Under intensified global climate change and complex land use transitions, the Leaf Area Index (LAI) serves as a key ecological indicator to monitor vegetation responses to natural and anthropogenic factors. This study provided a comprehensive spatiotemporal diagnosis of the LAI and uniquely integrated remote sensing data with the Geodetector model to quantitatively assess both individual and interactive effects of natural and human drivers. Specifically, we analyzed LAI dynamics in the Jinsha River Basin from 2000 to 2023 using Sen’s Slope and Mann–Kendall tests, combined with Geodetector modeling to identify drivers and their interactions. Furthermore, ARIMA-based forecasting offered forward-looking insights to support land use planning and ecosystem resilience. Results revealed a fluctuating upward trend in LAI, with larger areas improving than degrading, and distinct seasonal and spatial patterns, with a notably higher LAI in southern regions. Elevation and temperature were the primary drivers, explaining 57% and 54% of spatial variation, respectively, with their combined effects further enhancing explanatory power. The future LAI trend appeared stable without significant changes. These findings demonstrated LAI’s utility for assessing land use change impacts and ecological sustainability, providing a scientific basis for land use optimization, ecological restoration, and sustainable regional development under the human–earth system framework.

Water, land, energy, and food are fundamental resources for human survival and ecological stability, yet they face intensifying pressure from surging demands and spatial mismatches. Integrated governance of their interconnected nexus is pivotal to achieving sustainable development. In this study, we analyze the water-land-energy-food (WLEF) nexus synergies in China’s North China Plain, a vital grain base for China’s food security. We develop a city-level WLEF evaluation framework and employ a coupling coordination model to assess spatiotemporal patterns of the WLEF system from 2010 to 2022. Additionally, we diagnose critical internal and external influencing factors of the WLEF coupling system, using obstacle degree modeling and geographical detectors. The results indicate that during this period, the most critical internal factor was per capita water resource availability. The impact of the external factor—urbanization level—was characterized by fluctuation and a general upward trend, and by 2022, it had become the dominant influencing factor. Results indicated that the overall development of the WLEF system exhibited a fluctuating trend of initial increasing then decreasing during the study period, peaking at 0.426 in 2016. The coupling coordination level of the WLEF system averaged around 0.5, with the highest value (0.526) in 2016, indicating a marginally coordinated state. Regionally, a higher degree of coordination was presented in the southern regions of the North China Plain compared with the northern areas. Anhui province achieved the optimal coordination, while Beijing consistently ranked lowest. The primary difference lies in the abundant water resources in Anhui, in contrast to the water scarcity in Beijing. Internal diagnostic analysis identified per capita water availability as the primary constraint on system coordination. External factors, including urbanization rate, primary industry’s added value, regional population, and rural residents’ disposable income, exhibited growing influence on the system over time. This study provides a theoretical framework for WLEF system coordination and offers decision-making support for optimizing resource allocation and promoting sustainable development in comparable regions.