2017
DOI: 10.3390/su9020189
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Overall Urban–Rural Coordination Measures—A Case Study in Sichuan Province, China

Abstract: Focusing on urban-rural development issues, this paper analyzes the necessity of coordinated development between the narrowing gap and integral development. An overall urban-rural development dynamic model aimed at two major objectives is pointed out. A principal component analysis (PCA)-Grey Entropy measurement model is proposed to evaluate urban-rural coordination from economic development, social security, public services, and environmental quality perspectives. In this model, principal component analysis (… Show more

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Cited by 17 publications
(19 citation statements)
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“…Wu and Wang [34] utilized RS, GIS techniques and analytic hierarchy process (AHP) method to set up the assessment indices of landscape resources around rural-urban regions in southern Jiangsu Province, China. Zhu et al applied a Principal Component Analysis (PCA) and Grey Entropy measurement model to evaluate urban-rural coordination by considering the indices of economic, social security, public services, and environmental quality [35]. Liang and Peng used AHP to examine the success factors of autonomous landscape development in rural areas, covering 8 criteria and 28 sub-criteria [36].…”
Section: Introductionmentioning
confidence: 99%
“…Wu and Wang [34] utilized RS, GIS techniques and analytic hierarchy process (AHP) method to set up the assessment indices of landscape resources around rural-urban regions in southern Jiangsu Province, China. Zhu et al applied a Principal Component Analysis (PCA) and Grey Entropy measurement model to evaluate urban-rural coordination by considering the indices of economic, social security, public services, and environmental quality [35]. Liang and Peng used AHP to examine the success factors of autonomous landscape development in rural areas, covering 8 criteria and 28 sub-criteria [36].…”
Section: Introductionmentioning
confidence: 99%
“…With combined consideration of economic level, median values of type II with 65, 90, and Figure 1 showed an example of a Lorenz curve. The Gini coefficient is the ratio of the area A to the area (A+B) [18,19], as calculated in Equation (2). The Gini coefficient could be approximated from the curve using the trapezoidal rule in which the area B in Figure 1 was calculated by the sum of all trapezoids.…”
Section: Data Sourcesmentioning
confidence: 99%
“…The Gini coefficient could be approximated from the curve using the trapezoidal rule in which the area B in Figure 1 was calculated by the sum of all trapezoids. = 1 (2) where Xi was the cumulative proportion of various provinces. Rural and urban regions of 31 provinces was ranked by their burden values from lowest to highest, which were distributed with equal proportion.…”
Section: Data Sourcesmentioning
confidence: 99%
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“…This is the premise followed in this research, that is, many variables have been compiled to later obtain the most significant and the correlation between them through PCA. Moreover, from this statistical method, initial effective indexes of selected variables and then several comprehensive indexes [27] that allow us to know which variables are really significant are obtained.…”
Section: Principal Component Analysismentioning
confidence: 99%