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Spatial and Temporal Analyses of Human Population Dynamics and Social Vulnerability

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Global Health".

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 3917

Special Issue Editor


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Guest Editor
Department of Geography, University of Wisconsin-Milwaukee, Milwaukee, WI 53201, USA
Interests: GIS technology; spatial and statistical analyses; human population dynamics

Special Issue Information

Dear Colleagues,

With the increasing availability of massive data on human location and activities, studies on human population dynamics have moved beyond the location and distribution of human populations with inquiries into how human populations change over time, and how changing human populations affect related social processes. These massive data are still accumulating, and they include census data (e.g., U.S. decennial censuses and American Community Survey) and data from social media and mobile devices. The inquires can rest on the aggregates of the distribution and movement of individuals at different spatial and temporal scales ranging from intracity residential mobility, migration across regions, to immigration across countries. The inquiries can also be based on individual level identities, behaviors, and activities to examine how micro-environment factors, e.g., social organization and emerging technology, would affect large-scale aggregates. Human population dynamics is a fundamental driver of the ever-changing human society. It has perceived with causes and consequences, one of which is the social vulnerability of human society. How does human population dynamics affect the social vulnerability of human society to hazards? How can the social vulnerability be accurately measured? How does the emerging technologies (e.g., social media networks) and social organizations affect human population dynamics and social vulnerability?

This Special Issue seeks to publish research addressing the following broad aspects:

  • Spatial and temporal movement patterns in human population at different scales;
  • Contributing factors and consequences of human population migration;
  • Migration of socially vulnerable due to hazards or environmental change;
  • Patterns in Geographic mobility, especially, of the socially vulnerable;
  • The conceptual frameworks, approaches, and applications of social vulnerability;
  • The applications of new sensing technologies to human location, movement, activities, and behaviors;
  • The effects of social media on human population dynamics and social vulnerability.

Dr. Zengwang Xu
Guest Editor

Manuscript Submission Information

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Keywords

  • migration
  • georgaphic mobility
  • social vulnerability
  • hazards
  • social media
  • social sensing
  • movement patterns
  • environment migration

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Published Papers (1 paper)

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Research

20 pages, 4299 KiB  
Article
Evaluating Urban Vitality of Street Blocks Based on Multi-Source Geographic Big Data: A Case Study of Shenzhen
by Ziyu Wang, Nan Xia, Xin Zhao, Xing Gao, Sudan Zhuang and Manchun Li
Int. J. Environ. Res. Public Health 2023, 20(5), 3821; https://doi.org/10.3390/ijerph20053821 - 21 Feb 2023
Cited by 10 | Viewed by 3417
Abstract
Urban vitality is the comprehensive form of regional development quality, sustainability, and attractiveness. Urban vitality of various regions within the cities has difference, and the quantitative evaluation of urban vitality within the cities can help guide to future city constructions. Evaluation of urban [...] Read more.
Urban vitality is the comprehensive form of regional development quality, sustainability, and attractiveness. Urban vitality of various regions within the cities has difference, and the quantitative evaluation of urban vitality within the cities can help guide to future city constructions. Evaluation of urban vitality needs the combination of multi-source data. Existing studies have developed index method and estimation models mainly based on geographic big data to evaluate urban vitality. This study aims to combine remote sensing data with geographic big data to evaluate urban vitality of Shenzhen at street block scale and build the estimation model by random forest method. Indexes and random forest model were built, and some further analyses were conducted. The results were: (1) urban vitality in Shenzhen was high in the coastal areas, business areas, and new towns; (2) compared to indexes, the estimation model had advantages of more accurate results, combination of various data, and the ability to analyze feature contributions; and (3) taxi trajectory, nighttime light, and housing rental data had the strongest influence on urban vitality. Full article
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