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ISPRS Int. J. Geo-Inf. 2017, 6(9), 264;

Examining the Driving Factors Causing Rapid Urban Expansion in China: An Analysis Based on GlobeLand30 Data

School of Geography, Faculty of Geographical Science, Beijing Normal University, No. 19, Xinjiekouwai Street, Haidian District, Beijing 100875, China
Author to whom correspondence should be addressed.
Received: 29 June 2017 / Revised: 19 August 2017 / Accepted: 21 August 2017 / Published: 25 August 2017
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A large number of studies have dealt with the driven forces of land expansion, in which the remote sensing data and statistical data are most commonly used. The recent progress based on the statistical data have not been fully tested and discussed by the remote sensing data, and the remote sensing data used in the previous studies are usually interpreted within certain areas which is not convenient for global comparison. In this paper, the 30-m GlobalLand Cover Dataset (GlobeLand30) and socioeconomic data from 2000 to 2010 are adopted to investigate the factors driving impervious surface expansion in China based on a multilevel regression model. The GlobeLand30 provides a world-wide data framework which has a sound basis for regional comparison research. The variables are selected according to the existing research. Most, but not all, results are consistent with the previous studies when using impervious surface data of GlobeLand30. The main findings are: (1) the market demand caused by economic development, such as the increase in GDP from 2000 to 2010, plays a positive role in the expansion of developed land; (2) the land supply, as reflected by the ratio of the total of land transfer fees to fiscal revenue, also has a positive effect on the increase in impervious surfaces; (3) the percentage of the increase by private workers to the increase in total workers and certain other frequently-used variables are not relevant after controlling for land demand- and supply-related variables; and (4) the growth in impervious surfaces is related to the amount of the cultivated land, which implies the necessity for a more stringent farmland protection policy. Considering the need to compare across regions, we suggest that GlobeLand30 should be used for more studies to better understand the driving forces of land expansion. View Full-Text
Keywords: remote sensing data; developed land; driving forces; land supply; multilevel model remote sensing data; developed land; driving forces; land supply; multilevel model

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Liao, C.; Dai, T.; Cai, H.; Zhang, W. Examining the Driving Factors Causing Rapid Urban Expansion in China: An Analysis Based on GlobeLand30 Data. ISPRS Int. J. Geo-Inf. 2017, 6, 264.

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