The measurement of surface moisture on beaches is vital for studying aeolian sand transport mechanisms, but existing techniques are not adequate for monitoring the surface moisture dynamics over a substantial beach section. In this study, we investigated the suitability of a new remote sensing method to monitor the spatiotemporal variation in surface moisture on a sandy beach using a long-range static terrestrial laser scanner (TLS). The TLS was permanently deployed on top of a 42 m high building overlooking the study site at Ostend-Mariakerke, Belgium. Considering the effect of target surface roughness on the intensity and the laboratory’s length limitation, a new intensity correction method is proposed which only uses the field point cloud data measured on a homogenous beach surface (without time-consuming indoor experiments). Based on the corrected intensity data, the relation of the beach surface moisture to the corrected intensity was modeled by an exponential model with a correlation-coefficient squared of 0.92. A moisture estimation model was developed which can directly derive the beach surface moisture from the original intensity data of the TLS with a standard error of 2.27%. The hourly surface moisture dynamics across two tidal cycles on the beach were investigated as a case study, in which the point clouds derived from corresponding unmanned aerial vehicle (UAV) imagery are utilized to improve the calculation accuracy of the incidence angles of TLS point clouds at long distances. Results reveal that, after the intensity correction, the long-range static TLS is an extremely suitable technique to monitor the surface moisture dynamics (daytime and nighttime) over a substantial beach section (hundreds of meters) at a high scanning frequency (minutes to hours).

在海滩上测量表面湿度对于研究风沙输送机制至关重要，但是现有技术不足以监视整个海滩上的表面湿度动态。在这项研究中，我们研究了一种新的遥感方法是否适合使用远程静态陆地激光扫描仪（TLS）来监测沙滩上表面水分的时空变化。TLS永久部署在一座高42 m的建筑物顶部，俯瞰比利时Ostend-Mariakerke的研究场地。考虑到目标表面粗糙度对强度的影响和实验室的长度限制，提出了一种新的强度校正方法，该方法仅使用在同质海滩表面上测量的场点云数据（无需进行费时的室内实验）。根据校正后的强度数据，用指数系数为0.92的指数模型对海滩表面湿度与校正后强度的关系进行建模。开发了一个湿度估算模型，该模型可以直接从TLS的原始强度数据中得出海滩表面的湿度，标准误差为2.27％。作为一个案例，研究了海滩上两个潮汐周期的小时表面湿度动态，其中利用来自相应无人机图像的点云来提高TLS点云入射角的计算精度。长距离。结果表明，强度校正后，