ISE 2016* Application of an unmanned aerial system to obtain remotely sensed data to derive a high resolution digital terrain model of river topography for use in flow dependent inundation modeling of riparian vegetation and gar (Lepisosteiformes) habitat (#48)
An unmanned aerial system was used to collect 0.20 meter digital imagery over approximately 32 km of the Guadalupe River, Texas. The resulting images were processed to generate mosaics and image-based point clouds. GPS-surveyed ground targets were used to enable accurate georeferencing to a projected coordinate system. The point cloud was classified into ground and non-ground points. An existing USGS DEM was used as a block minimum filter to identify seed points for the ground surface. An adaptive TIN ground filter was then applied to the entire point cloud to iteratively classify ground points in the dataset. A DTM was generated from the classified ground points and the accuracy assessed based on the RMSE of observed (GPS validation points) and coincident DTM-derived elevations. The resulting DTM was compared to an existing 1 meter LIDAR DTM for an overlapping section of the river channel. Model results were integrated with a water surface elevation model for the reach to develop a flow dependent inundation model of gar habitat quantity and quality.
