Fractal characteristics of vertical landscape of soil erosion in the Yimeng mountainous area
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Abstract
Taking the Yimeng mountainous area, one of the most representative area of the Rocky Area of Northern China, as a case study, according to the Standards for Classification and Gradation of Soil Erosion (SL190-2007), supported by the technology of GIS and RS and the data of Landsat TM image and relief map, this study aimed to explore the fractal characteristics of the vertical landscape of soil erosion in the Rocky Area of Northern China. The vertical landscape of soil erosion was divided to 16 belts with the elevation range of 50 m. The perimeter-area fractal dimension (D) was calculated by the software of Fragstats ver 3.3, and the landscape stability index (SI) was obtained form D. The results showed that there was obvious variability of the soil erosion landscape in vertical dimension. In the landscape level, D increased dramatically at first and then slightly, while SI decreased quickly at first and then slowly. In the class level, as to the whole study area, the sequence of D values of the soil erosion intensity types from large to small was that of moderate, slight, intense, very intense, sever and minimal. And the sequence of SI was that of minimal, sever, very intense, moderate, intense and slight. With elevation rising, the D value of the soil erosion intensity type of minimal, intense, very intense and the slight in higher elevation tended to increase and the SI vice versa. As to the D and SI of the slight and sever type, the values inclined to reduced, while to the moderate type on the higher elevation, D and SI tended to increase. These indicated that in the lower elevation areas, the human activities disturbed landscape pattern and stability further than natural factors on the higher (intense and very intense) soil erosion intensity landscape types. While in the higher areas, the pattern and stability of the lower (moderate and slight) soil erosion intensity landscapes were impacted greater by natural factors.
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