Strategic Management of Regional Land Carrying Capacity: Evidence from Hubei Province Using an Improved Projection Pursuit Model

Benyan Ren¹Tianshu Shao^1*Yuelong Su^2,3*

• ¹Zhejiang University of Finance and Economics Dongfang College, Haining, China
• ²Central China Normal University, Wuhan, China
• ³Huazhong Agricultural University, Wuhan, China

This study aims to address the challenges of insufficient regional adaptability and complex non-linear relationships in land carrying capacity (LCC) assessment by constructing a comprehensive evaluation framework tailored to geographically diverse regions such as Hubei Province (HP). We developed an improved projection pursuit model optimized by a differential evolution algorithm (DEA-PTM) to evaluate LCC through a four-dimensional system encompassing water and soil resource carrying capacity (WSCC), social carrying capacity (SCC), economic carrying capacity (ECC), and ecological and environmental carrying capacity (EECC). Empirical analysis was conducted using data from HP from 2010 to 2023. An obstacle degree model (ODM) and an autoregressive integrated moving average (ARIMA) model were further integrated to identify limiting factors and predict future trends. The results indicate that the LCC of HP showed a sustained growth trend from 2010 to 2023, with a cumulative increase of 24.7%, and exhibited a distinct "east-high, west-low" spatial pattern. Significant heterogeneity existed among subsystems, with WSCC higher in the east and EECC stronger in the west. Ecological pressure and water-soil resource constraints were identified as the core obstacles to LCC improvement. The ARIMA model predicts a continued increase in overall LCC to 1.671 by 2035, but a decline in EECC, highlighting the risk of ecological degradation. This study provides a scientifically robust framework for regional land resource optimization and sustainable development policy-making.