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

Renner K, Schneiderbauer S, Pruß F, Kofler C, Martin D, Cockings S. Int. J. Disaster Risk Reduct. 2018; 27: 470-479.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1016/j.ijdrr.2017.11.011

PMID

unavailable

Abstract

Population data is commonly available for administrative units referring to the year of the last census. That level of aggregation and the static character of the information pose particular difficulties for spatial analysis in applications such as disaster management or spatial planning, for which much more time-sensitive population distributions are required. In this study, a flexible model to create dynamic gridded population data with a spatial resolution of 100m is implemented for the mountainous, hazard-prone and highly touristic region of the Autonomous Province of Bolzano, based on the integration of multiple data sources within an explicit spatio-temporal modelling framework. It is argued that dynamic gridded population information provides an improvement to the existing regional datasets. Our study shows that integrating daily and seasonal changes to the distribution of population improves exposure information for risk assessments especially in highly touristic areas.


Language: en

Keywords

Bolzano; Population dynamics; Population exposure; Population grid; Spatio-temporal modelling

NEW SEARCH


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