基于地面约束的滨岸湿地微地貌LiDAR检测研究

 应用激光雷达数据生产高精度的数字地面模型，可为滨岸环境的研究提供精细的微地貌数据。提出用地面特征约束斜率分割区域，对陆面点采用小角度多重迭代分割，提取沟槽特征的方法；设计了一个综合应用斜率分割、密度和反射强度分割、高度分割来提取水下地形、出露沙洲、有水沟槽地等地面特征的技术方案。以佛罗里达州西海岸Citrus County滨岸地带作为研究区域，根据滨岸湿地地面要素在激光雷达点云中的特征，将其划分为滩涂、沟槽、出露沙洲、浅水水下地形，建立了的微地貌地面模型。通过对地面的拟合度检验以及光学影像目视解译对比，证明所采用的分割方法与常规建模方法相比，能更有效的处理地面破碎和水域环境下的点云分割工作，提高了DEM建模精度。

LiDAR Detection Model of Tidal Wetland Microrelief Based on Ground Constraint Conditions

High resolution digital terrain model derived up from LiDAR point clouds can provide more details of microrelief information for tidal wetland environment researches. Tidal wetland microrelief is divided into four components based on LiDAR classification models: underwater points, shoal, bank, and wet or dry ditches.Using ground features as constraint boundary, the foot points of ditches and bank are picked up from a land point cloud with multi iteration classification tools.The reflect intension and point density of LiDAR point cloud are calculated. Using the intension and density threshold values in point cloud classification, shoal, underwater points and wet ditches can be identified.Taking Citrus County, west coast of Florida as a case study, a microrelief DEM is built. A fitting analysis and a flood submergence process are carried out to check up the DEM precision. Comparing with the result of image eyes judgment,the classification model proposed in this paper can generate microrelief DEM with more details than general slope threshold models do.