Shallow Landslide Susceptibility Mapping by Random Forest Base Classifier and Its Ensembles in a Semi-Arid Region of Iran

By Viet-Ha Nhu, Ataollah Shirzadi, Himan Shahabi, John J. Clague, Marten Geertsema, Abolfazl Jaafari, Mohammadtaghi Avand, Shaghayegh Miraki, Davood Talebpour Asl, Binh Thai Pham and 2 more. Forests, 2020

108 citations recorded by the source corpus.

We generated high-quality shallow landslide susceptibility maps for Bijar County, Kurdistan Province, Iran, using Random Forest (RAF), an ensemble computational intelligence method and three meta classifiers—Bagging (BA, BA-RAF), Random Subspace (RS, RS-RAF), and Rotation Forest (RF, RF-RAF). Modeling and validation were done on 111 shallow landslide locations using 20 conditioning factors tested by the Information Gain Ratio (IGR) technique. We assessed model performance with statistically based indexes, including sensitivity, specificity, accuracy, kappa, root mean square error (RMSE), and area under the receiver operatic characteristic curve (AUC). All four machine learning models that we tested yielded excellent goodness-of-fit and prediction accuracy, but the RF-RAF ensemble model (AUC = 0.936) outperformed the BA-RAF, RS-RAF (AUC = 0.907), and RAF (AUC = 0.812) models. The results also show that the Random Forest model significantly improved the predictive capability of the RAF-based classifier and, therefore, can be considered as a useful and an effective tool in regional shallow landslide susceptibility mapping.

Subfields: Global and Planetary Change, Management, Monitoring, Policy and Law, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/35234b6d42ba029cd3c64ff84c9ff6c69cf4e52c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Global and Planetary Change

1. Ataollah Shirzadi
2. Himan Shahabi
3. Kamran Chapi
4. N. Al‐Ansari
5. Jie Dou

In Management, Monitoring, Policy and Law

1. Ataollah Shirzadi
2. Kamran Chapi
3. Jie Dou
4. Himan Shahabi

In Mechanical Engineering

1. Kamran Chapi
2. Ataollah Shirzadi
3. Jie Dou
4. Himan Shahabi

Citations in the corpus

• Comparison of Support Vector Machine, Bayesian Logistic Regression, and Alternating Decision Tree Algorithms for Shallow Landslide Susceptibility Mapping along a Mountainous Road in the West of Iran (2020, background): “forest (RF) [64], naïve bayes tree (NBT) [11,15], baysian logistic regression (BLR) [65], Fisher’s linear discriminant function (FLDA) [66], bayes net (BN) [67], grey wolf optimizer (GWO) [68,69], naïve bayes (NB) [70]; naïve Bayes tree (NBTree) [71–73], evidential belief function (EBF) [74], and ke”