Landslide susceptibility mapping using ensemble bivariate and multivariate statistical models in Fayfa area, Saudi Arabia

By Ahmed M. Youssef, Biswajeet Pradhan, Mustafa Neamah Jebur, Hassan M. El-Harbi. Environmental Earth Sciences, 2015

168 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Management, Monitoring, Policy and Law, Safety, Risk, Reliability and Quality

View Paper: https://www.semanticscholar.org/paper/5dab8ad251d507fc3f4d95675ea1412c028b5c1e

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. Haoyuan Hong
2. Wei Chen
3. Qiqing Wang
4. Zhou Zhao
5. Huichan Chai
6. D. Tien Bui

In Management, Monitoring, Policy and Law

1. Haoyuan Hong
2. Wei Chen
3. Qiqing Wang
4. Zhou Zhao
5. Huichan Chai
6. D. Tien Bui
7. Binh Thai Pham

In Safety, Risk, Reliability and Quality

1. Qiqing Wang
2. Zhou Zhao
3. Haoyuan Hong
4. Wei Chen
5. Huichan Chai

Citations in the corpus

• Landslide susceptibility mapping based on GIS and support vector machine models for the Qianyang County, China (2016, methodology): “The area under the curve (AUC) represents the quality of the probabilistic model to reliably predict the occurrence or non-occurrence of landslides (Youssef et al. 2015a, b).”