A Comparative Assessment of Random Forest and k-Nearest Neighbor Classifiers for Gully Erosion Susceptibility Mapping
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Methodology
2.2.1. Gully Dataset
2.2.2. Gully Erosion Geo-Environmental Factors
2.2.3. Gully Erosion Susceptibility Mapping Using Data Mining Methods
Random Forest (RF)
K-Nearest Neighbor (KNN)
2.2.4. Assessment of Data Mining Based Models
3. Results
Validation of Gully Erosion Susceptibility Maps
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Row | Code | Lithology | Geological Age |
---|---|---|---|
1 | Qft2 | Low level pediment fan and valley terrace deposits | Quaternary |
2 | Plc | Polymictic conglomerate and sandstone | Pliocene |
3 | pCk | Dull green grey salty shales with subordinate intercalation of quartzitic sandstone (KAHAR FM; Morad series and Kalmard Formation) | Pre-Cambrian |
4 | Ekgy | Gypsum | Late Eocene |
5 | E2l | Nummulitic limestone | Eocene |
6 | pCmt2 | Low - grade, regional metamorphic rocks (Green Schist Facies) | Pre-Cambrian |
7 | OMql | Massive to thick - bedded reefal limestone | Oligocene-Miocene |
8 | Pd | Red sandstone and shale with subordinate sandy limestone (Dorud Formation) | Permian |
Variable | Importance | |
---|---|---|
KNN | RF | |
Rainfall | 100.00 | 48.74 |
Altitude | 74.35 | 30.46 |
Distance from rivers | 50.64 | 14.95 |
Drainage density | 30.11 | 6.40 |
Distance from road | 19.39 | 18.36 |
Land use | 17.56 | 2.18 |
NDVI | 5.66 | 8.92 |
Slope | 5.63 | 6.32 |
Lithology | 4.54 | 4.07 |
Profile curvature | 1.23 | 2.70 |
Slope aspect | 0.92 | 4.82 |
Plan curvature | 0.00 | 4.94 |
Observation | Predicted | Class Error | |
---|---|---|---|
0 | 1 | ||
0 | 137 | 33 | 0.1941 |
1 | 25 | 145 | 0.1470 |
Node Size | mtry | Trees | Best Tree |
---|---|---|---|
5 | 5 | 700 | 235 |
GPM Zones | RF | KNN | ||
---|---|---|---|---|
Range | Area% | Range | Area% | |
Low | <0.217 | 46.42 | <0.2 | 13.23 |
Moderate | 0.217–0.45 | 15.42 | 0.2–0.5 | 10.83 |
High | 0.45–0.677 | 19.99 | 0.5–0.8 | 42.16 |
Very high | >0.677 | 18.18 | >0.8 | 33.78 |
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Avand, M.; Janizadeh, S.; Naghibi, S.A.; Pourghasemi, H.R.; Khosrobeigi Bozchaloei, S.; Blaschke, T. A Comparative Assessment of Random Forest and k-Nearest Neighbor Classifiers for Gully Erosion Susceptibility Mapping. Water 2019, 11, 2076. https://doi.org/10.3390/w11102076
Avand M, Janizadeh S, Naghibi SA, Pourghasemi HR, Khosrobeigi Bozchaloei S, Blaschke T. A Comparative Assessment of Random Forest and k-Nearest Neighbor Classifiers for Gully Erosion Susceptibility Mapping. Water. 2019; 11(10):2076. https://doi.org/10.3390/w11102076
Chicago/Turabian StyleAvand, Mohammadtaghi, Saeid Janizadeh, Seyed Amir Naghibi, Hamid Reza Pourghasemi, Saeid Khosrobeigi Bozchaloei, and Thomas Blaschke. 2019. "A Comparative Assessment of Random Forest and k-Nearest Neighbor Classifiers for Gully Erosion Susceptibility Mapping" Water 11, no. 10: 2076. https://doi.org/10.3390/w11102076
APA StyleAvand, M., Janizadeh, S., Naghibi, S. A., Pourghasemi, H. R., Khosrobeigi Bozchaloei, S., & Blaschke, T. (2019). A Comparative Assessment of Random Forest and k-Nearest Neighbor Classifiers for Gully Erosion Susceptibility Mapping. Water, 11(10), 2076. https://doi.org/10.3390/w11102076