[Background]In studies related to soil and water loss,the primary emphasis is frequently placed on large-scale regional data,presenting a challenge in effectively articulating the specific conditions found in small-scale mountainous areas.Investigating fine-scale conditions in small mountainous regions is of significant practical importance for assessing soil and water loss.[Methods]This study utilized unmanned aerial vehicle(UAV)data to generate high-precision digital elevation model(DEM)and 3D model.Based on DEM data,multiple terrain factors were calculated,and the classification of terrain factors was achieved through correlation analysis and cluster analysis.Subsequently,the selection and weighting of terrain factors were accomplished using the variation coefficient method and principal component analysis,leading to the establishment of a terrain complexity model.Later,a constant offset was introduced and normalized within the terrain complexity model to derive a soil and water loss risk assessment factor model.Finally,validation analysis was conducted by comparing it with 3D model and on-site reconnaissance data.[Results]1)Coefficients for slope,surface incision depth,profile curvature,and plan curvature in the soil and water loss risk assessment factor model were 1.933,0.338,0.206,and 2.633,respectively.2)In the entire study area,the medium risk area accounted for 28.50％,with a dispersed distribution.The very high risk area accounted for 4.42％,concentrated in the south and northwest.Overall,the area was predominantly at a medium to low risk.3)The risk of soil and water loss was higher in regions Fl and F2 due to factors such as steep terrain,low vegetation coverage,and soil desertification.The F3 region exhibited relatively mild soil and water loss due to its flat terrain and extensive cultivation of crops.[Conclusions]The model is capable of accurately delineating areas prone to soil and water loss,providing valuable insights for geoscientific research on soil and water loss and sedimentation in small-scale mountainous regions.
关键词
无人机/地形复杂度/水土流失/相关性分析/变异系数/主成分分析
Key words
UAV/terrain complexity/soil and water loss/correlation analysis/variation coefficient/principal component analysis
维普
万方数据