Predicting gully initiation: comparing data mining techniques, analytical hierarchy processes and the topographic threshold

@inproceedings{Svoray2012PredictingGI,
  title={Predicting gully initiation: comparing data mining techniques, analytical hierarchy processes and the topographic threshold},
  author={Tal Svoray and Evgenia Michailov and Avraham Cohen and Lior Rokach and Arnon Sturm},
  year={2012}
}
Predicting gully initiation at catchment scale was done previously by integrating a geographical information system (GIS) with physically based models, statistical procedures or with knowledge-based expert systems. However, the reliability and validity of applying these procedures are still questionable. In this work, a data mining (DM) procedure based on decision trees was applied to identify areas of gully initiation risk. Performance was compared with the analytic hierarchy process (AHP… CONTINUE READING

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References

Publications referenced by this paper.
SHOWING 1-10 OF 63 REFERENCES

The analysis of river basins and channel networks using digital terrain data

DG Tarboton, RL Bras, I. Rodriguez-Iturbe
  • TR 326, Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Boston.
  • 1989
VIEW 7 EXCERPTS
HIGHLY INFLUENTIAL

C4.5: Programs for Machine Learning

VIEW 3 EXCERPTS
HIGHLY INFLUENTIAL

Drainage reorganization on an emerged lake bed following base level fall, the Dead Sea, Israel

D Bowman, S Devora, T. Svoray
  • Quaternary International 233: 53–60.
  • 2011
VIEW 1 EXCERPT