Revealing coastal vegetation structural diversity through LiDAR-derived relative entropy

Abstract. Coastal wetlands are among the most valuable ecosystems globally, due to the high ecological function of their structurally complex vegetation communities. However, there remains a lack of vegetation structural complexity (VSC) indicators tailored for coastal wetland applications. Here, we developed a new VSC index, vegetation structure relative entropy (VSRE), based on a measure of the asymmetry of the difference between two probability distributions. While the currently used VSC index all fail to capture the discrete and continuous complexity gradients of coastal vegetation communities, VSRE demonstrated ideal performance in these applications, exhibiting strong robustness across varying point cloud densities. By applying this indicator to 1,337 LiDAR samples of natural coastal vegetation, we used Alpha Earth Foundation data and a deep learning model to create a seamless VSRE spatial map of coastal wetlands in China, with high spatial resolution (10 m) and accuracy (R² = 0.96). VSRE mapping provides crucial ecosystem structural information beyond vegetation classification data and conventional optical indices, highlighting the high spatial heterogeneity of VSC in coastal wetlands. This study offers a valuable foundation for prioritizing conservation areas and enhancing the resolution and accuracy of coastal zone ecological modelling.