ORIGINAL RESEARCH article
Front. Environ. Sci.
Sec. Environmental Informatics and Remote Sensing
Volume 13 - 2025 | doi: 10.3389/fenvs.2025.1580169
This article is part of the Research TopicNew Frontiers in Forest Landscape RestorationView all 7 articles
An improved RSEI-based evaluation for effective forest area by integrating forest structure and quality
Provisionally accepted
- China University of Geosciences Wuhan, Wuhan, China
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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. 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. 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%). 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.
Keywords: Anthropic disturbances, Ecosystem Service Values(ESV), Remote sensing-based ecological index (RSEI), Stable Forest, Effective Forest Area(EFA)
Received: 20 Feb 2025; Accepted: 27 Aug 2025.
Copyright: © 2025 Luo, Chai and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Bo Chai, China University of Geosciences Wuhan, Wuhan, China
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