Can slope spectrum information entropy replace slope length and steepness factor: A case study of the rocky mountain area in northern China - Xu, Fujin; Zhao, Weijun; Yan, Tingting; Qin, Wei; Chen, Henan (Catena (Giessen), 2022)
•The calculation method of slope spectrum information entropy is simpler than LS factor.•Slope spectrum information entropy can reflect soil erosion intensity in the rocky mountain area.•The correlation of slope spectrum information entropy with soil erosion intensity was revealed.•Slope spectrum information entropy can replace LS factor to evaluate soil erosion.•The functional relationship model of slope spectrum information entropy and LS factor was built. Slope spectrum information entropy (SSIE) can reflect the overall fluctuation characteristics of the topography with convenient calculation. In order to explore whether the complex slope length and steepness factor (LS factor) can be replaced by SSIE in the evaluation of soil erosion in the rocky mountain area, this study took the rocky mountain area in northern China (the first zone of soil and water conservation) as the research object. The soil texture of study area is the most typical “soil-rock dual structure”. The SSIE, soil erosion intensity (SEI), and LS factor were calculated using ASTER GDEM and Landsat8 image data (30 m × 30 m). The correlation between the SSIE and SEI was revealed, and a functional relationship model of SSIE and LS factor was built. This study clarified whether SSIE could replace the LS factor to evaluate soil erosion in the “soil-rock dual structure” area. The results showed that: (1) The slope spectrum curves of the six secondary zones of soil and water conservation in the study area presented “L” shape, and the SSIE was between 0.59 and 2.79 nat. SEI grades were mainly micro-erosion, with strong erosion and above accounting for 1.7%. The spatial distribution difference was significant and strong erosion and above was mostly distributed in mountainous and hilly areas. The LS factor of the whole region was between 0 and 55.03, with an average value of 1.37. The regions with an average LS factor < 5 accounted for more than 82% in each secondary zone. (2) The significant logarithmic function relationship of SSIE and SEI was displayed on the secondary zone (R2 = 0.9372, P < 0.01), tertiary zone (R2 = 0.7908, P < 0.01), and basin scales (R2 = 0.3534, P < 0.01). (3) The relationship of SSIE and LS factor also was significant logarithmic function on the secondary zone (R2 = 0.7866, P < 0.05), tertiary zone (R2 = 0.8269, P < 0.01), and basin scales (R2 = 0.8958, P < 0.01). It was indicated that in the typical hydraulic erosion areas of “soil-rock dual structure”, SSIE can replace the LS factor to evaluate SEI and soil erosion modulus.