Shallow landslide susceptibility mapping: a comparison between logistic model tree, logistic regression, nave bayes tree, artificial neural network, and support vector machine algorithms

• Main Authors: Nhu, V. H., Shirzadi, A., Shahabi, H., Singh, S. K., Al-Ansari, N., Clague, J. J., Jaafari, A., Chen, W., Miraki, S., Dou, J., Luu, C., Górski, K., Pham, B. T., Nguyen, H. D., Ahmad, B. B.
• Format: Article
• Published: MDPI AG 2020
• Subjects: NA Architecture
• Online Access: http://eprints.utm.my/id/eprint/87497/; http://www.dx.doi.org/ 10.3390/ijerph17082749

Shallow landslides damage buildings and other infrastructure, disrupt agriculture practices, and can cause social upheaval and loss of life. As a result, many scientists study the phenomenon, and some of them have focused on producing landslide susceptibility maps that can be used by land-use manage...