Journal of Geographical Sciences ›› 2015, Vol. 25 ›› Issue (12): 1452-1466.doi: 10.1007/s11442-015-1245-0

• Research Articles • Previous Articles     Next Articles

Slope spectrum critical area and its spatial variation in the Loess Plateau of China

Guoan TANG1,2,3, Xiaodong SONG4, Fayuan LI1,2,3, Yong ZHANG5, Liyang XIONG1,2,3   

  1. 1. Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing 210023, China
    2. State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Nanjing 210023, China
    3. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
    4. State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, CAS, Nanjing 210008, China
    5. Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China;
  • Received:2015-04-01 Accepted:2015-06-18 Online:2015-12-31 Published:2016-01-05
  • About author:

    Author: Ren Huiru (1983-), PhD Candidate, specialized in coastal environment and modeling.

  • Supported by:
    National Natural Science Foundation of China, No.41171299, No.41171320, No.41401237


Slope spectrum has been proved to be a significant methodology in revealing geomorphological features in the study of Chinese loess terrain. The determination of critical areas in deriving slope spectra is an indispensable task. Along with the increase in the size of the study area, the derived spectra are becoming more and more alike, such that their differences can be ignored in favor of a standard. Subsequently, the test size is defined as the Slope Spectrum Critical Area (SSCA). SSCA is not only the foundation of the slope spectrum calculation but also, to some extent, a reflection of geomorphological development of loess relief. High resolution DEMs are important in extracting the slope spectrum. A set of 48 DEMs with different landform areas of the Loess Plateau in northern Shaanxi province was selected for the experiment. The spatial distribution of SSCA is investigated with a geo-statistical analysis method, resulting in values ranging from 6.18 km2 to 35.1 km2. Primary experimental results show that the spatial distribution of SSCA is correlated with the spatial distribution of the soil erosion intensity, to a certain extent reflecting the terrain complexity. The critical area of the slope spectrum presents a spatial variation trend of weak-strong-weak from north to south. Four terrain parameters, gully density, slope skewness, terrain driving force (Td) and slope of slope (SOS), were chosen as indicators. There exists a good exponential function relationship between SSCA and gully density, terrain driving force (Td) and SOS and a logarithmic function relationship between SSCA and slope skewness. Slope skewness increases, and gully density, terrain driving force and SOS decrease with increasing SSCA. SSCA can be utilized as a discriminating factor to identify loess landforms, in that spatial distributions of SSCA and the evolution of loess landforms are correlative. Following the evolution of a loess landform from tableland to gully-hilly region, this also proves that SSCA can represent the development degree of local landforms. The critical stable regions of the Loess Plateau represent the degree of development of loess landforms. Its chief significance is that the perception of stable areas can be used to determine the minimal geographical unit.

Key words: digital elevation model, slope spectrum, critical area, spatial variation, independent geomorphological unit, Loess Plateau