A Vector Field Approach to Estimating Environmental Exposure Using Human Activity Data
(2022) In ISPRS International Journal of Geo-Information 11(2).- Abstract
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... (More)
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.
(Less)
- author
- Guo, Zijian ; Liu, Xintao and Zhao, Pengxiang LU
- organization
- publishing date
- 2022-02-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Environmental exposure, Mobility pattern, Spatial justice, Vector field
- in
- ISPRS International Journal of Geo-Information
- volume
- 11
- issue
- 2
- article number
- 135
- publisher
- MDPI AG
- external identifiers
-
- scopus:85124830135
- ISSN
- 2220-9964
- DOI
- 10.3390/ijgi11020135
- language
- English
- LU publication?
- yes
- id
- 9973845d-774c-4c59-a066-f8ba6f5e6db7
- date added to LUP
- 2022-05-19 09:42:37
- date last changed
- 2023-05-15 12:27:09
@article{9973845d-774c-4c59-a066-f8ba6f5e6db7,
abstract = {{<p>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.</p>}},
author = {{Guo, Zijian and Liu, Xintao and Zhao, Pengxiang}},
issn = {{2220-9964}},
keywords = {{Environmental exposure; Mobility pattern; Spatial justice; Vector field}},
language = {{eng}},
month = {{02}},
number = {{2}},
publisher = {{MDPI AG}},
series = {{ISPRS International Journal of Geo-Information}},
title = {{A Vector Field Approach to Estimating Environmental Exposure Using Human Activity Data}},
url = {{http://dx.doi.org/10.3390/ijgi11020135}},
doi = {{10.3390/ijgi11020135}},
volume = {{11}},
year = {{2022}},
}