Satellite Topographic Mapping in Complex Intertidal Wetlands: A Canopy-Height-Constrained Fusion of ICESat-2 Photon-Derived Structural Samples and Single-Phase Submeter Optical Imagery
High-resolution topographic mapping of intertidal wetlands is essential for geomorphic analysis, yet existing remote sensing methods often struggle with vegetation interference, dependence on dense time-series data, and limited representation of fine geomorphic features. We propose a canopy-height-constrained stratified cooperative inversion framework for the entire intertidal wetland, integrating single-phase submeter optical imagery (Jilin-1), spaceborne photon-counting light detection and ranging (LiDAR) Ice, Cloud, and Land Elevation Satellite 2 (ICESat-2), and machine learning. To accurately construct digital elevation model (DEM) and canopy height model (CHM) training samples in salt-marsh environments, we developed an ATL03 photon-classification workflow combining histogram-based control-point extraction and morphological refinement to generate these samples directly from ICESat-2 ATL03 photons. The retrieved CHM was then introduced as a structural constraint in the DEM retrieval model to support canopy-terrain signal decoupling in vegetated salt-marsh areas. A case study on Chongming Island, Shanghai, China, demonstrated that the DEM retrieval achieved high accuracy on the test set (R ${}^{2} =0.94$ , root-mean-squared error (RMSE) = 0.28 m) and maintained consistent performance against independent UAV-LiDAR validation data (R ${}^{2} = 0.53-0.77$ and RMSE = 0.34–0.53 m). The retrieved 0.5-m DEM reproduced regional elevation gradients, tidal-creek networks, and microtopographic variations across bare flats and vegetated marshes. Shapley additive explanation (SHAP) analysis showed that elevation retrieval over bare mudflats relied mainly on spectral predictors, whereas vegetated areas exhibited a complementary spectral-texture-CHM structure, with CHM consistently ranking as a mid-to-high predictor (fourth–seventh). This further supports the role of CHM as an effective structural constraint. By using only single-phase imagery and ATL03-derived DEM/CHM samples, the framework enables intertidal topographic retrieval that includes vegetated areas. It therefore provides an efficient and low-cost pathway for high-accuracy intertidal topographic monitoring under complex environmental conditions and limited image availability.