Integrated and simultaneous mapping of blue carbon ecosystems by using tide-level, phenological, and biophysical features from optical and SAR images

• Simultaneously mapping BCEs containing mangroves, saltmarshes, and intertidal seagrasses. • Integrating phenological, tide-level, and biophysical features to detect multi-temporal and multi-class BCEs. • BCEs classification exceeds 90% accuracy across climates and ecoregions, proving its broad applicability. Blue carbon ecosystems (BCEs) are nature-based solutions critical for mitigating climate change and biodiversity loss. Accurate mapping of BCEs is fundamental to carbon accounting, maximizing their ecosystem service value, and informing conservation and restoration efforts. Yet, most existing studies focus on single ecosystem mapping and lack multi-class classification approaches capable of addressing the spectral similarity among different BCEs. To address this issue, we developed a novel algorithm on Google Earth Engine, namely Multi-class Blue Carbon Ecosystem Mapping by integrating Tide-level, Phenological, and Biophysical features (MBCEM-TPB) to simultaneously map mangroves, saltmarshes, and intertidal seagrass meadows, thereby characterizing the full composition of BCEs. Specifically, we first composited multi-temporal imagery under different tidal levels, phenological stages, and biophysical features from Sentinel-1 and Sentinel-2 data. Based on spectral similarity principles, we performed training sample migration and then generated interannual blue carbon maps for 2019, 2021, and 2023 using Random Forest classifier. The algorithm was evaluated across eight study sites encompassing different BCEs combinations (two or three ecosystem types) spanning diverse climate zones, bioregions, and levels of ecosystem complexity. The overall accuracy of the MBCEM-TPB algorithm exceeded 93.65% across three periods, demonstrating its robustness and generalizability, even in complex intertidal landscapes. This study provides the first unified multi-class classification algorithm for BCEs and offers a generalizable approach applicable at global scales, supporting refined blue carbon accounting and ecosystem management.