Coastal salt marshes exhibit strong seasonal variations that may induce subsequent changes in their morphology. However, such changes are insufficiently understood due to a lack of data at seasonal timescales. Knowledge of the seasonal variability is essential for coastal management and ecosystem conservation. Terrestrial laser scanning (TLS) technology allows the rapid acquisition of high-resolution and large-scale vegetation and morphology data with an error of <3 cm. In this study, we used a TLS system to retrieve high-accuracy digital canopy models (DCM) for low vegetation species (approximately 20 cm) Suaeda salsa and digital terrain models (DTM) of a marsh in the Yellow River Delta. We conducted three TLS surveys on the same field on January 5, April 21, and November 20, 2019, which spanned from the dry to wet seasons. The centimeter-scale TLS data retrieved the seasonal variations of vegetation and elevation distributions. The DCMs of the study area showed that the percentages of vegetation-occupied regions were 13.5% and 22.5% in the dry and wet seasons, respectively. The DTMs indicated a net erosion of the study area throughout the year, but at a larger erosion rate in the dry than the wet season, that is, a rate of 2.5 and 0.2 cm/month, respectively. Spatially, regions with vegetation and zones adjacent to creeks underwent slight deposition. We inferred that the larger riverine sediment supply and higher vegetation density in the wet (summer) season mitigated erosion, while the influence of rich sediment supply was crucial. This work demonstrates the applicability of TLS in detecting the distribution of low-height vegetation species, and quantifying vegetation and morphological changes of marshes at seasonal timescales owing to its high resolution.

沿海盐沼表现出强烈的季节性变化，可能引起其形态的后续变化。但是，由于缺乏季节性时标的数据，因此对此类变化的了解不足。了解季节变化对于沿海管理和生态系统保护至关重要。地面激光扫描（TLS）技术可以快速获取分辨率小于3 cm的高分辨率和大规模植被和形态数据。在这项研究中，我们使用TLS系统检索低植被物种（大约20厘米）Suaeda salsa的高精度数字树冠模型（DCM）和黄河三角洲沼泽地的数字地形模型（DTM）。我们于2019年1月5日，4月21日和2019年11月20日在同一领域进行了3次TLS调查，涵盖了从干燥到潮湿的季节。厘米级TLS数据检索了植被和海拔分布的季节性变化。研究区域的DCM显示，在干旱和潮湿季节，植被占用区域的百分比分别为13.5％和22.5％。DTM指示了研究区域全年的净侵蚀，但在干旱时期的侵蚀率比潮湿季节的侵蚀率大，即分别为2.5厘米/月和0.2厘米/月。在空间上，具有植被的区域和邻近小河的区域略有沉积。我们推断，湿季（夏季）较大的河流沉积物供应量和较高的植被密度减轻了侵蚀，而丰富的沉积物供应量的影响至关重要。这项工作证明了TLS的适用性，因为它具有较高的分辨率，因此在检测低高度植被物种的分布以及量化季节性时标中沼泽的植被和形态变化方面具有实用性。