An improved RSEI-based evaluation for effective forest area by integrating forest structure and quality

Introduction Ecosystem stability confers more abundant and comprehensive ecosystem service values. However, current valuation methods often simplify these ecosystems as undisturbed, ideal, and standardized—neglecting inherent variations in structure and quality—and thereby risk skewing service valuations. Methods We propose a coupled calculation model based on patch stability that integrates land cover dynamics with transitions in the Remote Sensing-based Ecological Index (RSEI). From this model, we derive a novel valuation metric, the Effective Forest Area (EFA). We validate both the model and the metric using Heshan City—a coal mining city facing resource depletion—as a case study. Results Between 2010 and 2020, despite a net increase in total forest area, management practices driven by fast-growing forestry industries degraded the quality of stable forests and resulted in a persistent decline in their extent. Even in regions with intensive ecological compensation, achieving desired restoration outcomes proved challenging, a situation that ultimately reduced the overall function and service value of the regional forest ecosystem. The results show that, compared to the EFA model, traditional calculation methods overestimated the forest ecosystem service value in all regions, with the overestimation being highest in the Spontaneously Developed Rural Area (35%), followed by the Industrial Heritage Tourism Area (29%), and the Urbanization Area (26%). Discussion The EFA model underscores the critical impact of structural and quality changes on ecosystem service value, thereby enabling more comprehensive evaluations—assessments that are essential for developing nature-based solutions and strategies to enhance ecosystem quality.