China has undergone rapid industrialization and urbanization over the past 40 years. In this process, as a large country with a vast territory and a large population, China’s population development and land utilization have been greatly affected and undergone dramatic changes. In this paper, we mainly discuss the temporal and spatial variation characteristics of land-use efficiency in China from 1991 to 2016 and the regional disparities and explore the impacts of demographic transition on land-use efficiency by employing a STIRPAT model. In terms of space, China’s land-use efficiency has significant agglomeration distribution characteristics and regional inequality, and the degrees of agglomeration and differentiation have gradually become enhanced over time. Our study on the influences of demographic transition on land-use efficiency found a Kuznets curve relationship between the transition of population size and land-use efficiency, as well as between the income level transition and land-use efficiency. Especially, land-use efficiency first increases up to the population threshold of 10,611.877 × 10⁴, then efficiency decreases as the population grows. The overall average population in the whole country is 4117.753 × 10⁴, which is smaller than the identified threshold. Interestingly, the factors influencing land-use efficiency also showed very significant regional disparities. In the eastern region, there is a U-curve relationship between the population employed in secondary industries (ES2) and land-use efficiency. Land-use efficiency decreases down to the ES2 threshold of 343.674 × 10⁴ for the eastern region, whereas the overall average ES2 is 874.976 × 10⁴, indicating that this region has reached the turning point where land-use efficiency will improve as the population employed in secondary industries increases. Meanwhile, the increase in the human capital level was significantly positively correlated with land-use efficiency in the eastern region. For the central region, the transition of the urban–rural population structure (measured by the urbanization rate) significantly increased land-use efficiency. In addition, the results of panel estimation showed a Kuznets relationship between the population employed in tertiary industries (ES3) and land-use efficiency in the western region. Land-use efficiency increases up to the ES3 threshold of 455.545 × 10⁴, and then decreases with an increasing population employed in tertiary industries, whereas the overall average ES3 in the western region is 415.97 × 10⁴, which is smaller than the identified threshold. Policymakers could use these findings to inform rational suggestions with a sound scientific basis regarding the promotion of land-use transition.

The simulation of landscape pattern optimization allocation (LPOA) to achieve ecological security is an important issue when constructing regional ecological security patterns. In this study, an LPOA model was developed by integrating a binary logistic regression model and a nonlinear programming model with a particle swarm optimization algorithm in order to consider the complexity of landscape pattern optimization in terms of the quantitative structure and spatial layout optimization, integrating the landscape suitability and factors that influence landscape patterns, and under constraints to maximize the economic, ecological, and comprehensive benefits of landscape patterns. The model was employed to simulate the LPOA in the Longquanyi District of Chengdu City, Sichuan Province, China. The model successfully obtained an appropriate combination of the landscape quantitative structure and spatial layout, as well as effectively integrating the landscape suitability and factors that influence the landscape pattern. Thus, the model addressed the problems of previous studies, such as neglecting the coupling between quantitative structure optimization and spatial layout optimization, ignoring the macrofactors that affect landscape patterns during optimization modeling, and initializing particles without considering the suitability of the landscape. Furthermore, we assessed and analyzed the accuracy and feasibility of the landscape pattern spatial layout optimization results, where the results showed that the overall accuracy of the optimization results was 84.98% with a Kappa coefficient of 0.7587, thereby indicating the good performance of the model. Moreover, the simulated optimization allocation scheme for the landscape pattern was consistent with the actual situation. Therefore, this model can provide support and a scientific basis for regional landscape pattern planning, land use planning, urban planning, and other related spatial planning processes.

The demographic transition that accompanies the urbanization transformation has a key impact on land use efficiency. This study applies the PVAR, SDM, and threshold models to investigate the influence of China’s demographic dividend composition on urban land use efficiency, aiming to provide guidance for the strategic management and allocation of demographic resources, thereby optimizing urban land resource utilization. The key findings are as follows: (1) Spatial effects reveal that the scale and structural dividends of the population size dividend significantly inhibit urban land use efficiency, whereas the technological dividend of the population quality dividend initially restrains but ultimately enhances it. The combined impact of quantitative and qualitative demographic dividends on land use efficiency is most pronounced in the west and least in the east. High population provinces see significant land use efficiency benefits, contrasting with medium and low population provinces. (2) Both population size and quality dividends exhibit a single-threshold effect on land use efficiency. In summary, cultivating diverse talents with superior technical skills is essential for fostering the upgrade of new industrialization models, ultimately significantly enhancing land use efficiency.