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Pengxiang Zhao

Researcher

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A Vector Field Approach to Estimating Environmental Exposure Using Human Activity Data

Author

  • Zijian Guo
  • Xintao Liu
  • Pengxiang Zhao

Summary, in English

Environmental exposure of people plays an important role in assessing the quality of human life. The most existing methods that estimate the environmental exposure either focus on the individual level or do not consider human mobility. This paper adopts a vector field generated from the observed locations of human activities to model the environmental exposure at the population level. An improved vector-field-generation method was developed by considering people’s decision-making factors, and we proposed two indicators, i.e., the total exposure indicator (TEI) and the average exposure indicator (AEI), to assess various social groups’ environmental exposure. A case study about the risky environmental exposure of coronavirus disease 2019 (COVID-19) was conducted in Guangzhou, China. Over 900 participants with various socioeconomic backgrounds were involved in the questionnaire, and the survey-based activity locations were extracted to generate the vector field using the improved method. COVID-19 pandemic exposure (or risk) was estimated for different social groups. The findings show that people in the low-income group have an 8% to 10% higher risk than those in the high-income group. This new method of vector field may benefit geographers and urban researchers, as it provides opportunities to integrate human activities into the metrics of pandemic risk, spatial justice, and other environmental exposures.

Department/s

  • Centre for Geographical Information Systems (GIS Centre)

Publishing year

2022-02-01

Language

English

Publication/Series

ISPRS International Journal of Geo-Information

Volume

11

Issue

2

Document type

Journal article

Publisher

MDPI AG

Topic

  • Geosciences, Multidisciplinary

Keywords

  • Environmental exposure
  • Mobility pattern
  • Spatial justice
  • Vector field

Status

Published

ISBN/ISSN/Other

  • ISSN: 2220-9964