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Terrain relief periods of loess landforms based on terrain profiles of the Loess Plateau in northern Shaanxi Province, China

  • Jianjun Cao
  • Guoan Tang
  • Xuan Fang
  • Jilong Li
  • Yongjuan Liu
  • Yiting Zhang
  • Ying Zhu
  • Fayuan Li
Research Article
  • 2 Downloads

Abstract

The Loess Plateau is densely covered by numerous types of gullies which represent different soil erosion intensities. Therefore, research on topographic variation features of the loess gullies is of great significance to environmental protection and ecological management. Using a 5 m digital elevation model and data from a national geographic database, this paper studies different topographical areas of the Loess Plateau, including Shenmu, Suide, Yanchuan, Ganquan, Yijun, and Chunhua, to derive representative gully terrain profile data of the sampled areas. First, the profile data are standardized in MATLAB and then decomposed using the ensemble empirical mode decomposition method. Then, a significance test is performed on the results; the test confidence is 95% to 99%. The most reliable decomposition component is then used to calculate the relief period and size of the gullies. The results showed that relief periods of the Chunhua, Shenmu, Yijun, Yuanchuan, Ganquan, and Suide gullies are 1110.14 m, 1096.85 m, 1002.49 m, 523.48 m, 498.12 m, and 270.83 m, respectively. In terms of gully size, the loess landforms are sorted as loess fragmented tableland, aeolian and dune, loess tableland, loess ridge, loess hill and loess ridge, and loess hill, in descending order. Taken together, the gully terrain features of the sample areas and the results of the study are approximately consistent with the actual terrain profiles. Thus, we conclude that ensemble empirical mode decomposition is a reliable method for the study of the relief and topography of loess gullies.

Keywords

loess gully DEM terrain profile EEMD Loess Plateau 

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Notes

Acknowledgements

This work was funded by the National Natural Science Foundation of China (Grant Nos. 41471316, 41671389, and 41501487) and the Natural Science Foundation of Jiangsu Province (No. BK20161118). The authors are very grateful to the anonymous referees for their comments provided for improvement of the manuscript.

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Copyright information

© Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Jianjun Cao
    • 1
    • 2
  • Guoan Tang
    • 1
  • Xuan Fang
    • 1
    • 2
  • Jilong Li
    • 1
  • Yongjuan Liu
    • 2
  • Yiting Zhang
    • 2
  • Ying Zhu
    • 2
  • Fayuan Li
    • 1
  1. 1.Key Laboratory of Virtual Geographic Environment of Ministry of EducationNanjing Normal UniversityNanjingChina
  2. 2.School of Environment ScienceNanjing Xiaozhuang UniversityNanjingChina

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