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<p>Quantifying the true surface area of vegetated terrain in mountainous regions is critical for accurate environmental modelling but remains technically challenging. Steep slopes, complex canopy structures, and heterogeneous landforms distort conventional area estimates derived from two-dimensional projections, leading to systematic biases in biomass, carbon, and hydrological assessments. This study introduces a novel three-dimensional framework for surface quantification that integrates satellite-derived elevation, canopy height, and spectral data through adaptation of the SPACEBALL algorithm—a computational geometry approach originally designed for molecular surface analysis. By combining the Copernicus GLO-30 Digital Elevation Model, GEDI LiDAR canopy heights, and Dynamic World land cover classifications, the method constructs a detailed digital representation of forested mountain terrain. Super-resolved Sentinel-2 imagery at 1&#xa0;m resolution further enhances canopy delineation and allows NDVI-based weighting of vegetated surfaces. The integrated model enables terrain- and canopy-aware computation of effective three-dimensional vegetated surface area, capturing the fine-scale variability often overlooked in conventional approaches. The results demonstrate substantial improvements in surface estimation accuracy and highlight the potential of 3D terrain–canopy fusion to support high-fidelity modeling of biomass, carbon dynamics, and ecosystem services in complex landscapes.</p>

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A novel geometric approach to surface area estimation in forested mountain terrain using multi-source elevation and canopy height data

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年8月5日

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  • Ewa Panek-Chwastyk,
  • Mateusz Chwastyk

摘要

Quantifying the true surface area of vegetated terrain in mountainous regions is critical for accurate environmental modelling but remains technically challenging. Steep slopes, complex canopy structures, and heterogeneous landforms distort conventional area estimates derived from two-dimensional projections, leading to systematic biases in biomass, carbon, and hydrological assessments. This study introduces a novel three-dimensional framework for surface quantification that integrates satellite-derived elevation, canopy height, and spectral data through adaptation of the SPACEBALL algorithm—a computational geometry approach originally designed for molecular surface analysis. By combining the Copernicus GLO-30 Digital Elevation Model, GEDI LiDAR canopy heights, and Dynamic World land cover classifications, the method constructs a detailed digital representation of forested mountain terrain. Super-resolved Sentinel-2 imagery at 1 m resolution further enhances canopy delineation and allows NDVI-based weighting of vegetated surfaces. The integrated model enables terrain- and canopy-aware computation of effective three-dimensional vegetated surface area, capturing the fine-scale variability often overlooked in conventional approaches. The results demonstrate substantial improvements in surface estimation accuracy and highlight the potential of 3D terrain–canopy fusion to support high-fidelity modeling of biomass, carbon dynamics, and ecosystem services in complex landscapes.