality declines. Overall, the proposed framework advances accessibility measurement for urban drone delivery systems and provides spatial planning evidence for identifying peripheral areas that warrant further operational and policy evaluation.
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Li et al. (2026) studied this question.
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