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dc.contributor.authorChen, J.
dc.contributor.authorFan, W.
dc.contributor.authorLi, K.
dc.contributor.authorLiu, Xin
dc.contributor.authorSong, M.
dc.date.accessioned2018-12-13T09:11:20Z
dc.date.available2018-12-13T09:11:20Z
dc.date.created2018-12-12T02:46:35Z
dc.date.issued2019
dc.identifier.citationChen, J. and Fan, W. and Li, K. and Liu, X. and Song, M. 2019. Fitting Chinese cities’ population distributions using remote sensing satellite data. Ecological Indicators. 98: pp. 327-333.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/71771
dc.identifier.doi10.1016/j.ecolind.2018.11.013
dc.description.abstract

© 2018 Elsevier Ltd Remote sensing satellite data from 2012 to 2013 are used to fit the Chinese cities’ population distributions over the same period in order to verify the population distribution in China from a relatively objective perspective. Most scholars have used nighttime light data and vegetation indexes to fit the population distribution, but the fitting effect has not been satisfactory. In this paper, processed Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime light data, net primary productivity of vegetation (NPP), and average slope data were used to fit the population distribution from the three dimensions of economic growth, ecological environment, and topographic factors, respectively. The fitting effect was significantly improved compared with other studies (R2 values of 0.9244 and 0.9253 in 2012 and 2013, respectively). Therefore, this method provides a practical and effective way to fit the population distribution for remote cities or areas lacking census data. Furthermore, there is important practical significance for the government to formulate its population policies rationally, optimize the spatial distribution of population, and improve the ecological quality of the city.

dc.publisherElsevier
dc.titleFitting Chinese cities’ population distributions using remote sensing satellite data
dc.typeJournal Article
dcterms.source.volume98
dcterms.source.startPage327
dcterms.source.endPage333
dcterms.source.issn1470-160X
dcterms.source.titleEcological Indicators
curtin.departmentSustainability Policy Institute
curtin.accessStatusFulltext not available


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