Mangrove forests have adapted to sea level rise (SLR) increases by maintaining their forest floor elevation via belowground root growth and surface sediment deposits. Researchers use surface elevation tables (SETs) to monitor surface elevation change (SEC) in mangrove forests, after which this information is used to assess SLR resiliency or to dictate active forest management for vulnerable systems. This method requires significant investments in terms of time and human resources and is limited in the number of points it can measure per plot. We use a low‐cost, portable terrestrial laser scanning (TLS) system to assess SEC for three mangrove forests on Pohnpei Island (Federated States of Micronesia). Cloth simulation filtering was used for ground detection, after which results were refined by filtering points using angular orientation. Digital elevation models then were generated via kriging interpolation for data collected in 2017 and 2019, after which the heights of corresponding points were compared across years. Extreme elevation changes, due to disturbances such as footprints or fallen logs, were removed using interquartile range analysis. The TLS‐obtained average SEC ranged between −6.92 and +6.01 mm, which exhibited an average consistency of 72% when compared to simultaneously collected SET data (root mean square error = 1.36 mm). We contend that this approach represents an improvement over the manual method, where very few points typically are used, that is, ≅ 36 points vs. ≅ 30,000 points in the case of TLS, and could contribute to improved monitoring and management of these rapidly changing forest environments.

中文翻译：

---

使用低成本，快速扫描的地面激光扫描仪评估红树林的表面海拔变化

红树林通过地下根系生长和地表沉积物沉积来维持其林底高度，从而适应了海平面上升（SLR）的增加。研究人员使用地表海拔表（SET）来监测红树林的地表海拔变化（SEC），之后该信息将用于评估SLR的适应力或指示易受害系统的主动森林管理。这种方法需要大量的时间和人力资源投资，并且每个样地可以测量的点数有限。我们使用一种低成本的便携式陆地激光扫描（TLS）系统来评估密克罗尼西亚联邦波恩培岛上三片红树林的SEC。使用布料模拟过滤进行地面检测，然后通过使用角度方向过滤点来精炼结果。然后通过克里格插值法为2017年和2019年收集的数据生成数字高程模型，然后比较多年中对应点的高度。使用四分位间距分析可消除由于足迹或原木掉落等干扰引起的极端海拔变化。TLS获得的平均SEC在−6.92至+6.01 mm之间，与同时收集的SET数据（均方根= 1.36 mm）相比，其平均一致性为72％。我们认为，这种方法是对手动方法的一种改进，该方法通常很少使用点，即TLS为36点，而TLS为30,000点，并且可以有助于改善对这些快速变化的监视和管理森林环境。