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doi:10.3808/jei.201900414
Copyright © 2017 ISEIS. All rights reserved

China Population Distributions at Multiple Geographical Scales and Their Correlates

X. Liu1, J. F. Wang2,*, G. Christakos3, and Y. L. Liao2

  1. Curtin University Sustainability Policy Institute (CUSP), Curtin University, Bentley WA 6102, Australia
  2. The State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Nature Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  3. Institute of Island & Coastal Ecosystems, Ocean College, Zhejiang University, Hangzhou, 310058, China; and Department of Geog raphy, San Diego State University, California, USA

*Corresponding author. Tel.: +86 10 64888965; fax: +86 10 64889630. E-mail address: wangjf@lreis.ac.cn (J. F. Wang).

Abstract


Most population distribution studies have focused on a single spatial resolution scale, thus, leading to a limited representation of the “real-world”. The present work, instead, proposes a “zoom lens” approach to detect and remove localized variation while retaining the general population distribution trends at multiple resolution scales. Different “focal length optics” are able to eliminate the unnecessary spatial details and filter out the underlined trend at the specified resolution. As spatial resolution scale decreases, the general trend and local variation of population distribution can be identified from the fine resolution to the national level. On the basis of smallscale analysis, it was shown that high-density population in China is roughly aligned with an oblique trend line along the Heihe–Tengchong Line, which provides a mathematical foundation for it. It was also found that the positive relationship between correlates and population distribution became more significant at the national scale. Topographic elevation has the largest negative impact on population distribution at the country level, whereas water accessibility has the largest effect on population distribution at any resolution. Furthermore, by combining the “zoom lens” approach with geographic weighted regression, the population distribution correlates (main roads, railways, live green vegetation, elevation, relief amplitude, rivers and lakes) were studied. A significant deterioration of accessibility to main roads and water in certain areas was identified at the national scale, which was not detected without “zoom lens” approach. Therefore, this study demonstrated that correlation or any other relationship may vary at different spatial scales of study.

Keywords: China population distributions, correlates of population distribution, multiple geographical scales, spatial analysis, spatial filter


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