The Effects of Environmental Risk Factors on City Life Cycle: A Link Analysis

Erkan Isikli*, Alp Ustundag, Emre Cevikcan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Due to rapid industrialization and urbanization, social economy develops in an unparalleled speed, while it certainly fosters the consumption of natural resources and the pressure to protect the ecological environment. Hence, there is a two-way relationship between the well-being of humans and the natural environment. In this study, link analysis techniques along with multivariate statistical analysis were employed to discover the effects of environmental risk factors on city life cycle, where suicides, immigration, and emigration were considered as the fundamental indicators of how cities evolve. Association rules, classification trees, MANOVA, and linear discriminant analysis were applied to data on air quality, socioeconomic development, and demographical factors belonging to the cities of Turkey. The results indicate that socioeconomic development levels of cities differ along attraction and life satisfaction dimensions. People tend to choose a city with better development level and better air quality in order to increase their life satisfaction. Additionally, developed cities are less likely to have issues with air quality and citizens who live in a poorly developed city are least satisfied with their lives.

Original languageEnglish
Pages (from-to)1379-1394
Number of pages16
JournalHuman and Ecological Risk Assessment (HERA)
Volume21
Issue number5
DOIs
Publication statusPublished - 4 Jul 2015

Bibliographical note

Publisher Copyright:
© 2015, Copyright © Taylor & Francis Group, LLC.

Keywords

  • association rule mining
  • classification trees
  • demographics
  • environmental risk factors
  • multivariate statistics
  • population parameters

Fingerprint

Dive into the research topics of 'The Effects of Environmental Risk Factors on City Life Cycle: A Link Analysis'. Together they form a unique fingerprint.

Cite this