SAFETYLIT WEEKLY UPDATE

We compile citations and summaries of about 400 new articles every week.
RSS Feed

HELP: Tutorials | FAQ
CONTACT US: Contact info

Search Results

Journal Article

Citation

Tominga A, Silm S, Orru K, Vent K, Klaos M, Võik EJ, Saluveer E. Int. J. Disaster Risk Reduct. 2023; 96: e103887.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.ijdrr.2023.103887

PMID

unavailable

Abstract

Key to strong disaster management practices is to have a clear understanding of people's whereabouts in disaster areas. One novel method for retrieving this information near real time is mobile positioning data. The goals of this research were to develop a methodology for identifying de facto populations and population groups in potential disaster areas, evaluate their spatio-temporal variation, and assess the applicability of the associated statistics in disaster management. Population groups - residents and temporary residents, workers, foreign and domestic tourists, regular and transit visitors - were identified based on Estonian historical mobile positioning data, where the details of stays and trips are provided based on longitudinal mobility behaviour. The main findings included that population changes follow clear week-hourly rhythms for de facto populations, residents and workers, but not for tourists and temporary residents. There are distinctive and identifiable geographical differences in how population group presence changes over time. Rescue workers asserted that the methodology of population statistics enabled them to assess population presence and composition in areas more precisely than registry-based approaches. This should evacuation planning, resource allocation and communication activities while preparing for and responding to disasters.


Language: en

Keywords

Crisis management; Mobile positioning data; Population statistics

NEW SEARCH


All SafetyLit records are available for automatic download to Zotero & Mendeley
Print