Evaluating forest ecosystem services (FES) is crucial for comprehensively recognizing forest value and for formulating targeted forest management plans. However, hurdles persist in traditional FES evaluations that are based on conventional data (e.g., statistical yearbooks and survey data), such as a coarse evaluation scale and difficulty in formulating refined and spatially continuous evaluation results. Forest canopy cover, canopy height, and forest aboveground biomass (AGB) are the core fundamental inputs of a robust FES evaluation. Their accuracy and degree of refinement will influence the final evaluation results obtained. To overcome the above issues, this study first explored accurate estimation methods for all 3 parameters above and then evaluated FES multidimensionally, by using these results combined with other remote sensing products and applying various principles and algorithms. Our results show that a high estimation accuracy (>80%) of the 3 key parameters is achievable for coniferous to broad-leaved forest stands and that FES evaluation results are obtainable with a high resolution and spatial continuity. The service functions, such as nutrient retention, carbon sequestration and oxygen release, and product supply are stronger while others relatively are weaker. It is worth noting that carbon storage by the AGB carbon pool surpasses that of other carbon pools. Finally, the potential of FES varies according to forest type. Compared with broad-leaved forest, coniferous forest has a greater capacity for product supply, windbreak, and sand fixation services. This study offers a methodological reference for the formulation of policies related to the paid use of FES.
CITATION STYLE
Gao, T., Gao, Z., Sun, B., Liu, H., & Wu, Z. (2024). Evaluating Forest Ecosystem Services in the Greater Khingan Mountains Area Using Remote Sensing. Ecosystem Health and Sustainability, 10. https://doi.org/10.34133/ehs.0163
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