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China Population Distributions at Multiple Geographical Scales and Their Correlates
Liu, X.1; Wang, J. F.2; Christakos, G.3,4; Liao, Y. L.2
2019-09-01
Source PublicationJOURNAL OF ENVIRONMENTAL INFORMATICS
ISSN1726-2135
Volume34Issue:1Pages:15-27
Corresponding AuthorWang, J. F.(wangjf@lreis.ac.cn)
AbstractMost 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 small-scale 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.
KeywordChina population distributions correlates of population distribution multiple geographical scales spatial analysis spatial filter
DOI10.3808/jei.201900414
WOS KeywordWATER-RESOURCES ; SURFACE ; SIMULATION ; MODELS ; OPTIMIZATION ; DENSITY ; CLIMATE ; IMAGERY ; TRENDS
Indexed BySCI
Language英语
Funding ProjectNSFC[4127404] ; MOST[2012CB955503]
Funding OrganizationNSFC ; MOST
WOS Research AreaEnvironmental Sciences & Ecology
WOS SubjectEnvironmental Sciences
WOS IDWOS:000474810100002
PublisherINT SOC ENVIRON INFORM SCI
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/58475
Collection中国科学院地理科学与资源研究所
Corresponding AuthorWang, J. F.
Affiliation1.Curtin Univ, Curtin Univ Sustainabil Policy Inst CUSP, Bentley, WA 6102, Australia
2.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
3.Zhejiang Univ, Ocean Coll, Inst Isl & Coastal Ecosyst, Hangzhou 310058, Zhejiang, Peoples R China
4.San Diego State Univ, Dept Geog, San Diego, CA 92182 USA
Recommended Citation
GB/T 7714
Liu, X.,Wang, J. F.,Christakos, G.,et al. China Population Distributions at Multiple Geographical Scales and Their Correlates[J]. JOURNAL OF ENVIRONMENTAL INFORMATICS,2019,34(1):15-27.
APA Liu, X.,Wang, J. F.,Christakos, G.,&Liao, Y. L..(2019).China Population Distributions at Multiple Geographical Scales and Their Correlates.JOURNAL OF ENVIRONMENTAL INFORMATICS,34(1),15-27.
MLA Liu, X.,et al."China Population Distributions at Multiple Geographical Scales and Their Correlates".JOURNAL OF ENVIRONMENTAL INFORMATICS 34.1(2019):15-27.
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