Amid intensifying global climate anomalies and accelerating urban expansion, land use systems have become increasingly dynamic, complex, and uncertain. Accurately predicting and scientifically evaluating the evolution of land use patterns is essential to advancing territorial spatial governance and achieving ecological security goals. However, most existing land use models emphasize quantity forecasting and spatial allocation, while overlooking the third critical dimension—structural complexity, which is essential for understanding the nonlinear, fragmented evolution of urban systems, thus limiting their ability to fully capture the evolutionary characteristics of urban land systems. To address this gap, this study proposes an integrated SD-PLUS-FD model, which combines System Dynamics, Patch-based Land Use Simulation, and Fractal Dimension analysis to construct a comprehensive three-dimensional framework for simulating and evaluating land use patterns in terms of quantity, spatial distribution, and structural complexity. Wuhan is selected as the case study area, with simulations conducted under three IPCC-aligned climate scenarios—SSP1-2.6, SSP2-4.5, and SSP5-8.5—to project land use changes by 2030. The SD model demonstrates robust predictive performance, with an overall error of less than ±5%, while the PLUS model achieves high spatial accuracy (average Kappa >0.7996; average overall accuracy >0.8856). Fractal dimension analysis further reveals that since 2000, the spatial boundary complexity of all land use types—except forest land—has generally shown an upward trend across multiple scenarios, highlighting the increasingly nonlinear and fragmented nature of urban expansion. The FD values for construction land and cultivated land declined to their historical low in 2005, then gradually increased, reaching their peak under the SSP1-2.6 scenario. Notably, the increase in FD for construction land was significantly greater than that for cultivated land, indicating a stronger dynamic response in spatial structural evolution. In contrast, forest land exhibited pronounced scenario-dependent variations in FD. Its structural complexity remained generally stable under all scenarios except SSP5-8.5, reflecting higher structural resilience and boundary adaptability under diverse socioclimatic conditions. The SD-PLUS-FD model effectively reveals how land systems respond to different socioclimatic drivers in both spatial and structural dimensions. This three-dimensional framework reveals how land systems respond to socioclimatic drivers across temporal, spatial, and structural scales, offering strategic insights for climate-resilient planning and optimized land resource management in rapidly urbanizing regions.

Photovoltaic double-skin façades (PV-DSFs) can block solar radiation heat, mitigate air heat transfer, facilitate ventilation cooling, and generate electricity, making them a high-performance building envelope suitable for hot southern regions in summer. The thermal performance of DSFs is relatively well understood; however, with the addition of photovoltaic glass panels, the influence of design parameters is altered due to thermoelectric coupling effects. Then, the influence of design parameters on their thermoelectric performance remains unclear, hindering their design optimization. This paper establishes a mathematical model for DSFs with MATLAB (R2023a) to analyze their thermoelectric performance and the impact of design parameters. The results indicate that the daily power generation of PV-DSFs is primarily influenced by the solar radiation on the west-facing vertical surface. The wall exterior surface gains heat via longwave radiation during the day and loses heat at night, while convective heat dissipation occurs throughout the entire day, with radiative heat flux being the dominant mechanism. The power generation of photovoltaic cells is significantly influenced by their coverage ratio, while the impact of other factors can be neglected. The temperature of the wall’s exterior surface is significantly influenced by the heat storage of the outer cladding panel, the solar absorptivity of the exterior surface, and the emissivity of the interior surface. Among these factors, the heat storage of the outer cladding panel primarily affects the attenuation and delay of peak values and temperature fluctuations on the exterior surface. Meanwhile, the solar absorptivity of the exterior surface and the emissivity of the interior surface mainly influence the peak temperature of the wall’s exterior surface, with the effect becoming more pronounced when the interior surface emissivity is lower.