Literature DB >> 22252280

Applying GIS and fine-resolution digital terrain models to assess three-dimensional population distribution under traffic impacts.

Chih-Da Wu1, Shih-Chun Candice Lung.   

Abstract

Pollution exhibits significant variations horizontally and vertically within cities; therefore, the size and three-dimensional (3D) spatial distribution of population are significant determinants of urban health. This paper presents a novel methodology, 3D digital geography (3DIG) methodology, for investigating 3D spatial distributions of population in close proximity to traffic, thus the potential highly exposed population under traffic impacts. 3DIG applies geographic information system and fine-resolution (5 m) digital terrain models to obtain the number of building floors in residential zones of the Taipei metropolis; the vertical distribution of population at different floors was estimated based on demographic data in each census tract. In addition, population within 5, 10, 20, 50, and 100 m from the roadways was estimated. Field validation indicated that model results were reliable and accurate; the final population estimation differs only by 0.88% from the demographic database. The results showed that among the total 6.5 million Taipei residents, 0.8 (12.3%), 1.5 (22.9%), 2.3 (34.9), and 2.7 (41.1%) million residents live on the first or second floor within 5, 10, 20, and 50 m, respectively, of municipal roads. There are 22 census tracts with more than half of their residents living on the first or second floor within 5 m of municipal roads. In addition, half of the towns in Taipei city and county with >13.9% and 12.1% of residents live on the first and second floors within 5 m of municipal roads, respectively. These findings highlight the huge number of Taipei residents in close proximity to traffic and have significant implications for exposure assessment and environmental epidemiological studies. This study demonstrates that 3DIG is a versatile methodology for various research and policy planning in which 3D spatial population distribution is the central focus.

Mesh:

Year:  2012        PMID: 22252280     DOI: 10.1038/jes.2011.48

Source DB:  PubMed          Journal:  J Expo Sci Environ Epidemiol        ISSN: 1559-0631            Impact factor:   5.563


  2 in total

1.  Mapping the vertical distribution of population and particulate air pollution in a near-highway urban neighborhood: implications for exposure assessment.

Authors:  Chih-Da Wu; Piers MacNaughton; Steve Melly; Kevin Lane; Gary Adamkiewicz; John L Durant; Doug Brugge; John D Spengler
Journal:  J Expo Sci Environ Epidemiol       Date:  2013-10-02       Impact factor: 5.563

2.  An Improved Method of Determining Human Population Distribution Based on Luojia 1-01 Nighttime Light Imagery and Road Network Data-A Case Study of the City of Shenzhen.

Authors:  Qiang Zhou; Yeqing Xu; Yuanmao Zheng; Jinyuan Shao; Yinglun Lin; Haowei Wang
Journal:  Sensors (Basel)       Date:  2020-09-04       Impact factor: 3.576

  2 in total

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