# Dynamic Population Distribution and Perceived Impact Area of the Tibet Dingri MS6.8 Earthquake Based on Mobile Phone Location Data

## TL;DR

This paper uses mobile phone data to study population movement and communication behavior after a major earthquake in Tibet, revealing how people responded differently based on the earthquake's impact.

## Contribution

The study introduces a novel rapid assessment method for earthquake impact areas using mobile phone location data and compares interpolation techniques for spatial analysis.

## Key findings

- Population distribution and mobile signal activity varied significantly post-earthquake, reflecting behavioral differences based on seismic impact.
- Mobile data decline zones correlated strongly with high-intensity regions, showing effectiveness in identifying affected areas within 30 minutes.
- Short-term communication surges occurred beyond 100 km from the epicenter, indicating differentiated behavioral responses.

## Abstract

Based on the collected mobile phone location data, this paper analyzes changes in four mobile location-based indicators and their spatiotemporal distribution characteristics before and after the earthquake, summarizing crowd movement patterns and communication behaviors after the MS6.8 Dingri earthquake. By comparing natural neighbor interpolation and Thiessen polygon interpolation methods, we explore novel rapid assessment approaches for earthquake perception ranges, combined with actual seismic intensity maps. The results indicate an uneven distribution of population and differing dynamics in mobile phone signal activity. This reflects different behavioral patterns and the potential perceived extent of the earthquake. Within 50 km of the epicenter, all four indicators showed varying degrees of decline post-earthquake, while areas beyond 100 km exhibited short-term surges, reflecting differentiated behavioral responses based on seismic impact severity. In areas experiencing strong shaking, risk avoidance behavior predominated, while in areas where shaking was noticeable but less severe, communication behavior was more prominent. Mobile data decline zones showed high spatial correlation with intensity VIII+ regions, proving their effectiveness as rapid indicators for identifying strongly affected areas. Notably, mobile location data enabled accurate identification of strongly affected zones within 30 min post-earthquake.