Abstract
As a type of terrain break, the gully shoulder line is of great significance to locate the scope of surface failure and soil erosion. Based on the knowledge of the terrain structure of loess gullies, this paper modeled sight lines to calculate the three-dimensional maximum elevation angle (3D MEA). Then, a critical MEA value of 35° was determined via human vision to extract negative terrain and shoulder lines considering unmanned aerial vehicle (UAV)- and light detection and ranging (lidar)-based digital elevation models (DEMs). In addition to the DEM resolution, the uncertainties caused by the direction number, look distance and skip radius of computer sight were further examined. It was suggested that the process should involve observing at least 12 directions to detect complete information on terrain breaks. The simulation process required a relatively large look distance to analyze global terrain changes because a small distance could limit sight within the local window. The skip radius could result in the process ignoring nearby abrupt changes in terrain, thus causing negative terrain to be misclassified as positive terrain near shoulder lines. The concept of wall morphology was introduced to attribute the critical value to the repose angle of loess gullies. Eventually, the MEA was compared with many other parameters. It could be concluded that the slope is limited to the local scale, while the MEA could combine local and global scales using a large look distance. The hillshade is limited to one viewing direction, but the 3D MEA is a comprehensive layered index from multiple directions. This study is a novel exploration of interdisciplinary hydraulic engineering and information technology. This approach reduces terrain breaks from three-dimensional space into a one-dimensional index and simplifies shoulder lines as a critical 3D MEA value related to loess material properties. This research could be adopted for soil and water conservation.
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