Journal of Range and Watershed Managment

Evolution the efficiency of Random Forest in Gully erosion susceptibility mapping

Document Type : Research Paper

Authors

Somayeh Movahedi 1
aboalhasan fathabadi
null null 2
Ali Heshmatpour 3

1 شگاه گنبد کاووس

2 null

3 Gonbad

https://doi.org/10.22059/jrwm.2019.263178.1286
Abstract
In this study using Frequency Ratio (FR), Statistical Index (SI), Weights Of Evidence(WOF), Logistic Regression (LR), Random Forest (RF) models the probability of gully formation was calculated in Aytamar watershed and susceptibility maps was prepared. First the thematic maps of 13 gully conditioning factors including lithological formations, distance to faults, faults density, altitude, slope-length, slope angle, slope aspect, plan curvature, profile curvature, distance to roads, land use, distance to rivers, stream power index and topographic wetness index was prepared. Then landslide inventory map was combined with each gully conditioning factor and all models weights and parameters were calculated. Area under curve for test data was calculated as 0.74, 0.78, 0.75, 0.86 and 0.96 for Frequency Ratio (FR), Statistical Index (SI), Weights Of Evidence(WOF), Logistic Regression (LR), Random Forest (RF) models, respectively. Random forest, Frequency Ratio and Logistic Regression have the least the area of high susceptibility zone, respectively. With respect three validation criteria multivariate methods including Random Forest and Logistic Regression had the best performance among all models.

Keywords

Gully erosion
Bivariate
Multivariate Methods
ROC Curve
Aytamar watershed
Journal of Range and Watershed Managment
Volume 72, Issue 1
Spring 2019
Pages 241-261

  • Receive Date 01 August 2018
  • Revise Date 11 June 2019
  • Accept Date 21 June 2019
  • Publish Date 22 May 2019

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