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.
Highlights
As a core subject of soil and water conservation research in sustainable ecosystems, soil erosion is affected by various natural and human factors [1,2]
Scale Effects of Soil Erosion Patches Scale effects of soil erosion patches can be explored through analyzing the differences and the change in agricultural tillage method, wherein the high-load and intensive farming style has been transformed to new eco-friendly one, is beneficial to lighten the erosion
The scale response of Perimeter-Area Fractal Dimension (PAFRAC) indicates that the structure of patches tends to suffer higher complexity; the change of CONNECT suggests that the stability of different landscape components is enhanced when the scale is below 150 m, after which the connection of erosion patches is weakened; and the weak scale effect of the Shannon’s Diversity Index (SHDI) index illustrates that, withiSnustthaienasbeililteyc2t0e1d7, 9r,a1n24g3e of scales, nearly no disappearance of patch types occurs
Summary
As a core subject of soil and water conservation research in sustainable ecosystems, soil erosion is affected by various natural and human factors [1,2]. As an important a3reofa15in terms of agricultural and economic production in Hubei Province of China, the Danjiangkou reservoir has process-based soil erosion studies Under this optimum cell size, we intend to explore been thtrheeattiemnee-dscableyesffoeiclt eofrososiiloenro. The first step is to calculate the NDVI (normalized differential vegetation index), which is used for constructing vegetation coverage grid data in ArcGIS from the images; the second step is to generate slope grid data, which is derived from the DEM using the ‘slope’ function in the software These grid data are converted into vectors to be consistent with the land use data. We adopt a method to study soil erosion using a remote sensing monitoring method based on the indicator rules proposed by Zhou in 2005 [31], overlay the vectors of land use, vegetation coverage, and slope data in order to obtain the soil erosion map. Based on the fractal theory and landscape pattern metrics, we treat the soil erosion unit as a patch from the view of landscape ecology, calculating and comparing the landscape pattern metrics at different spatial scales in order to explore and reveal the inherent law of soil erosion change with scale
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