Loess shoulder-line extraction based on bidimensional empirical mode decomposition and edge detection 后印本

摘要: Shoulder-lines are topographic features of loess landforms, and their dynamic changes visually reflect differences in gully erosion status and processes on the Chinese Loess Plateau. Therefore, accurate shoulder-line extraction is important for understanding loess landforms. However, existing extraction methods cannot sufficiently record loess shoulder-line details, reducing extraction accuracy. Based on digital elevation model (DEM) data acquired in 2013 and 2016, this study systematically analyzed the loess shoulder-line morphology in a small watershed on the Chinese Loess Plateau. We integrated theoretical approaches (e.g., signal processing) with bidimensional empirical mode decomposition (BEMD) combined with edge detection (Laplacian of Gaussian (LOG) operator) to automatically extract loess shoulder-lines, and assessed the extraction accuracy through a comparison with three methods (LOG, illumination model, and positive–negative terrain) from existing studies and manual extraction results. The proposed method transformed loess landform research from the spatial domain to the frequency domain. BEMD combined with edge detection effectively revealed shoulder-line features while maintaining the local completeness of shoulder-lines, specifically in areas with high terrain complexity or curvature. The extraction accuracy was 90.11% in the study area, with a mean absolute error (MAE) of 0.8040 m and a median absolute error (MedAE) of 1 m. When applied to different loess landform types, the method demonstrated broad universality and feasibility. The extraction accuracy exceeded 95.00% in the loess tableland watershed, and reached 91.90% in the loess hill watershed. Thus, our proposed method provides a novel perspective for shoulder-line extraction, which can effectively characterize changes in loess landforms at different scales and ensure the automation and high accuracy of shoulder-line extractions. Ultimately, this study is expected to advance gully erosion research on the Chinese Loess Plateau from a frequency-domain perspective.