Analysis of Influencing Factors of Ecosystem Service Value Based on Machine Learning—Evidence from the Huaihe River Ecological Economic Belt, China

By integrating multi-source data, this study systematically analyzes the evolution of land use structure, spatiotemporal differentiation characteristics of Ecosystem Service Value (ESV), and core driving mechanisms in the Huaihe River Ecological Economic Belt (HREEB) in eastern China from 2000 to 2020, based on the ESV equivalent accounting model and XGBoost-SHAP coupled framework. The main results are as follows: (1) The land use structure is dominated by cropland, construction land, and forest land. Over the 20-year period, cropland was continuously converted out, primarily transforming into construction land and forest land, while other land types remained relatively stable. (2) Temporally, the total ESV showed a fluctuating downward trend, first increasing and then decreasing from 2000 to 2020. Spatially, the ESV exhibited a corridor effect of “decreasing from the river channel center to both banks”. High-value areas were concentrated in the eastern river–sea linkage zone and the central-western inland rising zone, while extremely low-value areas in 2020 were located in the northern Huaihai Economic Zone (with dense construction land), indicating an overall medium service level. (3) The evolution of ESV was driven by both natural and human factors: among natural factors, water coverage, elevation, and slope had positive effects, while high temperature had an inhibitory effect; among human–economic factors, population density showed an “increase first and then decrease” effect, and urban expansion significantly weakened ESV in the later period. The spatial differentiation presented a pattern of “natural background support in the upper reaches and socioeconomic intervention in the lower reaches”. This study provides a scientific basis for the optimization of territorial space and ecological protection and restoration in the Huaihe River Ecological Economic Belt, and also offers a replicable research paradigm for ecosystem service management in similar river basin-type regions.