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August 1, 2026˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciencesOpen Access

Sensitivity of Spaceborne LiDAR, Optical, and SAR Features for Forest Biomass Modelling: A GEDI–Sentinel-2–SAOCOM Analysis

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Authors

EÖEren Gürsoy ÖZDEMİRBartin UniversityÖNÖmer Gökberk NarinAfyon Kocatepe UniversitySASaygın AbdikanHacettepe University

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Implication

Randomized trial evaluates satellite data for biomass estimation in forests, indicating significant nonlinear interactions.

Key Points

  • This research aims to assess the effectiveness of various satellite data sources in estimating aboveground biomass in forests.
  • Utilized 1,356 GEDI L4A footprints as reference data.
  • Incorporated multiple data sources, including GEDI LiDAR, Sentinel-2 bands, and SAOCOM SAR data.
  • Evaluated machine learning models, focusing on feature selection and predictive accuracy.
  • MLP model achieved highest predictive accuracy with R2 = 0.20, RMSE = 62.93 Mg/ha, MAE = 51.31 Mg/ha.
  • Non-linear models outperformed linear models, which had R2 values of 0.15 to 0.16.
  • Red-edge and SWIR bands, along with certain indices emerged as robust predictors over SAR-derived features.

Cite This Study

ÖZDEMİR et al. (2026) studied this question.

synapsesocial.com/papers/6a6d983ee258b358b3c6b653https://doi.org/10.5194/isprs-archives-xlix-b3-2026-1023-2026
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Forest aboveground biomass estimation through integration of sentinel-2 and PALSAR-2 time series: assessing models trained on GEDI and field inventory benchmarks2026 · 4 citations
  2. 2Global Coverage of Sentinel-1 and Spaceborne LiDAR: A Data-Driven Foundation for Forest Height Estimation2026
  3. 3Biomass Distribution Mapping of Boreal Forests using GEDI, Sentinel-2, and SRTM Data2026
  4. 4Synergistic Effects and Differential Roles of Dual-Frequency and Multi-Dimensional SAR Features in Forest Aboveground Biomass and Component Estimation2026
  5. 5Biomass Estimation and Saturation Value Determination Based on Multi-Source Remote Sensing Data2024 · 29 citations