Landslide susceptibility assessment using maximum entropy model with two different data sampling methods
By Aiding Kornejady, M. Ownegh, A. Bahremand. 2017
240 citations recorded by the source corpus.
Subfields: Global and Planetary Change, Infectious Diseases, Management, Monitoring, Policy and Law
View Paper: https://www.semanticscholar.org/paper/0c406c61d3ee4b0d545de5b4cce8636ee3352afe
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In Global and Planetary Change
- Ataollah Shirzadi
- Himan Shahabi
- Baharin bin Ahmad
- Khabat Khosravi
- Wei Chen
- Jianquan Ma
- Huichan Chai
- D. Tien Bui
In Management, Monitoring, Policy and Law
- Ataollah Shirzadi
- Himan Shahabi
- Baharin bin Ahmad
- Wei Chen
- Khabat Khosravi
- Jianquan Ma
- Huichan Chai
- D. Tien Bui
Citations in the corpus
- Spatial prediction of landslide susceptibility by combining evidential belief function, logistic regression and logistic model tree (2019, methodology): “After determination of the most effective conditioning factors, EBF model was applied for obtain of landslide susceptibility mapping using the following equation, and finally LSM was divided into five classes, namely very low, low, moderate, high and very high using natural breaks scheme (Kornejady ”