Estimating soil organic carbon density in mangroves of different stand ages using multi-source remote sensing and...

Mangrove ecosystems are highly efficient natural carbon sinks, yet quantifying soil organic carbon density (SOCD) across stand ages is critical for evaluating restoration benefits. This study integrated WorldView-2, LiDAR, and Sentinel-1 SAR data with machine learning to map SOCD in Qinglan Harbor, China. eXtreme Gradient Boosting achieved the highest accuracy (R ² = 0.72, RMSE = 2.87 kg m^-2) among four regression methods. Lasso regression identified LiDAR-derived structural metrics and optical vegetation indices as key predictors, highlighting the importance of 3D canopy structure and spectral data. Results showed age-dependent SOCD accumulation: mangroves older than 15 years stored significantly more carbon (11.47 kg m^-2) than 0-5 year stands (10.49 kg m^-2). These findings underscore the value of long-term restoration for blue carbon sequestration and provide a scalable monitoring framework that integrates multi-sensor remote sensing and machine learning to support coastal management and climate mitigation.