Studying future land use change for sustainable regional development remains a challenging task. Although many previous studies have conducted multi-scenario simulations, research on optimal scenarios that consider the impact of regional policies is relatively limited. In this paper, based on exploring the drivers of land use change, a land value assessment framework that considers the impacts of future land use change is developed by combining multi-objective programming and patch-generating land use simulation models. The framework is useful for predicting land use changes and assessing the ecological and economic values of land in different development strategy contexts (natural development scenario, economic development scenario, ecological protection scenario and green economy scenario). The results show that during the period 1990–2020, the forest area fluctuated greatly. The area of forest initially increased from 249.21 × 104 hm2 to 249.33 × 104 hm2, but then decreased to 248.53 × 104 hm2. Moreover, the model results show that altitude is the main driving force of land use change. By 2035, the economic value under the green economy scenario will be CNY 924.08 × 108, slightly lower than the CNY 938.01 × 108 under the economic development scenario. However, the ecological value under the economic development scenario will drop from CNY 675.43 × 108 CNY in 2020 to CNY 633.56 × 108 in 2025. Therefore, the green economy scenario will be more in line with the development needs of local policies, and the future land use distribution of this scenario can provide reference for regional land planning.

Understanding the relationship between vegetation photosynthesis levels and land use changes is crucial for assessing ecosystem health and plant growth status. Existing studies have not fully considered temporal and spatial dimensions, resulting in an incomplete understanding of the relationship between vegetation photosynthesis levels and land use. Based on solar-induced fluorescence (SIF) data from 2001 to 2022, this study used the Mann-Kendall (MK) test and spatial association analysis to explore the associations between temporal and spatial changes in vegetation photosynthesis levels and land cover change (LCC) in China. The contributions and findings are as follows: (1) A computational framework was utilized to comprehensively measure the spatial correlation between LCCs and chlorophyll levels based on their spatial co-occurrence. (2) The MK test results of the annual and monthly average vegetation photosynthesis levels revealed that most regions in China exhibited increasing trends, accounting for 90.01% and 91.78%, respectively. Moreover, the vegetation photosynthesis levels in western China had a downward trend, indicating that the vegetation ecosystem in this region may be under a certain degree of pressure or may face the risk of degradation. (3) Some economically developed provinces are facing ecological pressures caused by urbanization and industrialization, which have led to the degradation of vegetation ecosystems and a decrease in vegetation photosynthesis levels. (4) Highly supportive areas of the land use–vegetation photosynthesis level association analysis were mainly distributed in grassland and forest areas, indicating the effectiveness of forest protection and grassland management policies. Moreover, the decrease in vegetation photosynthesis mainly occurred in barren areas, illustrating that the management and protection of this type of land still need to be strengthened. These findings underscore the complex interplay between land use and vegetation health, providing insights for sustainable land management policies.