Debris flow hazard assessment based on support vector machine

Lifeng Yuan, Qingfeng Zhang, Wenwen Li, Lanjun Zou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Debris flow hazard assessment is a basic work of hazard monitoring, forecast, alleviation and control. Seven factors, including the maximum volume of once flow (L1), occurrence frequency of debris flow (L2), watershed area (S1), main channel length (S2), watershed relative height difference (S3), valley incision density (S6) and the length ratio of sediment supplement (S9) are chosen as evaluation factors of debris flow hazard degree. Using support vector machine (SVM) theory, 259 basic data of 37 debris flow channels in Yunnan Province are selected as learning samples in this study, then a kind of debris flow hazard assessment model based on SYM is produced. First instance applications gave encouraging results. After Cross Validation test, accuracy of this model came to 70.00%. Through verifying 7 groups of test data, classification accuracy came to 85.71%. The model shows that it has the advantages of best generation, convenience and high precision. SVM is regarded as a broadly applicative tool in debris flow hazard assessment.

Original languageEnglish (US)
Title of host publication2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS
Pages4221-4224
Number of pages4
DOIs
StatePublished - Dec 1 2006
Externally publishedYes
Event2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS - Denver, CO, United States
Duration: Jul 31 2006Aug 4 2006

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)

Other

Other2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS
CountryUnited States
CityDenver, CO
Period7/31/068/4/06

Keywords

  • Debris flow
  • Hazard assessment
  • Support Vector Machine (SVM)

ASJC Scopus subject areas

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

Fingerprint Dive into the research topics of 'Debris flow hazard assessment based on support vector machine'. Together they form a unique fingerprint.

  • Cite this

    Yuan, L., Zhang, Q., Li, W., & Zou, L. (2006). Debris flow hazard assessment based on support vector machine. In 2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS (pp. 4221-4224). [4242231] (International Geoscience and Remote Sensing Symposium (IGARSS)). https://doi.org/10.1109/IGARSS.2006.1083