Assessing debris flow susceptibility in Heshigten Banner, Inner Mongolia, China, using principal component analysis and an improved fuzzy C-means algorithm

  • Mingyuan Shi
  • Jianping ChenEmail author
  • Yang Song
  • Wen Zhang
  • Shengyuan Song
  • Xudong Zhang
Original Paper


Susceptibility analysis is important in any study of debris flows. Unlike debris flows in Southwest China, debris flows in Northern China occur with different characteristics and much lower frequency. However, neglecting the danger of possible debris flows in this northern area may result in a devastating disaster. In this paper, 12 debris flow catchments located near Zhirui town, in Heshigten Banner, Inner Mongolia, China, were investigated. A geographic information system, a global positioning system, and remote sensing were used to determine geological, topographical, morphological, and vegetation factors of influence. Principal component analysis was carried out to convert this set of possibly correlated factors into a set of values of linearly uncorrelated principal components. The accumulative contribution rate of the first five principal components retained most of the information on these factors, accounting for 90.9 %. An improved fuzzy C-means clustering analysis was applied to determine the susceptibility of debris flows in this area. This method is based on a quantum-behaved particle swarm optimization algorithm, which is an evolutionary algorithm that can achieve global optimization, and is not sensitive to the initial cluster centers. Results showed that the susceptibility levels for four of the debris flow catchments were high, six were moderate, and two were low. Our quantitative assessments based on these nonlinear methods were consistent with field investigations.


Debris flow susceptibility Principal component analysis Quantum-behaved particle swarm optimization algorithm Fuzzy C-means algorithm Debris flow catchments 



This work was supported by the State Key Program of National Natural Science of China (Grant No. 41330636).


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Mingyuan Shi
    • 1
  • Jianping Chen
    • 1
    Email author
  • Yang Song
    • 2
  • Wen Zhang
    • 1
  • Shengyuan Song
    • 1
  • Xudong Zhang
    • 1
  1. 1.College of Construction Engineering, Jilin UniversityChangchunChina
  2. 2.Department of Dermatology and VenereologyFirst Hospital of Jilin UniversityChangchunChina

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