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.