2018
DOI: 10.3390/su10051490
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Quantifying the Spatio-Temporal Dynamics of Rural Settlements and the Associated Impacts on Land Use in an Undeveloped Area of China

Abstract: Rapid urbanization and economic growth in China have accelerated changes in rural settlements and associated land-use types that are expected to alter ecological services and the environment. Relevant studies of the dynamics of rural settlements and corresponding rural land-use changes are in short supply, however, especially in undeveloped areas in China. This study, therefore, investigated the spatio-temporal dynamics of rural settlements and their impacts on other land-use types by using 30 m rural settleme… Show more

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Cited by 14 publications
(8 citation statements)
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References 45 publications
(93 reference statements)
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“…The growth trend of settlements will continue in China at a rapid pace before 2030 [30][31][32]. There is continuing needs for frequent monitoring of human settlement growth.…”
Section: Discussionmentioning
confidence: 99%
“…The growth trend of settlements will continue in China at a rapid pace before 2030 [30][31][32]. There is continuing needs for frequent monitoring of human settlement growth.…”
Section: Discussionmentioning
confidence: 99%
“…The development of network and information technology shortens the distance between rural areas and the market, improves the opportunity of external learning, and thus promotes the development of rural areas [10]. With the integration of new disciplines and new technologies, the spatial agglomeration of rural settlements has become a research hotspot [11][12][13][14][15][16][17][18][19].…”
Section: Literature Reviewmentioning
confidence: 99%
“…The kernel density estimation method is suitable for visual representation of spatial point patterns, and this method studies the distribution characteristics of points by examining the spatial variation of the point density in the regular area [68,69]. Kernel density analysis tools in arcGIS10.2 is used to calculate the density of elements in their surrounding neighborhoods.…”
Section: Kernel Densitymentioning
confidence: 99%