Gully erosion is the main cause of global land degradation. The factors controlling gully erosion at watershed scale have been extensively studied, but the spatial pattern of gullies and their primary environmental factors are unclear. In order to explore the primary factors at the regional scale of over thousands of square kilometers, 34 sample areas were selected in northeastern China and 10 environmental factors were proposed. Based on gully interpretations from high-resolution Google Earth images and spatial analysis, kernel density estimation (with polyline features), and correlation analysis, the results show that the maximum kernel density (KD) of the 34 sample areas ranged from 0.11 to 87.16, and there were significant positive correlations between the average KD and the maximum value and standard deviation. At the regional scale, topography (relief amplitude, slope, surface roughness, surface incision, and elevation with correlation coefficients (r) of 0.60, 0.59, 0.57, 0.48, and 0.41 respectively) was the primary environmental factor, with a significant positive correlation with KD. The correlation coefficients of the normalized difference vegetation index (NDVI) (r ¼ 0.32), annual precipitation (r ¼ 0.19), and soil (silt, sand, and clay content with r of 0.139, 0.117, and 0.085, respectively) decreased successively with the KD. At sample area scale, there were six areas with weak correlations between environmental factors and KD, 20 areas with topographic factors, six areas with annual precipitation, and two areas with NDVI as the primary factor. The correlation between soil texture and KD was low. There were different positive or negative correlations between the environmental factors and KD. The spatial distribution of gullies in northeastern China is heterogeneous, and the primary environmental factors were diverse. This study will help to understand the spatial pattern and formation mechanism of gullies at large scale.
Primary environmental factors controlling gully distribution at the local and regional scale: An example from Northeastern China
Year: 2021
