The Spatiotemporal Coupling Characteristics of Regional Urbanization and Its Influencing Factors: Taking the Yangtze River Delta as an Example

Xu, Dong; Hou, Guolin

doi:10.3390/su11030822

Cited by 54 publications

(41 citation statements)

References 39 publications

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“…For the calculation of the weight of the indexes, this paper first used the entropy method [57] to calculate the objective weight, the AHP (Analytic Hierarchy Process) [58] method to calculate the subjective weight, and then took the arithmetic mean of both as the final weight. As such, the subjective and objective weights were considered comprehensively.…”

Section: Cut Analysis Methodsmentioning

confidence: 99%

Cropland Use Transitions and Their Driving Factors in Poverty-Stricken Counties of Western Hubei Province, China

Xiang

Song

2019

Sustainability

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Agriculture is important for economic development in most poverty-stricken areas in China, but cropland use is facing challenges due to rapid industrialization and urbanization, causing serious issues for poverty alleviation and sustainable socioeconomic development. Cropland Use Transition (CUT) is one way to alleviate poverty and develop the economy in poverty-stricken areas. This paper chose 16 typical poverty-stricken counties in Western Hubei province as the case area. A morphology index system was established to evaluate CUT, and geographic information system software was used to analyze the temporal-spatial variations in CUT. Using the Radial Basis Function Neural Network (RBFNN) model, contributions of driving factors of population, economy, and industrial structure to CUT were analyzed. The results show that: (1) cropland use morphology can be divided into functional morphology and spatial morphology; (2) the spatial distribution of CUT was high in the north and low in the south, the temporal variation of CUT from 1995 to 2013 showed fluctuations, and the coefficient of CUT changed from 0.460 to 0.649 with a growth rate of 41%; (3) for the driving factors, population factors most significantly contributed to CUT, followed by industrial structure and economic factors. The results obtained in this study are in line with the findings of previous studies. The RBFNN model is suitable for evaluating the contributions of driving factors, which can solve the deficiency in previous studies caused by ignoring the internal relationship and target orientation of driving factors. This study suggests that poverty-stricken counties should narrow the urban–rural divide, encourage balanced labor and investment flow into cropland by formulating relevant economic policies, motivate farmers’ agricultural engagement, and use science and technology to promote CUT and the growth of the agricultural economy, poverty alleviation, and to coordinate urban–rural development.

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Section: Cut Analysis Methodsmentioning

confidence: 99%

Cropland Use Transitions and Their Driving Factors in Poverty-Stricken Counties of Western Hubei Province, China

Xiang

Song

2019

Sustainability

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“…Apart from developing transportation and other infrastructure and strengthening their industrial development, promoting the growth poles is a better strategy to promote provincial cooperation and achieve a high level of balanced development in the future. The primary task of achieving coupling coordination for these Low-Low areas may still involve the development of the economy [47]. These five cities as the growth poles would drive the economic and social development of the surrounding L-L areas.…”

Section: Discussionmentioning

confidence: 99%

Spatial Heterogeneity and Coupling of Economy and Population Gravity Centres in the Hengduan Mountains

Luo

Liu

et al. 2019

Sustainability

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The junction region of the Sichuan–Yunnan–Guizhou province (JRSYG) is a multinational community that includes the Hengduan mountainous areas, although its economy is lagging behind other regions in China. This study explored the spatial heterogeneity and coupling of economic and population gravity centres during the period 1995–2015, and determined the hotspots driving the economic development in the JRSYG region. We obtained the following results: (1) The global Moran’s I and the Moran scatter plots of the economy and population showed that the distribution of economy and population was a nature clustering. The scatter plots of the economy and population were mainly distributed in Quadrant III, with an L–L gathering. With the passage of time, the agglomeration and driving effects of the economy become stronger. (2) By the dynamic evolution process of the economy and population, the economy gravity centre (GE) and population gravity centre (GP) were approaching each other during the period 1995–2015. The equilibrium points showed an inverted U-shaped curve for the past few years. The spatial coupling of GE and GP increased every year. The balanced degree of regional development continuously improved. (3) The economic development level showed a polarisation pattern with a southwest growth pole and northeast growth pole. The point–axis spatial development pattern is presented, with two economic hotspots (Panzhihua and Luzhou) and three sub-hotspots (Xichang, Zhong shan, Zhaoyang). If further advantages from policy and infrastructure support are obtained, the hot poles can drive the social and economic development of the surrounding regions, which will alleviate regional differences in the future.

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“…Xu studied the coupling coordination relations among population, land, and economic urbanization, and between each pair of them. The research showed that economic urbanization was the main factor affecting the spatial-temporal difference in the overall coupling coordination degree [ 25 ]. Lin discussed the spatial distribution of cities in the process of rapid land urbanization and found that the land urbanization in China showed obvious spatial differences.…”

Section: Literature Reviewmentioning

confidence: 99%

Research on the Coupling Coordination Relationships between Urban Function Mixing Degree and Urbanization Development Level Based on Information Entropy

Xia

Lin

Ding

et al. 2020

IJERPH

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With the rapid development of urbanization, the blind expansion of urban space has led to a series of social problems. In this process, the degree of urban function mixing affects the urbanization development level, making it particularly important to study the degree of coupling coordination between the two aspects. In this paper, taking Beijing as an example, we use urban point of interest (POI) data and taxi GPS trajectory data to calculate the urban POIs’ spatial entropy and taxis’ temporal entropy, based on the information entropy. We use the POIs’ spatial entropy and taxis’ temporal entropy to measure the urban function mixing degree. Also, the model of coupling coordination degree is used to measure the degree of coupling coordination between the urban function mixing degree and the urbanization development level. The results indicate the following: First, the POIs’ spatial entropy and taxis’ temporal entropy have significant regional imbalances. On the whole, both show a declining pattern when moving from the central urban area to the outer suburbs. The urban function mixing degree and urbanization development level are also higher in the central urban area than in the outer suburbs. Second, the coupling coordination among the urbanization development level, POIs’ spatial entropy, and taxis’ temporal entropy is distributed unevenly across various regions, which means that the three types of coupling coordination are in balanced development in the central urban area, but in unbalanced development in the outer suburbs. Third, from the perspective of spatial correlation characteristics, the higher is the degree of spatial agglomeration, the higher are the urban function mixing degree and urbanization development level, and the higher is the coupling coordination degree among the urbanization development level, POIs’ spatial entropy, and taxis’ temporal entropy. Therefore, relevant departments should plan the construction of urban functional areas reasonably, according to the degree of coupling coordination between the urban function mixing degree and the urbanization development level in different regions, so as to realize the healthy and sustainable development of a city.

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The Spatiotemporal Coupling Characteristics of Regional Urbanization and Its Influencing Factors: Taking the Yangtze River Delta as an Example

Cited by 54 publications

References 39 publications

Cropland Use Transitions and Their Driving Factors in Poverty-Stricken Counties of Western Hubei Province, China

Cropland Use Transitions and Their Driving Factors in Poverty-Stricken Counties of Western Hubei Province, China

Spatial Heterogeneity and Coupling of Economy and Population Gravity Centres in the Hengduan Mountains

Research on the Coupling Coordination Relationships between Urban Function Mixing Degree and Urbanization Development Level Based on Information Entropy

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