Evaluating the scale effect of soil erosion using landscape pattern metrics and information entropy: A case study in the Danjiangkou reservoir area, China

Abstract

The regular patterns of soil erosion tend to change at different scales of observation, affecting the mechanism of soil erosion and its evolution characteristics. This phenomenon has essential scientific significance for the rational allocation of land resources and for studies on sustainable ecosystems. As an important agricultural area in China, Danjiangkou reservoir is threatened by severe soil erosion. In this study, we selected four kinds of landscape pattern metrics, including patch density, fractal dimension, Shannon diversity index, and connectivity, to analyze soil erosion intensity in the Danjiangkou reservoir area at different scales based on landscape ecological principles. In addition, we determine the optimum research scale of the experimental area by calculating the information entropy value of soil patches at different scales. The findings suggest that: (1) the landscape pattern of soil erosion in the experimental area is obviously scale-dependent, and the responses to scale differ from index to index; (2) as the scale of observation increases, the fragmentation of soil patches is weakened, the stability of different landscape components is enhanced, and the soil becomes less vulnerable to erosion; and (3) based on information entropy theory, 60 m is confirmed to be the optimum scale of this study.