A New Index to Assess Vulnerability to Regional Shrinkage (Hollowing out) Due to the Changing Age Structure and Population Density

이, 지민; Suh, Kyo

doi:10.3390/su13169382

Cited by 5 publications

(2 citation statements)

References 9 publications

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“…In recent years, research on the changing use of rural construction lands has attracted increasing attention from scholars, especially regarding the rural hollowing-out phenomenon. At present, research considering the hollow villages in China mainly focuses on their formation mechanisms [10][11][12][13], influencing factors [14][15][16][17], driving-force mechanisms [11,13,18], degree measurements [19][20][21], and comprehensive land remediation [22][23][24]. For example, Wang et al [11] believed that traditional hollowing in rural areas was mainly formed by a combination of land, population, and industry.…”

Section: Research Progress Of Rural Hollowingmentioning

confidence: 99%

Decoupling Analysis between Rural Population Change and Rural Construction Land Changes in China

Zhang

Jie

Song

et al. 2022

Land

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Developing countries account for about 86.5% of the world’s population and are experiencing rapid urbanization. Globally, the increase in the urban population is generally accompanied by the expansion of the latter and construction lands, as well as the reduction in the rural population and rural construction lands. However, with the rapid development of urbanization in China, the rural population has decreased, while the proportion of rural construction lands has increased, resulting in a significant waste of land resources. In order to quantitatively characterize the degree of deviation between the permanent rural population and rural construction lands based on the 2009–2016 demographic data and land survey data in China, we comprehensively used the decoupling model and the coordination degree model to analyze the temporal change characteristics, spatial distribution law, and the degree of deviation of rural construction land areas and the number of rural permanent residents. Firstly, according to the decoupling model, the type of decoupling between the area of rural construction lands and the number of rural permanent residents at the national scale was strongly negative. Secondly, according to the coordination degree model, the coordination type between rural construction land areas and the rural resident population was uncoordinated; at the provincial scale, the coordination system involved one city and one district (Beijing and the Tibet Autonomous Region) and the basic coordination of two cities (Tianjin and Shanghai). Xinjiang and Qinghai belonged to the reconcilable type, and the other 25 provinces belonged to the uncoordinated type. Finally, according to the comprehensive measurement model, the number of rural permanent residents and rural construction lands showed two types of decoupling: highly strong negative decoupling incoordination and moderately and weakly strong negative decoupling incoordination.

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Section: Research Progress Of Rural Hollowingmentioning

confidence: 99%

Decoupling Analysis between Rural Population Change and Rural Construction Land Changes in China

Zhang

Jie

Song

et al. 2022

Land

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“…However, identifying the population hollowing out issues are more complicated than a single socio-economic phenomenon, and the concept of population hollowing out needs to be comprehensively described using multi-source data based on multiple perspectives. Additionally, previous studies on population hollowing out were mainly concentrated on its connotation and formation mechanism [34], evolution law and stage features [35], affecting factors and driving forces [36,37], reclamation potential and measure [38], policy-making, et al [39][40][41][42]. Overall, most published research focused on the quantitative determination and regional spatial heterogeneity of population hollowing out at political boundary scale on a single time cross-section.…”

Section: Introductionmentioning

confidence: 99%

Identifying Population Hollowing Out Regions and Their Dynamic Characteristics across Central China

et al. 2022

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Continuous urbanization and industrialization lead to plenty of rural residents migrating to cities for a living, which seriously accelerated the population hollowing issues. This generated series of social issues, including residential estate idle and numerous vigorous laborers migrating from undeveloped rural areas to wealthy cities and towns. Quantitatively determining the population hollowing characteristic is the priority task of realizing rural revitalization. However, the traditional field investigation methods have obvious deficiencies in describing socio-economic phenomena, especially population hollowing, due to weak efficiency and low accuracy. Here, this paper conceives a novel scheme for representing population hollowing levels and exploring the spatiotemporal dynamic of population hollowing. The nighttime light images were introduced to identify the potential hollowing areas by using the nightlight decreasing trend analysis. In addition, the entropy weight approach was adopted to construct an index for evaluating the population hollowing level based on statistical datasets at the political boundary scale. Moreover, we comprehensively incorporated physical and anthropic factors to simulate the population hollowing level via random forest (RF) at a grid-scale, and the validation was conducted to evaluate the simulation results. Some findings were achieved. The population hollowing phenomenon decreasing gradually was mainly distributed in rural areas, especially in the north of the study area. The RF model demonstrated the best accuracy with relatively higher R2 (Mean = 0.615) compared with the multiple linear regression (MLR) and the geographically weighted regression (GWR). The population hollowing degree of the grid-scale was consistent with the results of the township scale. The population hollowing degree represented an obvious trend that decreased in the north but increased in the south during 2016–2020 and exhibited a significant reduction trend across the entire study area during 2019–2020. The present study supplies a novel perspective for detecting population hollowing and provides scientific support and a first-hand dataset for rural revitalization.

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Contribution of the Built Environment to Inclusiveness. A Case Study in a Rural Area

Ruá¹,

Huedo²,

Arín³

et al. 2023

Lecture Notes in Civil Engineering

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A New Index to Assess Vulnerability to Regional Shrinkage (Hollowing out) Due to the Changing Age Structure and Population Density

Cited by 5 publications

References 9 publications

Decoupling Analysis between Rural Population Change and Rural Construction Land Changes in China

Decoupling Analysis between Rural Population Change and Rural Construction Land Changes in China

Identifying Population Hollowing Out Regions and Their Dynamic Characteristics across Central China

Contribution of the Built Environment to Inclusiveness. A Case Study in a Rural Area

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