an innovative context-based crystal-growth activity space method for environmental exposure assessment: a study using gis and gps trajectory data collected in chicago

Clicks: 384
ID: 221358
2018
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #25 of 642 articles by views in archives of biochemistry and biophysics

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 642 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Scholars in the fields of health geography, urban planning, and transportation studies have long attempted to understand the relationships among human movement, environmental context, and accessibility. One fundamental question for this research area is how to measure individual activity space, which is an indicator of where and how people have contact with their social and physical environments. Conventionally, standard deviational ellipses, road network buffers, minimum convex polygons, and kernel density surfaces have been used to represent people’s activity space, but they all have shortcomings. Inconsistent findings of the effects of environmental exposures on health behaviors/outcomes suggest that the reliability of existing studies may be affected by the uncertain geographic context problem (UGCoP). This paper proposes the context-based crystal-growth activity space as an innovative method for generating individual activity space based on both GPS trajectories and the environmental context. This method not only considers people’s actual daily activity patterns based on GPS tracks but also takes into account the environmental context which either constrains or encourages people’s daily activity. Using GPS trajectory data collected in Chicago, the results indicate that the proposed new method generates more reasonable activity space when compared to other existing methods. This can help mitigate the UGCoP in environmental health studies.
Reference Key
wang2018internationalan Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Jue Wang;Mei-Po Kwan;Yanwei Chai
Journal archives of biochemistry and biophysics
Year 2018
DOI
10.3390/ijerph15040703
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.