Assessing rural revitalization potential through rural transformation degree and sustainability: A quantitative study of 460 case villages in Lingbao, China

Extensive international experience shows that only villages with sustainable transformation achieve rural revitalization, while those with intense but unsustainable or stagnant transformation struggle to revitalize. However, this cognition lacks robust quantitative substantiation. Therefore, we established a rural revitalization potential assessment framework based on the rural transformation degree and sustainability, employing the Penalty for a Bottleneck (PFB) method and Entropy Function to measure the rural transformation degree and sustainability of 460 villages in Lingbao City, Henan Province, China, from 2000 to 2021, thus evaluating rural revitalization potential. The Mann-Kendall (MK) test was conducted to detect rural transformation thresholds, further quantifying the spatial relationship between rural transformation degree and sustainability through bivariate spatial autocorrelation analysis (BSA). Our findings resonate with the central place theory that villages near those at advanced stages of development struggle to transform sustainably. Additionally, with the optimization of rural population density, and land use structure, these villages demonstrated a discernible upward trajectory in transformation sustainability. Villages with the highest rural revitalization potential were predominantly distributed in the northern of the Yellow River terrace, while those in the southwestern mountainous areas lacked revitalization potential due to low transformation degree. Generally, villages at higher altitudes and steeper slopes exhibited lower rural transformation degree, sustainability, and revitalization potential. With 30 km as the critical point, rural revitalization potential decreased initially and then increased with distance from the county government seat. This study provides essential references for the rational allocation of rural transformation and revitalization resources and for optimizing rural development planning.