Using UAS-Based Point Clouds to Generate High Resolution Digital Terrain Model for Forestry Research and Applications*
Abstract
Digital Terrain Models (DTMs) as well as Digital Surface Models (DSMs) have been widely used in many forestry applications, especially in locating forest roads, developing transportation planning, and determining the stand parameters. Generally, LiDAR (Light Detection and Ranging) point clouds have been used to generate DTMs, since LiDAR technology is able to provide multiple returns, which is very useful to separate the ground surface and non-ground objects such as trees, buildings etc. However, LiDAR technology generally requires a high cost and this, of course, has a negative effect on the use of LiDAR point clouds. In this study, the DTM of a study area was generated by means of the point cloud extracted from the aerial images taken from a UAS (Unmanned Aerial System). As the first step, the UAS-based point cloud was filtered to separate the points belong to the ground and non-ground objects. Thereafter, the filtered point cloud was interpolated to obtain the DTM of the study area. Finally, field measurements were conducted by using Real-Time Kinematic GPS (Global Positioning Systems) measurement technique to evaluate the accuracy of the produced DTM. Multiquadratic CRC, CP and CHTS surfaces were used as Q surfaces. Bi-linear surface was chosen as the trend surface when conducting the Multiquadratic interpolation algorithm. Accuracy evaluations revealed that it is possible to generate high-resolution DTMs by using UAS-based point clouds. The results indicated that the CRC and CHTS algorithms provided better results in representing the topography, compared to the CP algorithm.
Keywords
Unmanned Aerial System,Digital Terrain Model,Forestry,Point Clouds,Ground Filtering
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