Quantifying mobility-based seasonal individual heat exposure and the NEAP using multi-source spatiotemporal data

Under the dual drivers of global climate change and urbanization, heat waves have become one of the severe challenges to urban residents' health. This study investigates the neighborhood effect averaging problem (NEAP) across different socioeconomic status groups and seasons by integrating mobile phone signaling data, high-resolution land surface temperature remote sensing data, and cumulative exposure modeling. Using Hangzhou as the study area, we compared residents' mobility-based exposure (MBE) and residence-based exposure (RBE) based on mobility trajectory data from 5,747 (summer) and 6,167 (winter) residents. The study reveals: (1) Approximately 65% of residents experienced heat exposure mean reversion at both seasons, strongly validating the existence of the NEAP in heat exposure; (2) Human mobility behavior tends to reduce heat exposure levels in summer (MBE: 39.75°C, RBE: 39.85°C) while increasing exposure levels in winter (MBE: 13.89°C, RBE: 13.79°C); (3) Different socioeconomic status groups exhibited significantly different exposure patterns, with low socioeconomic status residents showing more pronounced NEAP in summer and the opposite in winter, while low SES groups faced higher heat exposure risks during summer. This study overcomes the limitations of traditional survey methods' insufficient spatial coverage and high costs, revealing the systematic regulatory effect of human mobility behavior on heat exposure. It also provides case evidence for developing social equity and urban climate adaptation policies. • We examined how the NEAP shapes heat exposure in Hangzhou, China. • We compared the differences among social groups and seasons. • Human mobility reduced heat exposure in summer while increasing it in winter. • High SES residents experienced less extreme heat in summer. • Low SES residents encountered higher heat exposure risks.