Spatial Coupling Relationship and Driving Mechanism of Population and Economy in Rural Areas in Qinling-Daba Mountains, China

Xiao, Jie; Qiao, Jiajun; Han, Dong; Liu, Yang; Pan, Tao

doi:10.1007/s11769-023-1379-4

Cited by 3 publications

(1 citation statement)

References 45 publications

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“…In the flat areas (<15°-25°) of the QinBa, there is a prevalence of cultivated land, experiencing a pronounced impact from human activities (Zhang & Ren, 2016). There is a great difference in altitude between the eastern and western parts of the Qinba (Figure 1), as well as a great difference in the development degree of industry and agriculture (Xiao et al, 2023).…”

Section: Construction Of the Indicator Systemmentioning

confidence: 99%

Quantifying human activity intensity in the Qinling‐Daba Mountains

Xie,

Yao

2024

People and Nature

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Human activities profoundly impact the Earth system such as climate change, biodiversity, disease transmission. Accurately acquiring and assessing the human activity intensity (HAI) is crucial to exploring human‐nature relationships. However, the mismatch of geospatial data products between humans and natural environmental factors is a data bottleneck that restricts the innovation and development of regional human‐Earth systems. Nowadays, some HAI data products exist, such as the global human footprint map and the cumulative human modification map, but their spatial resolution is still too coarse (1 km) for regional research. Importantly, there are limitations to the method of mapping HAI: an incomplete indicator system that ignores the natural dimension makes the assessment of HAI less accurate and comprehensive; ignoring correlations among indicators, subjective weighting method and overlapping indicators lead to potential overestimation of HAI. Here, a new approach to improve the quantification of HAI at the regional scale was presented and the HAI of the Qinling‐Daba Mountains (QinBa) was mapped and analysed as a case study. First. an improved indicator system was constructed from two dimensions: natural environment and resources (including topography and river density), social and economics (including population density, degree of land modification, remoteness from roads/railways, remoteness from settlements and road density). The models for scoring the indicators were then improved. Additionally, principal component analysis was adopted to transform seven indicators into four independent principal components (PCs). The four PCs were combined based on their variance contribution to generate the HAI map, effectively eliminating redundancy and correlation among the indicators. The results showed that the improved method solved the problem of overestimation in previous studies and objectively mapped the HAI of QinBa. We found that although QinBa's HAI was moderate (MHAI = 0.48), places with low HAI were isolated as ‘islands’ by places with high HAI, indicating that the scope of human activities in this area is extensive. This study not only provides novel insights into quantifying HAI but also provides high‐resolution HAI data (100 m) and priority attention zones for human‐nature interaction studies in QinBa, which can help guide policy‐making for management and conservation efforts. Read the free Plain Language Summary for this article on the Journal blog.

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Section: Construction Of the Indicator Systemmentioning

confidence: 99%

Quantifying human activity intensity in the Qinling‐Daba Mountains

Xie,

Yao

2024

People and Nature

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The Spatiotemporal Characteristics and Mechanism of Rural Spatial Shrinkage in Local County, Southeast China

Fan,

Li,

Liu

et al. 2024

Buildings

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The rapid urbanization process has brought about the shrinkage of rural space as a typical issue. Nevertheless, due to the dearth of effective assessment approaches, the patterns of rural spatial shrinkage remain poorly grasped. This study intends to establish a quantitative assessment model to scientifically disclose the spatiotemporal characteristics and mechanisms of rural spatial shrinkage. The “Population-Industry-Function-Land” (PIFL) assessment model has been rigorously constructed, encompassing eight assessment indices, such as the ratio of permanent residents, rural population density, and the rate of abandoned cultivated land. The model was adopted to conduct an analysis of the spatial shrinkage scenarios of the 18 administrative villages in Panxi Town spanning from 2011 to 2021. The results indicate that the temporal dimension of rural spatial shrinkage exhibits an accelerating trend, with discernible declines or increases in the ratio of permanent residents, rate of the elderly labor force, and housing vacancy rate. The shrinkage of rural spaces displays spatial heterogeneity, with more pronounced shrinkage characteristics observed in villages located further from the central town. According to the comprehensive shrinkage index, the villages are categorized into four types: relative shrinkage (0.2447 ≤ Z ≤ 0.2462), mild shrinkage (0.2463 ≤ Z ≤ 0.4423), moderate shrinkage (0.4424 ≤ Z ≤ 0.6125), and severe shrinkage (0.6126 ≤ Z ≤ 0.7988). The research findings possess significant reference value for the governance of rural spatial shrinkage.

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The Imbalanced Pattern of Population and Economy and Its Influencing Factors in the Wumeng Mountain Area

Xuan,

Xudong

2024

Journal of Resources and Ecology

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Spatial Coupling Relationship and Driving Mechanism of Population and Economy in Rural Areas in Qinling-Daba Mountains, China

Cited by 3 publications

References 45 publications

Quantifying human activity intensity in the Qinling‐Daba Mountains

Quantifying human activity intensity in the Qinling‐Daba Mountains

The Spatiotemporal Characteristics and Mechanism of Rural Spatial Shrinkage in Local County, Southeast China

The Imbalanced Pattern of Population and Economy and Its Influencing Factors in the Wumeng Mountain Area

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